Integrated Land Ecosystem - Atmosphere Processes Study

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Land-atmosphere-climate dynamics KEY GAPS

iLEAPS Newsletter Issue No. 7 ◆ June 2009 1 iLEAPS IPO IS iLEAPS Science Plan and Implementation Strategy is SPONSORED BY: available in English and in Chinese. ● University of Helsinki ● Finnish Meteorological Institute ● Ministry of Education, Finland Get your paper copy by contacting [email protected] or download the .pdf files from the iLEAPS web site at: www.ileaps.org

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2 iLEAPS Newsletter Issue No. 7 ◆ June 2009 CONTENTS

Editorial 4

SCIENCE Harmonisation of global land-use scenarios for the period 1500–2100 for IPCC-AR5 6

The role of land surface in the water and energy cycles Modelling land use and land management with the Community Land Model 10 Response of the UK land surface model to precipitation events 14 Evapotranspiration from tropical vegetation 18 The influence of a dry winter on the South-American monsoon 19 Streamflows simulated by ORCHIDEE over the Mississippi river basin 20 Data assimilation: effect of agricultural land-use modifications on surface fluxes 24 Cover photo Cover graphics based on photo taken Hotspots of vegetation-climate feedbacks in European climate scenarios 26 in Yunyang County, Yunnan Province, Southwestern China, 10 November 2002. Ecosystems in the biogeochemical cycles Photo provided by YAN Xiaodong (in photo), Institute of Atmospheric Physics, Nutrient constraints on carbon-climate feedback in an Earth System model 28 Chinese Academy of Sciences, Beijing, China. Topographic controls of CH4 and N2O fluxes from soils in eastern Canada 30 Graphics Ilpo Koskinen, Kimarko. Feedbacks among land surface, aerosols, dust, and trace gases El Niño and fire in equatorial Asia 34 Exchange of organic compounds between the biosphere and the atmosphere 36 iLEAPS Newsletter Amplification of the ‘Dust Bowl’ drought through human-induced land degradation 40 Tree species composition and VOC emissions in Europe during the Holocene 43 SSN Printed version 1796-0363 ISSN On-line version 1796-0401 Microbiological Meteorology 44 For submissions and subscriptions please contact [email protected] Evaluating coupled land-atmosphere models Publisher Combining multi-satellite observations and LSMs to estimate heat fluxes 48 iLEAPS Wetland extent under climate change and future methane emissions 52 International Project Office Erik Palmeninaukio 1 Process-based crop growth within the land-surface model JULES 54 PL 48 Including tropical croplands in a terrestrial biosphere model: West Africa 56 FI-00014 University of Helsinki Effects of agricultural production on regional CO fluxes and concentrations 57 Tel: +358 (0)9 191 50571 2 Fax: +358 (0)9 191 50860 A previously neglected methane source from the Andean páramo?58 [email protected] Monitoring the surface energy balance using remote sensing 60 www.ileaps.org Editorial Panel Group discussions iLEAPS Executive Committee Land-atmosphere feedbacks 62 Editor-in-Chief Land use 63 Anni Reissell Terrestrial biosphere model evaluation 64 Executive Editor ACTIVITIES Tanja Suni NASA-LCLUC meeting on land-cover and land-use change in Monsoon Asia 66 Circulation ACPC Steering Committee/ISSI Team meeting 68 3000 Project highlights: AMMA, GPWG/FIRE, POLARCAT, VOCBAS 70 Printed by J-Paino Oy, Finland Meetings 74 Layout by Ilpo Koskinen, Kimarko, Finland

iLEAPS Newsletter Issue No. 7 ◆ June 2009 3 EditorialEditorial

Guest Editor Nathalie de Noblet-Ducoudré

In recent years, the role land surfaces play in The objective of this Marie Curie – presentations) to try and address all the the climate system has received increasing iLEAPS conference was three-fold: complex aspects of the land-atmosphere in- attention. a) to illustrate our present knowledge on teractions: The scientific articles in this issue of the how land surfaces influence climate ● energy and water cycle iLEAPS Newsletter focusing on land-climate variability and changes through their ● biogeochemical cycles interactions are based on the presentations interactions with the atmosphere, at ● interactions with atmospheric chemistry and working group discussions at the Marie both regional and global scales; and aerosols Curie-iLEAPS Conference Feedbacks-Land- b) to illustrate our present knowledge on ● Climate Dynamics – Key Gaps: Current under- evaluation of models describing the the important feedbacks between the above. standing of how integrated land ecosystem climate system and the land-surfaces; atmosphere processes influence climate dy- Model evaluation still remains one of the c) to list the missing processes/compo- namics. big challenges. The introductory talk by Colin nents that may be involved in important The conference was organised 16–20 Prentice mainly summarised the current un- land-atmosphere feedbacks and that November 2008 in Hyères, France. The event knowns in quantifying the influence of land need to be explored in the near future. was the last one in a series of four Marie in the main biogeochemical cycles (carbon Curie-iLEAPS events taking place in 2007– The workshop was organised in four suc- and nitrogen). In addition, three specific 2008 (www.ileaps.org/marie-curie-ileaps). cessive sessions (combining oral and poster parallel discussion sessions chaired and re-

4 iLEAPS Newsletter Issue No. 7 ◆ June 2009 ➤ Smoke trapped in the nocturnal boundary layer in Rondonia, Brazil. Photo: Andi Andreae.

ported by early-career scientists allowed for vegetation were identified as phenomena Our interpretation is that the conference more interaction among the participants. not sufficiently understood at the moment. was meant to bring together specialists of The discussion sessions were: Acid deposition and the human influence in the land-atmosphere interactions at the ● land use in land-atmosphere interactions it were mentioned as well as the influence of continental to global scale and there are not global warming on wetlands. enough of them working in this field nowa- ● missing feedbacks that need to be quan- days. This is really worrying since the pur- tified Soil-plant interactions and the human in- fluence on the linked carbon-nitrogen-phos- poses of developing such dynamic global ● evaluation of not only our vegetation phorus cycles in plants and soil were also vegetation models, apart from using them models but also of their interactions with considered very important for better de- as diagnostic and impact tools, is to include the atmosphere. scription of carbon, nitrogen, and phospho- more feedbacks in the modelled climate The two main points raised in the Land- rus cycling. system! use group discussion (see page 63) were The Model evaluation group formulated Moreover, although the original goal of land-use transitions and cropland represen- a list of elements important for organised the conference was really to address coupled tation in dynamic global vegetation models and methodical model-data comparisons land-atmosphere studies to better under- (DGVM). (see page 64). The group recommended stand their interactions, more than half of Land-use transitions determine whether writing a review paper on the current state the talks and posters did not report on such forest within a grid box is primary (old- of best available data sets for model evalua- interactions but mainly on influence of ei- growth) or secondary (recovering from tion and encouraging the development and ther land on atmosphere or the reverse in previous human land-use activities). Carbon sharing of “best” data sets by the community. what we refer to as a ‘forced’ mode. This may budgets and physical feedbacks between The Model evaluation group also be the result of the rather recent inclusion of the land and the atmosphere are very differ- stressed the importance of documenting biogeochemical cycles, aerosol production, ent in these two forest types, and the group model processes better to improve under- emissions of biogenic compounds in those concluded that land-use transitions should standing of evaluation results. Closer collabo- models. be included in all DGVM contributing to the ration among modelling groups and be- This special issue gives an overview of IPCC 5th assessment report. tween the measurement and modelling the studies that were illustrated and dis- Several modelling groups throughout communities was also considered important. cussed throughout those four days with its the world are currently developing global In conclusion, the group reiterated the interdisciplinary diversity ranging from hy- cropland parameterisations. However, com- importance of confronting models with ob- drology to biology. pared to the development of DGVMs, servations and that this should be done The iLEAPS and GEWEX Parallel Science progress is slow, and the group suggested early and often. Models must be tested and Conferences with joint sessions to be organ- that although representing crops adequately evaluated in offline, partially coupled, and ised 24–28 August 2009 in Melbourne, would be most useful, it may be appropriate fully coupled modes over short and long Australia also stress the importance of to use the existing parameterisations of time scales and over small and large spatial research on land-climate interactions. This is natural vegetation as much as possible. scales. Experiments should include historical, illustrated by the iLEAPS Science Conference Finally, the Land-use group presented a present-day, and future time periods. sessions and by selected joint sessions, for wish list of datasets for representing land One of the main objectives of the work- example: Surface exchange processes from use in climate models. It included details on shop was to bring together early-career leaf level to Earth System scale (iLEAPS Ses- crop management, irrigation, and fire sup- scientists all working on land-atmosphere sion 1); Progress in land-atmosphere interac- pression. interactions but from different viewpoints: tions and climate change (iLEAPS Session 2); The Feedbacks discussion group (see physics, chemistry, biogeochemistry, and The role of atmospheric boundary layer proc- page 62) came up with a number of candi- biology. The successful discussions we had esses in modulating surface exchanges dates for important processes hitherto omit- proved that we achieved this objective, and (iLEAPS Session 3); Aerosols from the land sur- ted in climate modelling. many participants returned home with face and their interactions with the climate sys- tem (iLEAPS Session 4); Land in the climate The role of micro-organisms in atmos- contact details of potential collaborators. system (Joint Session A). ■ pheric chemistry such as aerosol formation There were quite fewer candidates than and photochemical processes and the role we originally expected: we had planned on of volatile organic compounds emitted by about 90 participants and selected only 55.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 5 George Hurtt is Associate Professor in the Depart- ment of Natural Resources and the Environment and the Institute for the Study of Earth, Oceans, and Space at the University of New Hampshire. He has published on a wide range of topics including the role of disper- sal in the dynamics and structure of plant communi- ties, latitudinal and elevational gradients in bio- diversity, and ocean and terrestrial ecosystem models for use in studies of the global carbon cycle and global climate change. His current research focuses on the development and application of mathematical models to address issues such as the sustainability of land-use practices, the effects of disturbances on ecosystem structure and function, and interactions between the biosphere, hydrosphere, and atmosphere. Harmonisation of global land-use scenarios for the period 1500–2100 for IPCC-AR5

*Authors 4–20 in alphabetical order George C. Hurtt1, Louise P. Chini1, Steve Frolking1, Richard Betts2*, Johannes Feddema3, Guenther Fischer4, Kees Klein Goldewijk5, Kathy Hibbard6, Anthony Janetos7, Chris Jones2, Georg Kindermann4, Tsuguki Kinoshita8, Keywan Riahi4, Elena Shevliakova9, Steve Smith7, Elke Stehfest5, Allison Thomson7, Peter Thornton10, Detlef van Vuuren5 and Ying Ping Wang11

1. Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, New Hampshire, USA 2. Met Office, Hadley Centre, Exeter, UK 3. University of Kansas, Lawrence, Kansas, USA 4. International Institute for Applied Systems Analysis, Laxenburg, Austria, and Graz University of Technology, Graz, Austria 5. Netherlands Environmental Assessment Agency, Bilthoven, the Netherlands 6. National Centre for Atmospheric Research, Boulder, Colorado, USA 7. Pacific Northwest National Laboratory – Joint Global Change Research Institute, College Park, Maryland, USA 8. National Institute for Environmental Studies, Tsukuba, Japan 9. Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA 10. Oak Ridge National Lab, Oak Ridge, Tennessee, USA 11. Marine and Atmospheric Research, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Australia

The evidence is now overwhelming that use activities (crop, pasture, and wood human activity has significantly altered basic This work was coordinated by a joint venture between harvest), some of it multiple times [1]. Agri- element cycles (e.g. of carbon and nitrogen), the Analysis, Integration and Modelling of the Earth cultural land now covers more than a third System (AIMES) core project of the International the water cycle, and the land surface (e.g. Geosphere-Biosphere Programme (IGBP) and the Inte- of the land surface [1,2], and globally there 6 2 vegetation cover, albedo) at regional, conti- grated Assessment Modelling Consortium (IAMC) in are 10–44 · 10 km of land that is recovering nental, and planetary scales, and that these preparation for IPCC-AR5. George C. Hurtt, Louise from previous human land-use activities alterations are influencing the regional and Parsons Chini, and Steve Frolking gratefully acknowl- (“secondary” land) [1]. global environment, including the Earth’s edge the support of a National Aeronautics and Space These land-use changes are estimated to climate system. Administration research grant (NNX07AH32G). Data have added carbon to the atmosphere, products described in this study are available at: During the last 300 years, 42–68% of the http://luh.unh.edu. altered the surface albedo, surface aero- land surface has changed because of land- dynamic roughness, and rooting depth of

6 iLEAPS Newsletter Issue No. 7 ◆ June 2009 vegetation, with resulting changes in re- gional and global water, carbon, and climate. Looking ahead, population and the demand for energy, food, fibre, and water are ex- pected to increase further, placing even greater pressure on the Earth system. In preparation for the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the international community is developing new advanced Earth System Models (ESM) to address the combined effects of human activities (e.g. land use and fossil fuel emissions) on the carbon-climate system. Figure 1. Land-use harmonisation scheme. ➤ In addition, four Representative Concen- tration Pathways (RCP) scenarios of the fu- Figure 2. Flow diagram of inputs, outputs, and model decisions for the global land-use model ture (2005–2100) are being provided by four ➤ Integrated Assessment Model (IAM) teams (GLM) used in harmonisation. to be used as input to the ESMs for future climate projections). The RCPs represent three mitigation pathways (two stabilisation and one overshoot and decline) and one no-policy pathway that continues to in- crease radiative forcing beyond 2100. The diversity of requirements and ap- proaches among ESMs and IAMs for track- ing land-use changes (past, present, and fu- ture) is significant. Moreover, IAM future pro- jections must smoothly transition from the end of historical reconstructions. For these reasons treating land use comprehensively and consistently among these communities in the IPCC exercise (Fig. 1) is an important challenge. As part of an international working group, we have been working to meet these challenges by developing a “harmonised” set of land-use change scenarios. Each harmo- nised scenario smoothly connects spatially gridded historical reconstructions of land use with future projections in a format required by the ESMs. changes for both the carbon cycle and cli- ing differences at the transition between the Previously, we created the Global Land- mate [3]. historical reconstruction ending conditions use Model (GLM) that produced estimates of and IAM initial conditions, and working to ° ° Our new land-use harmonisation strat- 1 x 1 fractional land-use patterns (e.g. crop, egy builds upon the GLM framework by preserve the future changes depicted by the pasture, secondary) and underlying land-use computing enhanced estimates of land-use IAMs at the grid level. transitions annually 1700–2000 [1]. patterns and underlying land-use transitions Fig. 3 illustrates preliminary harmonisa- Land-use transitions describe the annual annually for the time period 1500–2100 at tion time series results based on one of the changes in land use and are important be- 0.5° x 0.5° resolution (Fig. 2). Inputs include IAMs, the IMAGE model, aggregated globally cause changes such as harvesting trees and new gridded historical maps of crop and for the period 1900–2100. establishing or abandoning agricultural land pasture data from HYDE 3.0 1500–2005 [2], The four solid lines in Fig. 3 represent often directly alter land-surface characteris- updated estimates of historical national global time series (1900–2100) for cropland, tics that, in turn, affect energy, water, and wood harvest and of shifting cultivation, and pasture, primary land (natural vegetation carbon exchanges between the land surface future information on crop, pasture, and with no prior land-use history) and second- and the atmosphere. Resulting land-use data wood harvest from the IAMs implementa- ary land. The dashed lines represent global have been successfully used as input to a tions of the RCPs for the period 2005–2100. cropland and pasture time-series (2005– new global dynamic land model (LM3V) Our computational method integrates 2100) from the IMAGE model. The figure able to track the consequences of these these multiple data sources while minimis- shows that the transition from past to fu-

iLEAPS Newsletter Issue No. 7 ◆ June 2009 7 ture is smooth for all land-use categories (cropland, pasture, primary, and secondary) and close to the aggregated results from the IMAGE model (for cropland and pasture). It also shows that the harmonised land-use projections faithfully preserve future crop and pasture land-use changes computed by the IAMs. Fig. 4 summarises corresponding gridded results, and indicates that the har- monisation strategy does a reasonable job of also preserving IMAGE gridded changes, particularly when aggregated to 2° x 2° reso- lution, and at regional scales. Understanding the effects of human ac- tivities on the Earth system requires that the best technical expertise and data on land use be incorporated into the best climate models. Our approach of harmonising the treatment of land use between ESMs and IAMs represents a major advance that will Figure 3. Time series of global area of cropland, nised land-use data (output from GLM) does in- facilitate fuller and more consistent treat- pasture, primary land, and secondary land from the deed transition smoothly from past to future in ments of how both land use and land-use output of global land-use models (GLM) compared 2005 and faithfully preserves global land-use change influence the Earth system, including with IMAGE model (one of the IAMs) inputs. A ma- changes in the IAM land-use data (IMAGE cropland the effects of CO emissions, and corre- jor goal of our harmonisation was to re-grid the and pasture data). Primary and secondary land 2 IAM crop and pasture inputs by applying IAM were computed as part of the GLM. The algorithms sponding gridded land-surface changes that decadal changes to the historical reconstructions used there are one of the key contributions of our potentially have biogeophysical effects. to ensure a smooth transition from past to future work. Preliminary products from this activity in 2005. This figure shows that the global harmo- are currently available; final products will in- clude urban lands, and be finalised using data from all four IAMs later in 2009. Future efforts are necessary to fully implement these products and to integrate ESM and IAM modelling communities even more tightly for future studies of the coupled human-climate system. ■ [email protected]

1. Hurtt GC, Frolking S, Fearon MG, Moore III B, Shevliakova E, Malyshev S, Pacala SW, and Houghton RA 2006. The underpinnings of land-use history: three centuries of global gridded land-use transitions, wood harvest activity, and resulting secondary lands. Global Change Biology 12, 1208– 1229. 2. Klein Goldewijk K and van Drecht G 2006. HYDE 3: Current and historical population and land cover. In: Integrated modelling of global environmental change. An overview of IMAGE 2.4. (Bouwman AF, Kram T, and Klein Goldewijk K Eds.) Netherlands Environmental Assessment Agency (MNP), Bilt- hoven, The Netherlands, 2006. Figure 4. Scatter plot of gridded cropland changes ture changes while ensuring a smooth transition http://www.mnp.nl/hyde in IMAGE (one of the IAMs) data compared with from past to future in 2005—this figure shows that 3. Shevliakova E, Pacala SW, Malyshev S, Hurtt GC, cropland changes in the harmonised dataset (2005 although at 0.5-degree spatial resolution the land- Milly PCD, Caspersen JP, Sentman L, Fisk J, Wirth C, to 2100), at 0.5-degree (grey, n ~ 70,000), 2-degree use changes computed from the harmonisation and Crevoisier C 2009. Carbon cycling under 300 (black, n ~ 5000), and regional (red, n = 24) resolu- strategy do not preserve those provided by the years of land-use changes in the dynamic land tion. Our harmonisation scheme attempts to pre- IAMs, at 2-degree and regional spatial resolutions model LM3V. Global Biogeochemical Cycles (in serve spatial patterns of IAM decadal crop and pas- the land-use changes are preserved well. press).

8 iLEAPS Newsletter Issue No. 7 ◆ June 2009 iLEAPS Newsletter Issue No. 7 ◆ June 2009 9 Sam Levis is a Project Scientist in the Community Land Model (CLM) development and support team and the team’s “scientific liaison” at NCAR. Sam special- ises on vegetation and crop modelling, and his pub- lished work focuses on climate-vegetation interactions using coupled models. He has also studied aspects of land-atmosphere interactions relating to snow, volatile organic compounds, and hydrology. At the moment, Sam directs his attention to land use, land management, and biogeochemistry in Earth System Models. Other than at scientific meetings, Sam talks about his work to high school students, the Colo- rado Public Utilities Commission, science panels visit- ing NCAR, and university departments. He earned a BA in Physics from Cornell University, and an MSc and PhD in atmospheric and oceanic sciences (minor ecology) from the University of Wisconsin-Madison. While in graduate school, Sam worked on a three-month project in Germany at the Potsdam Institute for Climate Impact Research (PIK) with the LPJ (Lund-Potsdam-Jena)-Dynamic Global Vegetation Model group.

Samuel Levis1, Peter E. Thornton2, Gordon B. Bonan1 and Christopher J. Kucharik3 1. Climate and Global Dynamics Division, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA 2. Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA 3. University of Wisconsin, Madison, Wisconsin, USA Modelling land use and land management with the Community Land Model

Global climate models have included pro- Groups developing ESMs cannot neglect management such as crop type, planting, gressively more complex representations of the human footprint on the landscape in harvesting, tillage, fertilisation, and irrigation, the land surface to improve the simulated simulations of historical and future climates. particularly because global-scale datasets of biogeophysics (for instance, transport of wa- Traditionally we have represented this foot- these factors have lagged behind vegetation ter and energy among the atmosphere, land, print with a vegetation category mimicking mapping. and ocean) and biogeochemistry (carbon the behaviour of crops, sometimes using This is beginning to change. Today, we and nitrogen cycles, dust and biogenic emis- grassland or savannah as a proxy for man- are increasingly developing models that will sions). Such coupled systems of increasing aged ecosystems. predict the biogeophysical and biogeo- complexity are referred to as Earth System Most efforts have yet to incorporate chemical effects not only of natural but also Models (ESMs). more explicit representations of land of human-managed land cover [1, 2].

10 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Corn leaf area index (LAI) in Arlington, curves) [11]. Black horizontal lines indicate the the range of maximum observed values quoted in Wisconsin, USA, from a >50-year CN-crop point range of maximum simulated values by AgroIBIS the same study for fertilised and unfertilised corn, simulation driven with observed weather (filled [4]. Red (dash-dot) and blue (dashed) lines indicate respectively.

AgroIBIS is a state-of-the-art land-surface like a grass and distributed spatially accord- mum values of a range similar to the maxi- model with options to simulate dynamic ing to satellite data [6]. mum values observed at this site. The range vegetation [3] and crop life-cycles [4]. CN-crop’s new PFTs (corn, soy, and of maximum LAIs simulated by CN-crop is We have coupled the crop para- wheat) get grid cell coverage from the 1992 also similar to that simulated for this site by meterisations from AgroIBIS directly to the crop dataset of Ramankutty and Foley [7]. the AgroIBIS model (Fig. 1). carbon and nitrogen cycle algorithms (CLM- With guidance from AgroIBIS, we changed a The average annual cycle of the simu- CN [5]) of the Community Land Model ver- variety of parameters to distinguish the lated LAI looks completely different for corn, sion 3.5 (CLM3.5) [6]). We refer to this cou- simulations of corn, wheat, and soy from wheat, and soy relative to that of the grass pling as CN-crop. CLM’s generic crop. We expect to expand and the generic crop PFTs (Fig. 2). In summary, simulated carbon allocation CN-crop to include other crops of global The grass and generic crop grow in the in the plants – in the presence of limited significance, such as rice. natural portion of the model grid cell and nitrogen – determines simulated crop To allow crops to coexist with natural are not subject to human management, growth, leaf area index (sum of leaf area per vegetation in a model grid cell, yet be simu- such as harvest in late summer. Harvest re- unit area of ground, LAI), plant height, and lated separately by a crop and a dynamic moves the vegetation from the landscape at grain harvest. Temperature drives crop life- vegetation model, respectively [8], we sepa- a time that agrees qualitatively with obser- cycle transitions, which affect the plants’ rated the vegetated land unit into two: natu- vations for this site. The model also overesti- simulated carbon allocation and phenology. rally vegetated and human managed. PFTs mates the grass and generic crop LAIs For example, carbon allocation to the in the former share one soil column and throughout the growing season, while simu- crop’s leaf, live stem, fine root, and reproduc- compete for water, while crops in the latter lating quite reasonable LAIs for unfertilised tive pools begins upon leaf emergence and do not share soil columns to permit for dif- and rain-fed corn, wheat, and soy. ends with harvest, but allocation to the re- ferences in management. Methods of imple- With a more accurate representation of productive pool, in particular, happens only menting realistic [9] and prognostic irriga- agricultural landscapes we hope to improve during the last phase of development (from tion (not published), as well as fertilisation, the simulated biogeophysics and biogeo- the beginning of grain fill to physiological have not yet been attempted with CN-crop. chemistry in the CLM. These advances may maturity and harvest). The agreement of preliminary results improve fully coupled simulations with the CLM’s list of plant functional types (PFTs; with observations is encouraging. For exam- Community Climate System Model (CCSM), simple plant categories following general ple, the simulated LAI of corn in Arlington, while helping human societies answer ques- morphological and phenological characteris- Wisconsin, begins to increase every year tions about changing food, energy, and tics) includes a generic crop that is modelled upon leaf emergence and reaches maxi- water resources in response to changes in

iLEAPS Newsletter Issue No. 7 ◆ June 2009 11 Figure 2. 25-year average monthly leaf area index types occupy different parts of the single model the phenologies of corn, wheat, and soy are simu- (LAI) in Mead, Nebraska, USA, from a CN-crop point grid cell in this simulation. The grass and generic lated by CN-crop. simulation driven with observed weather [11]. The crop phenologies (i.e. their periods of greenness grass, crop, corn, wheat, and soy plant functional and dormancy) are simulated by CLM-CN, while

climate, the environment, and land use/ 2000. Testing the performance of a dynamic global 7. Ramankutty N and Foley JA 1998. Characterizing management [4, 10]. Land management ecosystem model: water balance, carbon balance, patterns of global land use: an analysis of global practices available in updated versions of and vegetation structure. Global Biogeochemical croplands data. Global Biogeochemical Cycles 12, CN-crop may include crop rotation, irrigation, Cycles 14, 795–825. 667–685. fertilisation, and tillage. ■ 4. Kucharik CJ and Brye KR 2003. Integrated 8. Levis S, Bonan GB, Vertenstein M, and Oleson KW BIosphere Simulator (IBIS) yield and nitrate loss 2004. The Community Land Model’s Dynamic Glo- [email protected] predictions for Wisconsin maize receiving varied bal Vegetation Model (CLM-DGVM): Technical de- amounts of nitrogen fertilizer. Journal of Environ- scription and User’s Guide. National Center for At- mental Quality 32, 247–268. mospheric Research (NCAR) Tech Note NCAR/TN- 1. Bondeau A, Smith PC, Zaehle S, Schaphoff S, Lucht 5. Thornton PE, Lamarque J-F, Rosenbloom NA, and 459+IA, 50 pp. W, Cramer W, Gerten D, Lotze-Campen H, Müller C, Mahowald NM 2007. Influence of carbon-nitrogen 9. Sacks WJ, Cook BI, Buenning N, Levis S, and Reichstein M, and Smith B 2007. Modelling the Helkowski JH 2008. Effects of global irrigation on cycle coupling on land model response to CO2 fer- role of agriculture for the 20th century global ter- tilization and climate variability. Global Biogeo- the near-surface climate. Climate Dynamics 33, restrial carbon balance. Global Change Biology 13, chemical Cycles 21, GB4018, doi:10.1029/ doi:10.1007/s00382-008-0445-z. 679–706, doi: 10.1111/j.1365-2486.2006.01305.x. 2006GB002868. 10. Lobell DB, Bala G, and Duffy PB 2006. Biogeo- 2. Osborne TM, Lawrence DM, Challinor AJ, Slingo JM, 6. Oleson KW, Niu G-Y, Yang Z-L, Lawrence DM, physical impacts of cropland management and Wheeler TR 2007. Development and assess- Thornton PE, Lawrence PJ, Stöckli R, Dickinson RE, changes on climate. Geophysical Research Letters ment of a coupled crop–climate model. Global Bonan GB, Levis S, Dai A, and Qian T 2008. Im- 33, L06708, doi:10.1029/2005GL025492. Change Biology 13, 169–183, doi: 10.1111/j.1365- provements to the Community Land Model and 11. Qian T, Dai A, Trenberth KE, and Oleson KW 2006. 2486.2006.01274.x. their impact on the hydrological cycle. Journal of Simulation of global land surface conditions from 3. Kucharik CJ, Foley JA, Delire C, Fisher VA, Coe MT, Geophysical Research 113, G01021, doi:10.1029/ 1948 to 2004: Part I: Forcing data and evaluations. Lenters JD, Young-Molling C, and Ramankutty N 2007JG000563. Journal of Hydrometeorology 7, 953–975.

12 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Africa Palaeofire Workshop 26–30 October 2009 Nairobi, Kenya

■ ■ Late-Quaternary sedimentary charcoal This workshop will expand the existing data records are used to explore the linkages coverage of late Quaternary charcoal records among climate, vegetation and humans and from Africa and produce a multi-authored to evaluate components of Earth System paper synthesizing late Quaternary palaeo- Models (ESM). The Global Palaeofire Working fire activity in Africa. Group (GPWG) has created the first Global Charcoal Database (GCD) now being used for regional syntheses and for testing Please contact: hypotheses. The African Palaeofire Workshop Macharia N. Anthony & Mitchell J. Power will train participants in the use and applica- (African Palaeofires Workshop registration) tions of the GCD. Specifically, the goal of this University of Utah workshop is to promote the exchange of Department of Geography information among the fire science commu- Utah Museum of Natural History nity within Africa. 1390 E. Presidents Circle The workshop will explore state-of-the- Salt Lake City, Utah 84112, USA art analytical techniques used in fire history Tel: +1 801 581 6520 reconstructions, and introduce workshop Fax: +1 801 581 8219 participants to palaeofire model simulations. Email: [email protected]

Additional information can be found on the GPWG website: www.bridge.bris.ac.uk/projects/QUEST_IGBP_Global_Palaeofire_WG

iLEAPS Newsletter Issue No. 7 ◆ June 2009 13 Marie-Estelle Demory is a research scientist and a Marie-Estelle’s principal scientific interest is the part-time PhD student at the National Centre for At- hydrological cycle, focusing on precipitation distribu- mospheric Science (NCAS Climate), University of Read- tion in atmospheric models of different resolution. This ing, UK. work contributes to her PhD project, which addresses Since 2005, she has been working within the UK- the role of land surface - atmosphere interactions in Japan Climate Collaboration, a joint project between global climate models. The project focuses on under- NCAS Climate, the UK Met Office and Earth Simulator standing the processes controlling the water cycle Center (Japan). The group is developing a high-resolu- over land, especially the role of soil moisture and its tion climate model. variability in time and space, which is mainly deter- (www.earthsimulator.org.uk) mined by the precipitation distribution.

Marie-Estelle Demory and Pier Luigi Vidale National Centre for Atmospheric Science (NCAS) Climate, Department of Meteorology, University of Reading, Reading, UK Does overestimated canopy interception weaken the UK land surface model response to precipitation events?

Interactions between the land surface and plained by the insensitivity of the boundary ● What are the implications for the land the atmosphere occur at all spatial and tem- layer evolution to soil moisture in the UM, surface state (e.g. soil moisture, photo- poral scales. These interactions are mainly together with an overly high frequency of synthetic activity)? regulated by the amount of radiation re- drizzle rainfall (0–1 mm day-1) [3]. Drizzle In order to remove the feedback proc- ceived at the Earth’s surface and by the hy- leads to relatively constant soil moisture and, esses between the land surface and the at- drological cycle. The atmosphere precipitates consequently, to small variability in evapora- mosphere in the UM, we isolated the land water, which modulates soil wetness, and in tion, which diminishes the impact of land surface model, JULES [4], used in the UM. We return transmits water to the atmosphere surface processes on the atmosphere [3]. forced it, as described below, with observed by soil evaporation and plant transpiration This study is an attempt to understand (CONTROL experiment) and synthetic at- (hereafter ET) (Fig. 1). the mechanisms involved in the land surface mospheric data that re-shape the observed These local interactions strongly depend response to different temporal distributions distribution of precipitation events by, for in- on the location, intensity and frequency of of precipitation. Because of the difficulty in stance, over-weighting high frequency (driz- precipitation. Precipitation, however, is not analysing mechanisms in a coupled land- zle) precipitation, so as to mimic the drizzle simulated properly in climate models [1], atmosphere model, a land surface-only precipitation simulated by the UM (SMOOTH and models disagree on the land surface - model (JULES) driven (forced) by meteoro- experiment). atmosphere coupling strength, the degree logical data is used in this study. We show here two of the simulations to which these two components influence The scientific questions addressed in our performed over the Alpine region for one each other [2]. study are: year after reaching equilibrium (via a ~25- An example is the UK - Met Office ● Is the land surface model used in the UM year spinup). general circulation model (GCM), the Unified sensitive to precipitation frequency and Model (UM). The UM is a fully coupled ocean 1. CONTROL: JULES is forced with the 3- intensity? - atmosphere - land surface model in which hourly meteorological data used in the the land surface - atmosphere feedback is ● What are the mechanisms involved in Global Soil Wetness Project GSWP2 [5]. The weak compared to that simulated by other the land surface response to drizzle pre- forcing data are the observed air tempera- models [2]. This deficiency has been ex- cipitation events? ture and humidity, wind, radiation, surface

14 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. A schematic diagram of the different sources of evaporation over a vegetated surface: soil evaporation, plant transpiration and evapora- tion from canopy interception (also called canopy evaporation).

In JULES, the canopy capacity is para- meterised as 0.5+0.05 · LAI (Leaf Area Index; the total leaf area per unit surface area), which is much larger than in most other land surface models (0.1 · LAI for SiB [6] and NCAR-LSM [7], 0.2 · LAI for CLASS [8]). This implies that JULES exaggerates the average interception of rainfall by leaves, especially if precipitation is in the form of drizzle. Changing this expression to 0.1 · LAI in the new CONTROL (called CONTROL_CAN) and SMOOTH (called SMOOTH_CAN) experi- ments (Fig. 2) has a beneficial effect on the partitioning of total evapotranspiration. ET contributes to 78% of the total evapo- transpiration in CONTROL_CAN (55% in SMOOTH_CAN) and evaporation from canopy interception to 17% in CONTROL- _CAN (39% in SMOOTH_CAN), although the mean total evapotranspiration does not change. In SMOOTH_CAN the plants are also more active than in SMOOTH, due to deep pressure, rainfall and snowfall rates for the This is because the consistently exaggerated soil moisture recharge in spring (Fig. 3). chosen year of 1983. evapotranspiration, together with the drizzle The new canopy capacity also has an 2. SMOOTH: To mimic drizzle precipita- precipitation, has not allowed sufficient impact on the amplitude of the seasonal tion events as simulated in the UM, each springtime recharge of deep soil moisture, cycle of soil moisture. In the CONTROL ex- GSWP2 forcing field listed above is averaged causing a peak-summer soil water deficit, periment, the amplitude is 139 mm. In the monthly, based on 3-hourly data to conserve and preventing plants from transpiring SMOOTH experiment, the amplitude is lower the diurnal cycle. Within a month, the model (Fig. 3). (126 mm); reducing the canopy capacity therefore receives the same amount of rain, The principal component of total evapo- amplifies it by 15% in SMOOTH_CAN (145 radiation, wind, etc., each day. The seasonal transpiration in the SMOOTH experiment is mm), and by 3% in CONTROL_CAN (143 cycle is also conserved. the evaporation from canopy interception mm). For reference, the multi-model ensem- Each grid point (112 over the domain) is (about 55%), while the CONTROL experi- ble GSWP2 data predict a soil moisture sea- considered independent, as if there were ment has a dominant ET (about 70%). sonal cycle amplitude of about 190 mm. 112 meteorological stations. In this summary, Although CONTROL is more realistic, the re- These results show that the combination of the results are presented for the entire do- sults still differ considerably from the multi- an overly large canopy interception capacity main, by taking an average of all grid points. model ensemble GSWP2 data, where ET and the overestimation of drizzle precipita- Total evapotranspiration (ET plus evapo- contributes to 82% of total evapotranspi- tion strongly affects the land surface state. ration from canopy interception) is generally ration and evaporation from canopy inter- Our study provides additional insight larger in the SMOOTH experiment than in ception to 16% over the same alpine do- into the causes for the poor land surface- the CONTROL experiment (Fig. 2), especially main. atmosphere coupling in the Unified Model in early summer. This result is consistent with The evaporation from canopy intercep- [2]. Evaporation of canopy interception is the UM (coupled) past simulations, which pro- tion is controlled by interception of precipi- fastest process involved in the water ex- duced too much evapotranspiration over tation by leaves, a function of the canopy changes between the land surface and the land [3]. capacity (mm), which is the maximum atmosphere, as it has an immediate re- However, in July the total evapotranspi- amount of water necessary to saturate the sponse that does not depend on the state of ration in SMOOTH is less than in CONTROL. canopy before the water falls over. soil, nor on the state of vegetation.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 15 Figure 2. Annual cycle of total evapotranspiration plus transpiration (ET) (green) for the CONTROL, with a new canopy capacity) experiments. The (blue), in mm day-1, partitioned into evaporation CONTROL_CAN (CONTROL with a new canopy ca- fields are averaged over the Alps (2-17.5E/42.5- from canopy interception (red) and soil evaporation pacity), SMOOTH and SMOOTH_CAN (SMOOTH 49N).

If the response in evaporation is domi- land-atmosphere interactions. As this is espe- 1. Randall DA et al. 2007: Climate Models and Their nated by evaporation of rain from canopy cially true for drizzle precipitation, decreasing Evaluation. In: IPCC 2007. Climate Change 2007. The interception, as is the case in JULES, the state the role of canopy interception is very likely Physical Science Basis. Contribution of Working of soil and vegetation has very little influ- to strengthen the land surface -atmosphere Group I to the Fourth Assessment Report of the ence on the atmosphere. By decreasing the coupling strength in the UM, which simu- Intergovernmental Panel on Climate Change [Solo- role of this process in JULES, we showed that lates too much drizzle precipitation [3]. After mon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, and Miller HL (eds.)]. Cam- soil moisture increased and its seasonal cycle further investigation, we plan to integrate bridge University Press, Cambridge, United King- was amplified, giving more weight to the soil these modifications into the UM to investi- dom and New York, NY, USA, 996 pp. evaporation and transpiration response. gate the feedback processes and possible 2. Koster RD, Dirmeyer PA, Hahmann AN, Ijpelaar R, impacts on precipitation. ■ Plant activity in our results indicated that Tyahla L, Cox P, and Suarez MJ 2002. Comparing deep soil moisture, involving longer-term the degree of land-atmosphere interaction in four processes, also plays an increasing role in the [email protected] atmospheric general circulation models. Journal of Hydrometeorology, 3, 363–375. 3. Lawrence DM and Slingo JM 2005. Weak land- atmosphere coupling strength in HadAM3: Role of soil moisture variability. Journal of Hydrometeoro- logy, 6, 670–680. 4. Best M 2005. JULES Technical Documentation. Met Office, Joint Centre for Hydro-Meteorological Re- search, Wallingford, UK. 5. GSWP2: Global Soil Wetness Project http://www.iges.org/gswp/ 6. Sellers PJ, Randall DA, Collatz GJ, Berry JA, Field CB, Dazlich DA, Zhang C, Collelo GD, and Bounoua L 1996. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: model formu- lation. Journal of Climate, 9, 676–705. 7. Bonan GB 1996. A Land Surface Model (LSM ver- sion 1.0) for ecological, hydrological and atmos- pheric studies: technical description and user’s guide. National Center for Atmospheric Research (NCAR) Technical Note NCAR/TN-417+STR. Na- tional Center for Atmospheric Research, Boulder, Colorado. 150 pp. 8. Arora VK and Boer GJ 2002. A GCM-based assess- Figure 3. 1-year time series of monthly total soil (blue), CONTROL_CAN (grey) and SMOOTH_CAN ment of the global moisture budget and the role moisture (mm day-1) averaged over the Alps (2- (light blue) experiments. of land-surface moisture reservoirs in processing 17.5E/42.5-49N) for the CONTROL (black), SMOOTH precipitation. Climate Dynamics, 20, 13–29.

16 iLEAPS Newsletter Issue No. 7 ◆ June 2009 iLEAPS Newsletter Issue No. 7 ◆ June 2009 17 Figure 1. The 21 tropical eddy-covariance measuring sites.

Joshua B. Fisher School of Geography and the Environment, Environmental Change Institute, University of Oxford, Oxford, UK Evapotranspiration from tropical vegetation

Tropical vegetation is a major source of glo- tion could not predict, followed by the Nor- bal land-surface evapotranspiration, and can malised Difference Vegetation Index (NDVI, thus play an important role in global hydro- 9%), precipitation (6%), and wind speed logical cycles and global atmospheric circu- (4%). lation [1, 2, 3]. Accurate prediction of tropical Overall, the radiation-based evapotran- evapotranspiration (evaporation from sur- spiration models performed best for three faces and transpiration by plants) is critical to reasons: our understanding of these processes under 1) evapotranspiration was largely unaffect- the changing climate. ed by atmospheric turbulent transfer, We examined the controls on evapo- especially at the wetter sites; transpiration in tropical vegetation at 21 2) the difficulty of characterising canopy pan-tropical eddy-covariance sites (Fig. 1), and stomatal resistance (water vapour conducted a comprehensive and systematic transfer in canopy and at leaf surface) evaluation of 13 evapotranspiration models consistently in the highly diverse vege- (based on radiation, temperature, or atmos- tation hindered the resistance-based pheric transfer/resistance) at these sites, and models; 1. Larson K, Hartmann DL, and Klein SA 1999. The assessed the ability to scale up model esti- 3) the temperature-based models captured role of clouds, water vapor, circulation, and bound- mates of evapotranspiration for the test ary layer structure in the sensitivity of the tropical the variability in tropical evapotranspira- region of Amazonia. climate. Journal of Climate 12, 2359–2374. tion inadequately. Net radiation turned out to be the 2. Numaguti A 1993. Dynamics and energy balance strongest determinant of evapotranspiration Finally, we evaluated the potential to of the Hadley circulation and the tropical precipi- (average evaporative fraction, the ratio of predict regional evapotranspiration for one tation zones: significance of the distribution of evapotranspiration to net radiation, 0.72) and test region: Amazonia. We estimated the evaporation. Journal of Atmospheric Science 50, explained 87% of the variance in monthly evapotranspiration for the whole Amazonia 1874–1887. evapotranspiration across the sites. Vapour- to be 1370 mm yr-1. ■ 3. Werth D and Avissar R 2004. The regional evapo- pressure deficit was the strongest predictor transpiration of the Amazon. Journal of Hydro- (14%) of the residual variation that net radia- [email protected] meteorology 5, 100–109.

18 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Anna Sörensson1, Claudio Menendez1 and Patrick Samuelsson2 1. Centro de Investigaciones del Mar y la Atmósfera (CIMA), University of Buenos Aires, Buenos Aires, Argentina 2. Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden The influence of a dry winter on the development of the South-American monsoon

In this sensitivity study, we used the Rossby tions over the whole continent. Members of Centre regional atmosphere model RCA3 [1] each ensemble differed only in initialisation modified by including the surface database dates. Ecoclimap and by adjusting the atmospheric Our study covered the monsoon of only physics to improve the performance of the one summer, from August 1992 to March model for tropical and subtropical climates 1993. However, the surface and dynamical (RCA3-E). The continental model domain processes of SAMS act independently of the had a horizontal resolution of 0.5º and 24 large-scale conditions [3, 4] and could there- levels in the vertical. fore be similar in other summers. Our results In the tropical and subtropical South showed that soil moisture anomalies induce America, a warm-season precipitation maxi- both large-scale and local precipitation re- mum associated with the South American sponses. Monsoon System (SAMS) dominates the The difference between the wet and seasonal precipitation cycle. The ongoing dry ensemble in the partitioning of surface deforestation in South America can decrease fluxes (the relationship of latent heat flux to soil moisture in the region which, in turn, can sensible heat flux) induced a large difference potentially modify the monsoon rainfall. between the ensembles in air column tem- Previous studies of the effect of modified perature over the central part of Amazonia. soil moisture on SAMS have led to quite op- In the dry ensemble, the continental air posite results [2, 3]. On the one hand, a dryer temperature was higher and brought in soil can lead to higher air column tempera- stronger Atlantic trade winds over the north- tures because evapotranspiration (latent ern part of the continent that were blocked heat flux; evaporation from surfaces and and turned anti-clockwise to the south by transpiration by plants) decreases and, there- the Andes mountains. Moisture convergence fore, a larger portion of outgoing energy will for dry initial conditions was therefore larger be in the form of warm air rising (sensible than for wet conditions east of the northern heat flux). This increases the thermal gradi- Andes and in southern Amazonia, producing 1. Kjellström E, Bärring L, Gollvik S, Hansson U, Jones ent between the continent and the ocean more rainfall over these regions during C, Samuelsson P, Rummukainen M, Ullerstig A, which can produce stronger inflow of the spring (Sep-Oct). Willén U, and Wyser K 2005. A 140-year simulation Atlantic trade winds over the continent, In summer (Dec-Jan), precipitation was of European climate with the new version of the bringing moisture to the monsoon region stronger in the wet ensemble than in the Rossby Centre regional atmospheric climate model and producing an early onset of the dry one in central Amazonia. Because no dif- (RCA3). Reports Meteorology and Climatology 108, monsoon. On the other hand, some studies ference was observed in moisture conver- Swedish Meteorological and Hydrological Institute, [e.g. 2] have shown that destabilisation of gence (a large-scale phenomenon) in this re- Norrköping, Sweden, 54 pp. the atmosphere through latent heat flux in- gion among the two ensembles, an explana- 2. Fu R and Li W 2004. The influence of the land fluences the large-scale circulation triggering tion could be local precipitation recycling: surface on the transition from the dry to wet the inflow of trade winds. A dry disturbance the region remained wetter since springtime season in Amazonia. Theoretical and Applied resulting in weaker latent heat fluxes may, precipitation was similar in both wet and dry Climatology 78, 97–110. therefore, lead to a later onset of the ensembles although the soil moisture condi- 3. Collini EA, Berbery EH, Barros VR, and Pyle ME 2008. monsoon. tions differed. How does soil moisture influence the early stages We explored the influence of anomalous Our results are only preliminary. A more of the South American monsoon? Journal of soil moisture in late austral winter on the thorough analysis on different time scales is Climate 2, 195–213. development of SAMS through two ensem- in progress. ■ 4. Fu R, Zhu B, and Dickinson RE 1999. How do bles of simulations. The first ensemble was atmosphere and land surface influence seasonal initialised with extremely dry and the other changes of convection in the tropical Amazon? one with extremely wet soil moisture condi- [email protected] Journal of Climate 12, 1306–1321.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 19 Matthieu Guimberteau is a PhD student at the Laboratoire de Météorologie Dynamique (LMD), an Institut Pierre-Simon Laplace (IPSL) laboratory in the University of Pierre & Marie Curie in Paris. His main research subjects are continental water balance and the influence of irrigation on thermal and water budgets over the main irrigated river basins world- wide. His experience in land surface models (LSM) started during his internship in the same laboratory working in a project developing the irrigation module in LSM ORCHIDEE. Matthieu has an education in vegetation biology, ecology, and general functioning of the continental biosphere.

Matthieu Guimberteau1, Katia Laval1, Alain Perrier2 and Jan Polcher1 1. Laboratoire de Météorologie Dynamique, Centre National de la Recherche Scientifique (CNRS), Paris, France 2. AgroParisTech, Unité de Formation et de Recherche (UFR) Physique de l’Environnement, Paris, France Streamflows simulated by ORCHIDEE over the Mississippi river basin: sensitivity to the forcing resolution and parameters

The variability and uncertainties of regional putes the hydrological exchanges between In each sub-basin, the water is routed water resources can be studied using land the soil, the vegetation and the atmosphere. through three reservoirs which do not inter- surface models (LSM). In order for the mod- The routing module that routes all the water act with the atmosphere: els to give reasonable results, we need a simulated by the model from the land 1) the slow and deep reservoir where the good understanding of the simulated proc- surface scheme to the outlet of the rivers drainage (water moving downward from esses. River discharge is a crucial variable to was activated in the model. surface water to groundwater) is an in- LSMs because it integrates all the large-scale The routing module of ORCHIDEE has put, hydrological processes on land surface. been described in [2] and is based on a 2) the fast reservoir where the runoff (por- Therefore, it is very useful for model valida- parameterisation of the lateral waterflow on tion against many available observations. tion of incoming water (such as precipi- a global scale [3]. Given the global map of tation and irrigation) not infiltrating in In this study, we tested the ability of LSM the main watersheds [4, 5] which delineates the soil but discharged from the area) is ORCHIDEE (ORganising Carbon and Hydrol- the boundaries of sub-basins (one of several an input, and ogy In Dynamic EcosystEm) to simulate basins that form a watershed) and gives the 3) the stream reservoir. streamflows (the amount of water flowing in directions of water flow, the total runoff a river; the main mechanism by which water simulated by ORCHIDEE is routed to the All these three reservoirs then flow into moves from the land to the oceans) with ocean (without anthropogenic uptakes such the stream reservoir of the next sub-basin two atmospheric input datasets (forcings) as irrigation). The resolution of the basin downstream. The reservoirs are characterised differing in resolution. map is 0.5° x 0.5° and we can have more by their time constants which have been ORCHIDEE is composed of three compo- than one basin in ORCHIDEE grid cell (sub- calibrated over the Senegal river basin only nents but only SECHIBA (Schématisation des basins) and the water can flow either to the [2], at a resolution of 1°. The time constant EChanges Hydriques à l’Interface Biosphère- next sub-basin within the same grid cell or determines how quickly the water is routed Atmosphère) [1] is used in this study; it com- to the neighbouring cell. through each reservoir.

20 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Monthly mean streamflows (m3 s-1) at observations and from different simulations. Left: NLDASslw simulations. Right: comparison between Vicksburg station for the period 1997–1999 from comparison between observations, NLDAS, and observations, NCC, and NLDASslw-tc.

The “slow reservoir” has the highest time Precipitation Climatology Project [8,9]) ob- We compared NCC and NLDAS data to constant (25 days) in order to simulate the served precipitation (average annual differ- observations by FLUXNET, a global network groundwater. The time constant of the “fast ence < 5%). However, we noticed large varia- of biosphere-atmosphere flux measure- reservoir” is lower (3.0 days) because it re- tion in radiation between the NCC and ments [10], over seven stations across USA tains the water of runoff which flows faster. NLDAS datasets: the average annual differ- during 1997 to 1999. We found a good The “stream reservoir”, which represents all ence was about 21% for short-wave and 8% agreement between NCC short-wave radia- the water of the stream, has the lowest value for long-wave radiation. tion and FLUXNET observations whereas (0.24 days). Those figures are the same for all the basins of the world. Our study focused on the Mississippi river basin in USA. We compared our streamflow simulations results with data ob- tained from databases of the University Cor- poration for Atmospheric Research (UCAR) (http://dss.ucar.edu/datasets/ds552.1/) and the United States Geological Survey (USGS) (http://waterdata.usgs.gov/nwis/sw) during the period 1997–1999. The results were ana- lysed for Vicksburg which is usually used as a reference station for the Mississippi river basin because it is near the outlet of the river. The two atmospheric data sets used as input to ORCHIDEE were NCC [NCEP (Na- tional Centers for Environmental Prediction) / NCAR (National Center for Atmospheric Re- search) Corrected by CRU (Climatic Research Unit)] [6] and NLDAS (North American Land Data Assimilation System) [7]. They include numerical model outputs and observations of meteorological variables such as precipita- tion, incident radiation, wind, and humidity. NLDAS has a higher longitude-latitude resolution (0.125°) than NCC (1°). The precipi- tation forcing of the two data is very similar Figure 2. Time series of monthly mean streamflows 1999, from observations, NCC, and NLDASslw-tc. over the basin and close to GPCP (Global (m3 s-1) at Vicksburg station, for the period 1997–

iLEAPS Newsletter Issue No. 7 ◆ June 2009 21 1. Ducoudré N, Laval K, and Perrier A 1993. A new set of parameterizations of the hydrologic ex- changes and the land–atmosphere interface within the LMD atmospheric global circulation model. Journal of Climate 6, 248–273. 2. Ngo-Duc T, Laval K, Ramillien G, Polcher J, and Cazenave A 2007. Validation of the land water stor- age simulated by ORganising Carbon and Hydrol- ogy In Dynamic EcosystEms (ORCHIDEE) with Gravity Recovery And Climate Experiment (GRACE) data. Water Resources Research 43, W04427, doi:10.1029/2006WR004941. Figure 3. Time series of monthly mean streamflows four LSMs (colours, left) [11], and ORCHIDEE (dashed 3. Hagemann S and Dümenil L 1998. A parameteri- (m3 s-1) at Vicksburg station for the period October pink, right). zation of the lateral waterflow on the global scale. 1997 – September 1999, from observations (black), Climate Dynamics 14, 17–31. 4. Vörösmarty CJ, Fekete BM, Meybeck M, and Lammers R 2000. Global system of rivers: its role in NCC long-wave radiation was systematically divided by a factor 10 (“NLDASslw-tc” ex- organizing continental land mass and defining underestimated compared to FLUXNET data. periment). land-to-ocean linkages. Global Biogeochemical Moreover, we found that the NLDAS short- The results of NLDAslw-tc were remark- Cycles 14, 599–621. wave data was systematically overestimated ably better than those of NLDASslw: the and the long-wave radiation even more un- 5. Oki T, Nishimura T, and Dirmeyer P 1999. Assess- maximal amount of water stored in the ment of annual runoff from land surface models derestimated than that of NCC. In order to stream reservoir during summer in using Total Runoff Integrating Pathways (TRIP), have the same amount of energy in both NLDASslw was largely reduced and shifted Journal of the Meteorological Society of Japan 77, datasets, we corrected the radiation of to the spring season. This shift also moved 235–255. NLDAS. the maximum peak of streamflow to May 6. Ngo-Duc T, Polcher J, and Laval K 2005. A 53-year The streamflow simulated with NLDAS instead of June/July, closer to the observed forcing data set for land surface models. Journal of forcing without the radiation correction one (March) (Fig. 1 right). Geophysical Research 110, D06116, doi:10.1029/ (“NLDAS” simulation) pointed out discrepan- This remaining time lag of two months 2004JD005434. cies with observations at Vicksburg over the can be explained by the variability of the http://hydro.iis.u-tokyo.ac.jp/~thanh/wiki/ mean period 1997–1999. There was a pro- results during the three years (Fig. 2). In fact, index.php?n=Main.NCCDataset nounced time shift in seasonality: ORCHIDEE the pronounced underestimation of the 7. Cosgrove BA, Lohmann D, Mitchell KE, Houser PR, simulated maxima of streamflow during peak flow simulated by ORCHIDEE in March Wood EF, Schaake JC, Robock A, Marshall C, Shef- summer (June/July) whereas the observa- 1997 together with the large overestimation field J, Duan Q, Luo L, Higgins RW, Pinker RT, Tarpley tions showed a maximum in March (Fig.1 in May 1999 (Fig. 2) explains the result ob- JD, and Meng J 2003. Real-time and retrospective left). The streamflow simulated with NCC tained for the mean period 1997–1999. We forcing in the North American Land Data Assimi- forcing (“NCC” simulation) was much more conclude that re-calibrating the time con- lation System (NLDAS) Project. Journal of Geo- realistic with a peak flow occurring in May stants is necessary when using a forcing physical Research 108, 8842, doi:10.1029/ (Fig. 1 right). resolution higher than 1° x 1° with the rout- 2002JD003118 http://ldas.gsfc.nasa.gov/ Correcting the radiation in the NLDAS ing scheme of ORCHIDEE. 8. Huffman R, Adler F, Rudolf B, Schneider U, and dataset (“NLDASslw” experiment) led to a Finally, we compared our results with Kehn PR 1995. Global precipitation estimates decrease in evapotranspiration and, conse- streamflow simulations performed by four based on technique for combining satellite-based quently, to a better mean annual discharge, other LSMs at Vicksburg (Fig. 3) [11]. The estimates, raingauge analyses and NWP model in- but the time shift in seasonality did not im- studied period was the same as ours (Octo- formation. Journal of Climate 8, 1284–1295. prove (Fig. 1 left). Therefore, we chose to ber 1997 – September 1999) and all the 9. Global Precipitation Climatology Project. evaluate the influence of the reservoir time models were forced by NLDAS with no ra- http://cics.umd.edu/~yin/GPCP/main.html constants on streamflow seasonality. diation correction. Therefore, we left the ra- 10. Baldocchi D, Falge E, and Gu L 2001. FLUXNET: A The time constants used in ORCHIDEE diation correction out from our simulation as new tool to study the temporal and spatial vari- were originally calibrated during experi- well and kept only the calibration of the ability of ecosystem-scale carbon dioxide, water ments with a resolution of 1° [2]. time constant of the stream reservoir and vapor, and energy flux densities. Bulletin of the In our NLDAS experiment, we applied the routing time step of ORCHIDEE. The four American Meteorological Society 82, 2415– 2434. LSMs exhibited large variations (Fig. 3); the the same time constants in the model to a 11. Lohmann D, Mitchell KE, Houser PR, Wood EF, ° much higher resolution (0.125 ). As a result, streamflow simulated by ORCHIDEE was in Schaake JC, Robock A, Cosgrove BA, Sheffield J, the stream reservoir stored much more good agreement with observations. Leaving Duan Q, Luo L, Higgins RW, Pinker RT, and Tarpley water in the NLDAS experiment than in the out the radiation correction actually im- JD 2004. Streamflow and water balance NCC one. In order to correct this, we imple- proved ORCHIDEE results. This was most intercomparisons of four land-surface models in ■ mented two changes: the time constant of likely because of compensating errors. the North American Land Data Assimilation Sys- the stream reservoir and the time step of tem project. Journal of Geophysical Research 109, the routing scheme of ORCHIDEE were both [email protected] D07S91, doi: 10.1029/2003JD003517.

22 iLEAPS Newsletter Issue No. 7 ◆ June 2009 The Earth System Science Partnership (ESSP) consists of four international global envi- ronmental change research programmes: DIVERSITAS, IGBP, IHDP, and WCRP. The aim of ESSP is to strengthen the cooperation amongst these programs to allow greater integration across disciplines, environment and development issues and the natural and social sciences. See for more information: www.essp.org A new ESSP Joint Project on Global Environmental Change and Human Health (GECHH)

Human activities increasingly affect the and complex linkages between global structure and functioning of ecosystems. In environmental†change (including climate turn, these changes can influence the entire change, land and sea use change, global chain of factors involved in the infectious biodiversity loss and change, global socio- disease cycle: pathogens, vectors, reservoir economic change) and human health. species, and human populations. Seemingly However, as yet, little systematic research has unrelated human activities can thus have been undertaken on the many important serious consequences for human diseases, aspects of this topic. Nor has there been both infectious and non-infectious. The any sustained attempt to establish an inter- scientific community recognises the growing national research community. need to better understand the multi-faceted

ESSP’s response 2. Describe spatial (geographic, intra/inter- population) and temporal differences With its wide network of scientists involved in health risks, to better understand in Global Environmental Change (GEC) vulnerabilities and priorities for inter- research, ESSP is well positioned to take up ventions this challenge. This Joint Project is being developed in partnership with the World 3. Develop adaptation strategies for reduc- Health Organisation (WHO). ing health risks, assess their cost-effec- tiveness, and communicate results (espe- The Project’s main research goals are to: cially to decision-makers) 1. Identify and quantify health risks posed 4. Foster research training programs, to by GEC, now and in the reasonably boost networked international research foreseeable (scenario) future capacity in GEC and human health ❏ Develop methods of modelling/under- standing tradeoffs between economic development, environmental change Co-Chairs, Global Environmental Change and and human health Human Health: ❏ Take account of the roles of culture, ● Prof. Ulisses Confalonieri, National School social institutions and technology of Public Health, Brazil choices in modulating health risks, affecting vulnerability and influencing ● Prof. Mark Rosenberg, Queens University, policy response Canada

See brochure for more information: www.essp.org/fileadmin/redakteure/pdf/others/GECHH_BrochureIHDP_OM.pdf

iLEAPS Newsletter Issue No. 7 ◆ June 2009 23 Rice field in northern Thailand. Photo: Tanja Suni.

Dominique Courault1, Emmanuel Kpemlie1, Rachid Hadria1, Aline Bsaibes1, Samuel Buis1, Albert Olioso1 and Olivier Hagolle2 1. National Institute of Agronomic Research of France (INRA), Avignon, France 2. Centre National d’ Etudes Spatiales (CNES), Toulouse, France Data assimilation: effect of agricultural land-use modifications on surface fluxes and microclimate

Evapotranspiration (evaporation from sur- landscape heterogeneity. The developed remote sensing images in the solar domain faces and transpiration by plants) and model combines a “Big Leaf” formulation of [3]. On the other hand, some important char- microclimate depend on feedback effects the surface fluxes (the whole vegetation is acteristics such as the soil moisture in the between the land surface and the atmos- approximated as one big “leaf”) and a sim- root zone and the aerodynamic roughness phere and on the spatial and temporal vari- plified representation of the atmospheric are impossible to determine directly. To solve ability of surface characteristics. Therefore, boundary layer [2]. It can predict the evolu- this problem, we implemented a meteoro- land-use modifications such as crop rotation tion of microclimate and land-surface fluxes logical method of variational data assimila- and reduction or increase of irrigation may such as evapotranspiration throughout the tion (VDA) [4] into PBLs. have a significant effect on regional climate day. In the VDA method, we defined a cost and water resources. The PBLs model considers the heteroge- function “J” that included observed surface

In order to determine such dependen- neity of the land surface by dividing the area temperatures Ts (from thermal infrared cies and to predict microclimate and land- in patches (“tiled approach”), each with par- images), a priori information (deduced from surface fluxes, we developed a coupled plan- ticular characteristics of main vegetation. climatology or expert knowledge) of the de- etary boundary layer – land-surface model Some of these, such as the leaf area index sired parameters (aerodynamic roughness (named PBLs [1]) which takes into account (LAI) and albedo, can be estimated from and soil moisture), and information of meas-

24 iLEAPS Newsletter Issue No. 7 ◆ June 2009 urement errors. The VDA method minimised J and obtained values for aerodynamic roughness and soil moisture by adjusting them until the observed Ts and the Ts esti- mated by PBLs were consistent. These values were then included in the patch characteris- tics in PBLs. An intensive experiment was conducted in 2006 over the Crau-Camargue region in south-eastern France with numerous ground and airborne measurements [1]. Among the various satellite data re- corded during this period, 32 FORMOSAT-2 images were acquired from March to Octo- ber with a time step of 3 days at a spatial resolution of 8 m, which allowed us 1) to derive accurate information of the vegeta- tion structure such as LAI and fcover (the fraction of green vegetation covering a unit area of horizontal soil) for the patches [5] and 2) to detect the main agricultural practices such as the cut dates of irrigated meadows [1]. In order to estimate evapotranspiration in the region, we mapped the spatial vari- ability of LAI and agricultural practices and used them as input data into two model types: a) the PBLs model with and without VDA and b) a crop model STICS [6] which takes into account the spatial variability of agricultural practices and predicts some future scenarios in case they are modified (used as input to PBLs if no measurements are available). Finally, we compared the evapotranspiration estimates from PBLs and from PBLs+VDA to measurements and found that PBLs+VDA gave better estimates (Fig. 1). Figure 1. Model estimates of evapotranspiration 26 Mar 1997 (bottom) 18 Apr 1997. Root mean The simulated surface fluxes by (latent heat flux LE) compared to measurements square error (RMSE) is given for PBLs only and for PBLs+VDA showed great spatial variation over wheat crops in Alpilles – ReSeDA region. (top) PBLs+VDA. because of differences in soil moisture and surface roughness - both highly dependant on the agricultural practices performed in 1. Courault D, Bsaibes A, Kpemlie E, Hadria R, Hagolle 4. Bouttier F and Courtier P 1999. Data assimilation the region. We concluded that 1) even at a O, Marloie O, Hanocq JF, Olioso A, Bertrand N, and concepts and methods. European Centre for Me- small scale, different crop types and agricul- Desfonds V 2008. Assessing the potentialities of dium-Range Weather Forecasts (ECMWF) Mete- tural practices induce significant variations FORMOSAT-2 data for water and crop monitoring orological Training Course Lecture Series, 59 pp. both on temperature and surface fluxes; 2) at small regional scale in south-eastern France. 5. Bsaibes A, Courault D, Baret F, Weiss M, Olioso A, in order to accurately assess their influence Sensors 8, 3460–3481. Jacob F, Hagolle O, Marloie O, Bertrand N, Desfond V, on climate and agricultural production, 2. Brunet Y, Nunez M, and Lagouarde JP 1991. A and Kzemipour F 2009. Albedo and LAI estimates detailed information of the agricultural simple method for estimating regional evapo- from FORMOSAT-2 data for crop monitoring. practices is necessary. transpiration from infrared surface temperature Remote Sensing of Environment 113, 716–729. At the moment, coupling between our data. International Journal of Photogrammetry 6. Brisson N, Mary B, Ripoche D, Jeuffroy MH, Ruget F, two models is passive (output of crop model and Remote Sensing 46, 311–327. Nicoullaud B, Gate P, Devienne-Barret F, Antonioletti STICS is used as input for PBLs). However, 3. Weiss M, Baret F, Leroy M, Hautecoeur O, Bacour C, R, Durr C, Richard G, Beaudoin G, Recous S, Tayot X, development of a more integrated approach Prévot L, and Bruguier N 2002. Validation of neural Plenet D, Cellier P, Machet JM, Meynard JM, and is in progress. ■ net techniques to estimate canopy biophysical Delecolle R 1998. STICS: a generic model for the variables from remote sensing data. Agronomie 22, simulation of crops and their water and nitrogen 547–553. balances. I. Theory and parameterization applied to [email protected] wheat and corn. Agronomie 18, 311–346.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 25 Anna Wramneby obtained her MSc in physical ge- ography from Lund University, Sweden in 2000. After a break of a few years, she returned to Lund and the Department of Physical Geography and Ecosystems Analysis, within the Geobiosphere Science Centre, to continue her scientific career. Anna started her current PhD work in 2004 under the supervision of Dr. Benjamin Smith, Dr. Patrick Samuelsson, and Prof. Martin T. Sykes. Her project involves the coupling of regional climate modelling and dynamic ecosystem modelling to investigate potential feedback mecha- nisms between the atmosphere and the terrestrial biosphere within the scope of regional climate change. She has now reached the fourth and final year of her PhD research.

Anna Wramneby1, Benjamin Smith1 and Patrick Samuelsson2 1. Geobiosphere Science Centre, Department of Physical Geography and Ecosystems Analysis, Lund University, Lund, Sweden 2. Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden Hotspots of vegetation-climate feedbacks under future greenhouse forcing in Europe

Coupled processes and mechanisms linking atmospheric and terrestrial ecosystem dy- namics play an important role in climate change, since interacting feedbacks have the potential both to amplify and dampen the magnitude of a change. Studies using Earth System Models (ESM), in which a global cir- culation model (GCM) is coupled to a model of terrestrial biogeochemistry and land sur- face dynamics applied at the global scale have demonstrated that changes in climate can lead to vegetation and carbon cycle changes that may, in turn, significantly modify the climate. Climate scenarios for the coming century point towards a northward expansion of boreal forests into tundra [1] and a possible partial deforestation in parts of the tropics [2]. Both of these phenomena are likely to play an important role in global climate change because of the resulting reduction in albedo (ratio of solar radiation reflected by a surface (clouds, snow, forest, ocean) to in- coming solar radiation) at high latitudes and Figure 1. Differences in forest cover between the period (1961–1990) in RCA-GUESS, indicating a the reduction in hydrological cycling in the scenario period (2071–2100) and the control future increase in forest fraction.

26 iLEAPS Newsletter Issue No. 7 ◆ June 2009 tropics. Although these feedbacks have been described at continental to global scales us- ing global models, the underlying processes are local to regional in character and are also likely to play an important role in regional climate change. Here we describe a regional “Earth Sys- tem” model, RCA3-GUESS; the product of coupling a regional climate model, RCA3 [3], with a process-based model of vegetation dynamics and ecosystem biogeochemistry, LPJ-GUESS [4]. The coupled model is applied under an emission scenario for the coming century to investigate feedbacks of vegeta- tion changes on the climate of Europe. LPJ-GUESS continuously updates RCA3 with daily values of leaf area index (leaf area per unit ground area, LAI) and the distribu- tion of different types of vegetated surfaces influencing the albedo, hydrological cycling, Figure 2. Winter albedo feedback showing the dif- etation dynamics). Positive values indicate a smaller and energy partitioning at the land surface. ferences in the albedo anomalies of the scenario albedo decrease (north-western Russia - deciduous The advantage of this type of a coupled period (2071–2100) and the control period (1961– tree fraction increases) and negative values an model approach is that the combined effect 1990) between RCA-GUESS (vegetation dynamics accentuated albedo decrease (Fennoscandian of the models is regional and dynamic, included) and standard RCA (only climate, no veg- Mountains – tree line advance). which in this particular study has enabled the identification of four potential regions/ In contrast to the albedo-related warm- vestigated feedbacks. We believe that our hotspots of vegetation-climate feedbacks in ing in the Fennoscandian mountain range, findings will be of general interest since veg- Europe. north-western Russia is characterised by a etation-climate feedbacks have been recog- The two northerly hotspots in the strong negative temperature feedback. In re- nised to play an active role in climate Fennoscandian Mountains and in north- ■ sponse to the initial CO2 forcing and warm- change. western Russia are dominated by the effect ing effect, the broadleaved, deciduous trees of the reduced albedo; feedbacks at the become relatively more abundant in the for- [email protected] southerly ones are related to decreasing est at the expense of conifers. The implica- evapotranspiration (the southerly sites are to tion of this is that the forest loses its dense 1. Bonan GB, Pollard D, and Thompson SL 1992. Ef- be investigated further). structure which, in turn, increases the albedo fects of boreal forest vegetation on global climate. Although the future carbon dioxide all year round. The net effect in this area is Nature 359, 716-718. (CO ) forcing overall leads to a warmer cli- 2 still an albedo reduction but a smaller one 2. Cox PM, Betts RA, Jones CD, Spall SA, and Totterdell mate, the albedo reduction has a sharply than in the Fennoscandian Mountains. This IJ 2000. Acceleration of global warming due to contrasting influence on temperature in the weakening of the albedo reduction is most carbon-cycle feedbacks in a coupled climate two northern hotspots via its effect on veg- notable in winter since there is less masking model. Nature 408,184–187. etation dynamics. Below, we explain how. of snow beneath a broadleaved deciduous 3. Kjellström E, Bärring L, Gollvik S, Hansson U, Jones RCA-GUESS simulates a treeline advance canopy (Fig. 2). C, Samuelsson P, Rummukainen M, Ullerstig A, in the Fennoscandian Mountains (Fig. 1). This Our results suggest that an albedo-re- Willén U, and Wyser K 2005. A 140-year simulation result is in agreement with many other stud- lated positive warming feedback in parts of of European climate with the new version of the ies of future warming, in which boreal forests northern Europe is rather modest compared Rossby Centre regional atmospheric climate model expand northwards into tundra [1]. The to the global greenhouse forcing. This is in (RCA3). Swedish Meteorological and Hydrological simulated successional order of the plant apparent disagreement with studies sug- Institute (SMHI) Reports Meteorology and Clima- functional types (PFT) involved agrees well gesting that albedo shifts related to affores- tology 108, SMHI, Norrköping, Sweden, 54 pp. with documented life history strategies of tation (planting forest to areas originally 4. Smith B, Prentice IC, and Sykes MT 2001. Represen- pioneer versus successional tree species without forest) and greening could signifi- tation of vegetation dynamics in modelling of Eu- from real plants and ecosystems [5]. cantly offset gains through enhanced car- ropean ecosystems: comparison of two contrasting Additional warming in boreal and tem- bon sinks [6]. approaches. Global Ecology and Biogeography 10, perate regions is likely to be attributed to The two contrasting albedo responses of 621–638. the feedback between decreasing albedo the Fennoscandian Mountains and north- 5. Loehle C 2000. Strategy space and the disturbance and the combined effect of expansion of western Russia also emphasise that spectrum: a life-history model for tree species co- forests and reduction in snow-covered areas. feedbacks may be highly regional in charac- existence. American Naturalist 156, 14–33. This is also why the albedo decrease in our ter. Our next step will be to take land man- 6. Betts RA 2000. Offset of the potential carbon sink simulations is accentuated in winter – forests agement into account – a feature that is from boreal forestation by decreases in surface mask snow (Fig. 2). most likely to affect the strength of the in- albedo. Nature 408, 187–190.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 27 Eva Kowalczyk is a mathematical modeller at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Melbourne, Australia. She has been working in the area of land surface - atmos- phere interactions for more than 20 years. In col- laboration with her CSIRO colleagues, she has worked on the development of several generations of land surface schemes in the CSIRO global circulation models.

Eva Kowalczyk1, Ying Ping Wang1, Rachel Law1, Bernard Pak1 and Ian Harman2

1. Centre for Australian Weather and Climate Research (CAWCR), Commonwealth Scientific and Industrial Organisation (CSIRO) Marine and Atmospheric Research, Aspendale, Victoria, Australia 2. Commonwealth Scientific and Industrial Organisation (CSIRO) Marine and Atmospheric Research, Canberra, Australian Capital Territory, Australia Nutrient constraints on carbon-climate feedback in an Earth System model

Predictions by climate models with a fully cently demonstrated by results from a cli- coupled carbon cycle consistently show a mate model with fully coupled carbon and positive feedback between the global car- nitrogen cycles [2]. bon cycle and climate. That is, an increase in Fig. 1 shows a simple analysis of the

atmospheric carbon dioxide (CO2) concen- amount of nitrogen required for storing the tration will result in a warmer climate, and a amount of accumulated carbon as esti- warmer climate will reduce the net carbon mated by eight of the eleven models in the uptake by the land biosphere and thus C4MIP Phase II experiment [1]. Previously, accelerate the growth rate of atmospheric Hungate et al. [3] assessed the plausibility of

CO2 concentration and global warming. the estimated carbon uptake by different However, there is considerable scientific terrestrial models as reported in the third uncertainty about the magnitude of this IPCC assessment report. We assumed that positive feedback at time scales from the carbon was stored in wood at a C:N ratio decades to centuries [1]. of 500:1 (g(C)/g(N)) and in soil at a C:N ratio Carbon (C) uptake by the terrestrial bio- of 25:1. This ratio provided a lower limit for sphere is co-limited by available soil nutri- the N required to store the carbon. This N ents, particularly nitrogen (N) and phospho- limit, in turn, gave the maximal C uptake rus (P), along with limitations by water and possible by terrestrial biosphere by 2100. Figure 1. The amount of carbon accumulated in light. Models used in the Coupled Carbon the land biosphere from 1860 to 2100 as predicted We estimated that the maximal amount Cycle Climate Model Intercomparison Project by eight models in the C4MIP Phase II experiment of N available for plant and soil from 1860 to (C4MIP) Phase II experiments [1] did not and the estimated amount of nitrogen required for 2100 was 8.3 Gt, less than the amount of N include nutrient limitation, and therefore storing the carbon for each model. We estimated required for the carbon uptake estimated by they may have overestimated the carbon that the maximal N available from 1860 to 2100 six of the eight models. Therefore, it is likely was 8.3 Gt (N) (solid line) by assuming that the uptake by the terrestrial biosphere and carbon was stored in wood at a C:N ratio of 500:1 that those models underestimated the glo- underestimated the magnitude of positive and in soil at a ratio of 25:1 on mass basis. This bal carbon-climate feedback. This result is carbon climate feedback. This has been re- analysis is preliminary. preliminary; a detailed analysis is necessary

28 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 2. A schematic diagram of the CASA-NP phosphorus (P). The model has one soil inorganic 1. Friedlingstein P, Cox P, Betts R, Bopp L, von Bloh W, model. The plant has three pools: leaf, root, and nitrogen pool and three inorganic soil phosphorus Brovkin V, Cadule P, Doney S, Eby M, Fung I, Bala G, wood; litter has three pools: metabolic, structural pools (labile, sorbed P, and occluded P). The inputs John J, Jones C, Joos F, Kato T, Kawamiya M, Knorr litter and coarse woody debris (CWD); and soil or- of N to soil include deposition and fixation, and the W, Lindsay K, Matthews D, Raddatz T, Rayner P, ganic matter has three pools: microbial biomass, input of P to soil includes deposition and weather- Reick C, Roeckner E, Schnitzler K-G, Schnur R, ing rate. slow, and passive pools. Each organic pool has Strassmann K, Weaver AJ, Yoshikawa C, and Zeng N three state variables, carbon (C), nitrogen (N) and 2006. Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison. to account for the complex interactions be- of CASA-NP using independent estimates of Journal of Climate 19, 3337–3353. tween carbon and nitrogen in different plant and soil pools. Figure 3 compares the 2. Thornton PE, Lamarque JF, Rosenbloom NA, and ecosystems under the present and future estimates of plant biomass carbon with the Mahowald NM 2007. Influence of carbon-nitrogen conditions. observation-based estimates as described in cycle coupling on land model responses to CO2 To take into account the nutrient limita- [8]. CASA-NP can reproduce the latitudinal fertilization and climate variability. Global Bio- tion on carbon uptake by the land bio- variation of plant biomass under the present geochemical Cycles 21, GB4018, doi:10.1029/ 2006GB002868. sphere, we need to implement nitrogen and climate conditions quite well. 3. Hungate BA, Dukes JS, Shaw R, Luo YQ, and Field phosphorus cycles in Earth System models. The next steps are to calibrate the CASA- CB 2003. Nitrogen and climate change. Science Nitrogen fixation is the most significant NP model using independent estimates of 302, 1512–1513. source of nitrogen for most unmanaged soil carbon, nitrogen, and phosphorus pools 4. Wang YP, Houlton B, and Field CB 2007. A model land systems but it has not been repre- and measurements of surface atmospheric of biogeochemical cycles of carbon, nitrogen and sented in most global biogeochemical CO2 concentrations. We will then conduct phosphorus including symbiotic nitrogen fixation models for the terrestrial biosphere. the uncoupled and coupled simulations for and phosphatase production. Global Bio- studying carbon-climate feedbacks and con- geochemical Cycles 21, GB1018, doi:10.1029/ Recently, a new model of N2 fixation based on resource optimisation principles straints of nutrient limitation on the magni- 2006GB002797. was developed by [4]. Their modelling tude of this positive feedback between car- 5. Houlton BZ, Wang YP, Vitousek PM, and Field CB framework has been used to explain the bon cycle and climate at time scales from 2008. A unifying framework for di-nitrogen (N2) geographic variation of N fixation globally, decades to centuries. ■ fixation in the terrestrial biosphere. Nature 454, 2 327–330, doi:10.1038/nature07028. see [5]. [email protected] 6. Fung IY, Doney SC, Lindsay K, and John J 2005. Based on previous work [6], we added Evolution of carbon sinks in a changing climate. nitrogen and phosphorus cycles into a car- Proceedings of the National Academy of Sciences bon cycle model CASA. The modified model of the United States of America (PNAS) 102, was named CASA-NP (Fig. 2). 11201–11206. The model consists of 9 carbon pools, 10 7. Kowalczyk EA, Wang YP, Law RM, Davies HL, nitrogen pools, and 12 phosphorus pools. Ni- McGregor JL, and Abramowitz G 2006. The CSIRO trogen fixation and biochemical soil phos- Atmosphere Biosphere Land Exchange (CABLE) phorus mineralization are represented ex- model for use in climate models and as an offline plicitly. model. CSIRO Marine and Atmospheric Research paper 013. Aspendale, Victoria. CSIRO Marine and We coupled CASA-NP with a land sur- Atmospheric Research. 37 p. face model CABLE [7], and this coupled 8. Olson JS, Watts JA, and Allison LJ 1985. Major model is being implemented into a global Figure 3. Comparison of the modelled plant world ecosystem complexes ranked by carbon in climate model for studying carbon-climate biomass carbon variation with latitude using CASA- live vegetation. The Carbon Dioxide Information interactions for the past, present, and future. NP (black circles) with observation-based estimates Center (CDIC), Oak Ridge National Laboratory, Oak We have calibrated the stand-alone version [7] (red circles). Ridge, Tennessee, USA.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 29 Sami Ullah recently joined the Lancaster Environment research on denitrification and greenhouse gas Centre at Lancaster University as a Senior Researcher emission from alluvial soils (river floodplain) in the investigating the influence of hydrologic fluxes on Lower Mississippi valley. nitrogen (N) transport and transformations in the In 2005, Dr. Ullah studied the influence of chronic hyporheic (an interface of surface-groundwater N loading on N2O emissions from riparian (wetlands mixing zone in river beds) zones of groundwater-fed bordering rivers) wetlands at Rutgers University, USA. rivers in UK. For 2006-2008, he worked at McGill University as a He started off his research as a student at Louisi- Postdoctoral Fellow on greenhouse gas fluxes from ana State University (LSU), USA, under the Fulbright forest soils in eastern Canada along a transect running Scholarship program in 1999. In 2001, Dr. Ullah en- from southern Ontario to northern Quebec under the rolled in the PhD program at LSU and completed his supervision of Dr. Tim Moore.

Sami Ullah1, 2 and Tim R. Moore1 1. Department of Geography, McGill University, Montreal, Canada 2. Lancaster Environment Centre, Lancaster University, Lancaster, UK

Topographic controls of CH4 and N2O fluxes from temperate and boreal forest soils in eastern Canada

Globally, forest soils are net sources of at- CH4 whereas poorly drained soils with larger (CO2) emissions, fluxes of CH4 and N2O need mospheric nitrous oxide (N2O) ranging from soil moisture contents are sources of CH4 [2]. to be included when modelling net green- -1 2.4 to 5.7 Tg (N2O-N) yr and net sinks for The net CH4 flux from soils is a balance be- house gas fluxes from forest soils. atmospheric methane (CH4) ranging from tween CH4 consumption through methano- In this study, we investigated fluxes of 1.8 to 11.8 Tg (CH -C) yr-1 [1]. trophy (aerobic process where bacteria 4 CH4, N2O, and CO2 from two temperate de- The large range in N O emissions and metabolise methane to energy and cell ciduous and two boreal forest sites in 20 2 material) and CH production through CH4 uptake in forest soils mainly arises from 4 plots including both well drained and poorly uncertainties associated with limited meas- methanogenesis (anaerobic process, forma- drained soils in eastern Canada. urements elucidating the influence of topo- tion of methane by microbes). The two deciduous forest catenas graphic heterogeneity and seasonality on Similarly, poorly drained forest soils can (groups of closely associated soils with

CH4 and N2O fluxes. emit more N2O than well drained soils similar parent material) were located near Canada contains about 400 million ha of because of their higher denitrifier activity [2]. Montreal (~45°N); the two boreal forest sites were located near Chibougamau in central forested land, about 10% and 33% of the N2O is produced in soils through nitrifica- total global and boreal forest cover, respec- tion (aerobic process, oxidation of ammonia Quebec (~49°N) and Eastmain in northern tively. This vast forest cover in Canada can into nitrite and further to nitrates by micro- Quebec (~52°N), respectively. have a significant influence on the exchange organisms) and denitrification (anaerobic mi- Four static flux measurement collars of greenhouse gases with the atmosphere. crobial process of converting nitrate to nitro- were installed at 4 locations within each plot Forested landscapes in Canada are not ho- gen gas). (total 80 collars) and fluxes were measured mogeneous, but rather consist of a mosaic Even though the aerial extent of poorly bi-weekly from May 2006 to May 2008 at of well and poorly drained soils determined drained and wetland soils in forested land- the two deciduous forest sites and during by topography. scapes may be small, the net exchange of the snow-free period in 2007 at the two boreal forest sites. In topographically heterogeneous forests, CH4 and N2O from these soils can be large. well drained soils are sinks of atmospheric Therefore, in addition to carbon dioxide In these forests, soil drainage class and

30 iLEAPS Newsletter Issue No. 7 ◆ June 2009 forest type significantly influenced fluxes of

CH4 and N2O (Table 1). Well drained soils were net sinks of atmospheric CH4 whereas poorly drained soils were net sources of CH4 in both deciduous and boreal forest soils, and both emission and consumption of at- mospheric CH4 were much stronger in de- ciduous than boreal forests (Table 1).

Among environmental variables, CH4 fluxes at plot scales at daily time steps were mainly regulated by % volumetric soil water content (VWC) and temperature (Table 2) both in well and poorly drained soils [3]. Both well drained and poorly drained soils in deciduous and boreal forests were net sources of atmospheric N2O; however, N2O emission rates in deciduous forests were larger than those from boreal forests (Table 1). In well drained soils, the driving force behind N O emissions in both decidu- 2 Figure 1. Relationship of annual N2O fluxes and soil forest soils. Boreal forest soils data are taken from ous and boreal forests appears to have been C:N ratio in well and poorly drained and boreal [3]. the large nitrification rate [4,5]. In contrast, denitrification was the major source of N2O emissions from poorly drained soil in de- ciduous forests (unpublished data).

Hourly N2O fluxes at the scale of indi- vidual flux chamber measurements in these forests did not show a strong correlation with substrate and environmental variables (Table 2) [6].

However, averaged annual N2O fluxes from well and poorly drained soils showed a significant exponential relationship with the soil carbon/nitrogen (C:N) ratio (Figure 1). This is in agreement with the findings of [7] in Europe. Soil C:N from these forests [5] and the White mountains forests in New Hampshire [8] also exhibited a significant relationship with nitrification rates, showing that the C:N ratio exerts a strong control on internal N cycling and N2O emissions because of its di- rect control on the rate of nitrification and Figure 2. Relationship of soil C:N ratios and nitrifi- [8] and for boreal forest soils in Quebec from [3] indirect effect on nitrate (NO3) supply in soils cation rates in deciduous and boreal forest soils. and [5]. for denitrifier activity. Data for the New Hampshire forests is taken from In general, when microbes decompose organic carbon, they respire about 60% of it as CO and assimilate about 40% in their 2 CO2 emissions were generally larger from In summary, forest type and the differ- biomass. Soils with a C:N ratio of around 25 well drained than from poorly drained soils ences in soil drainage caused by topo- would provide just enough N through de- in the deciduous forest soils and soil tem- graphic heterogeneity significantly influ- composition by bacteria to maintain the C:N perature and VWC explained 48 and 46% enced greenhouse gas fluxes in eastern ratio of microbial biomass at 10:1, assuming variability in CO2 emissions from well and Canada. Integrating these factors into mod- an assimilation fraction of 40%. poorly drained soils (Tables 1 & 2). elling greenhouse fluxes from forest soils is Soils with C:N ratios >25 are N-limited Moreover, deciduous forests emitted crucial, as was concluded in the discussions held at the iLEAPS workshop in Hyères, and thus whatever N is released is immobi- more CO2 than the boreal forest soils (Table lised by the microbes rather than released 1 and [4]). In boreal forests, soil temperature France in November 2009. and made available for nitrification and explained 11% of the variability in CO2 emis- Soil temperature and moisture are variables denitrification processes [9]. sions (Table 2). that are easily available and/or monitored

iLEAPS Newsletter Issue No. 7 ◆ June 2009 31 Soil drainage and/or CH4 flux N2O flux CO2 flux Forest type management type (kg (C) ha–1 yr–1)* (kg (N) ha–1 yr-1) (kg (C) ha–1 yr-1)

Deciduous Well drained –4.1 ± 0.1 0.58 ± 0.05 6377 ± 203 forest soils Poorly drained 28 ± 7 1.8 ± 0.3 4965 ± 192

Well drained –0.29 ± 0.30 0.05 ± 0.03 1306 ± 113 Poorly drained 0.50 ± 0.18 0.04 ± 0.04 1816 ± 208 Boreal forest soils Poorly drained ± ± ± cut-over wetland 71 28 0.09 0.005 1430 433

Well drained –0.36 ± 0.32 0.05 ± 0.03 1006 ± 102 burned forests

*Average fluxes from boreal forest soils represent snow-free period only (May to October).

Table 1. Annual fluxes of CH4, N 2O, and CO2 from boreal cut-over (clear-cut silviculture) forested well and poorly drained soils in temperate and wetland were 142 times larger than in mature boreal forests soils (mean ± SE). CH consumption boreal forested wetlands [3]. Well drained soils in 4 1. IPCC 2007: Climate Change 2007: The Physical Sci- in well drained soils was 14 times stronger in de- deciduous forests produced 3 times smaller N2O ciduous than in boreal forests, and CH4 emissions than those from poorly drained soils. N2O emissions ence Basis. Contribution of Working Group I to the from poorly drained soils were 56 times larger in in boreal cut-over forested wetland were 2.3 times Fourth Assessment Report of the Intergovernmen- deciduous than in boreal forests. CH emissions in 4 larger than in mature forested wetlands [3]. tal Panel on Climate Change [Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, and Miller HL (eds.)]. Cambridge University Deciduous forests Press, Cambridge, United Kingdom and New York, Gas flux Well drained soils Poorly drained soils NY, USA, 996 pp. 2. Ullah S, Frasier R, King L, Picotte-Anderson N, and ln(CH flux) = ln(CH flux) = Moore TR 2008. Potential fluxes of N O and CH CH flux 4 4 2 4 4 2.1 + 0.003VWC – 0.006T 0.77 + 0.008VWC – 0.42(CO flux) + 0.12T from soils of three forest types in Eastern Canada. [ln(CH m–2 d–1] s 2 s 4 R2 = 0.27; n = 123; p < 0.0001 R2 = 0.30; n = 116; p < 0.0001 Soil Biology and Biochemistry 40, 986–994. ln(N O flux) = ln(N O flux) = 3. Savage K, Moore TR, and Crill P 1997. Methane and N O flux 2 2 2 3.5 – 0.02T – 0.02(C:N ratio) 3.04 + 0.003 [NO ] carbon dioxide exchanges between the atmos- [ln(µg (N) m–2 h–1)] s 3 R2 = 0.10; n = 88; p < 0.01 R2 = 0.06, n = 84; p < 0.0001 phere and northern boreal forest soils. Journal of CO flux = CO flux = Geophysical Research 102, 29278–29288. CO flux 2 2 2 –0.54 + 0.01VWC + 0.20T 2.7 – 0.03VWC + 0.09T 4. Ullah S, Pelletier L, Frasier R, and Moore TR 2009. (g (C) m-2 d–1) s s R2 = 0.48; n = 479; p < 0.0001 R2 = 0.46; n = 486; p < 0.0001 Greenhouse gas fluxes during the snow-free pe- riod from boreal forest soils, Quebec. Canadian Boreal forest soils (well and poorly drained) Journal of Forest Research 39, 660–666. 5. Ullah S and Moore TR 2009. Soil drainage and

CH4 flux [CH ] = 0.69 + 0.1VWC + 0.04T vegetation control of nitrogen transformation rates –2 –1 4 s [ln(CH m d )] 2 4 R = 0.32; n = 227; p < 0.0001 in forest soils, southern Quebec. Journal of Geo- physical Research - Biogeoscience 114, G01014,

N2O flux doi:10.1029/2008JG000824. µ -2 -1 Non-significant with any variable [ln( g (N) m h )] 6. Groffman PM, Brumme R, Butterbach-Bahl K, Dobbie KE, Mosier AR, Ojima D, Papen H, Parton CO flux WJ, Smith KA, and Wagner-Riddle C 2000. Evaluat- 2 [CO2] = 0.11 + 0.07Ts (g (C) m-2 d-1) R2 = 0.23; n = 235; p < 0.0001 ing annual nitrous oxide fluxes at the ecosystem scale. Global Biogeochemical Cycles 14, 1061– 1070. o -2 -1 Table 2. Stepwise regression equations of CH4, N2O, ture (Ts) in C; CO2 emissions in g (C) m d . Data 7. Klemedtsson L, von Arnold K, Weslien P, and and CO fluxes with environmental variables. Volu- on CH and CO fluxes from boreal forest soils are 2 4 2 Gundersen P 2005. Soil C:N ratio as a scalar param- metric soil water content (VWC) in %; Soil tempera- taken from [4]. eter to predict nitrous oxide emissions. Global Change Biology 11, 1142–1147. 8. Ollinger SV, Smith ML, Martin ME, Hallett RA, and could be used for estimating the range wetlands results in larger emissions of CH 4 Goodale CL, and Aber JD 2002. Regional variations of CH and CO fluxes from forest soils. and N O compared to mature forests. This 4 2 2 in foliar chemistry and N cycling among forests of is a critical factor to consider in studies of Furthermore, N2O fluxes are highly vari- diverse history and composition. Ecology 83, 339– able but dependent on ecosystem scale vari- greenhouse gas exchange between land 355. ■ ables such as soil C:N ratio, which can be surface and the atmosphere. 9. Chapin FS, Matson PA, and Mooney HA 2002. Prin- used to estimate annual N2O fluxes. ciples of Terrestrial Ecosystem Ecology. Springer Finally, logging of boreal forested [email protected] Science Publishers, USA. 436 pp.

32 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Second DIVERSITAS Open Science Conference 13–16 October 2009, Cape Town, South Africa

The conference is entirely dedicated to Plenary speakers biodiversity science and its connections to Georges Brown, Brazil policy. Gretchen Daily, USA Strengthening Andy Dobson, USA Georgina Mace, UK biodiversity science Guy Midgley, South Africa Evolution ❑ Inventorying biodiversity Nyawira Muthiga, Kenya ❑ Building a global system for biodiversity Pavan Sukhdev, Germany monitoring ❑ Climate change and Achim Steiner, UNEP biodiversity ❑ Land use changes and ❑ Special call to early-career scientists biodiversity Improving prediction of and to developing country scientists biodiversity changes ❑ Understanding impact of biodiversity changes on eco- The conference will present a special award system functioning and ecosystem for outstanding research presented by an services, etc. early-career scientist. DIVERSITAS encourages early-career scientists and scientists from Supporting the science developing countries to attend. – policy interface Registration Building biodiversity scenarios for the Please register online at future ❑ Scientifically assessing the 2010 www.diversitas-osc.org ❑ biodiversity targets Mobilising scientific For more information, please contact: expertise for decision making ❑ Analysing success of economic incentives for DIVERSITAS biodiversity ❑ Managing for ecosystem Muséum National d’Histoire Naturelle, services, etc. 57 Rue Cuvier – CP 41 , 75231 Paris Cedex 05, France Focus on African issues Tel: +33 1 40 79 80 44 Reconciling biodiversity conservation and Fax: +33 1 40 79 80 45 food production ❑ Freshwater availability E-mail: [email protected] and quality, etc. www.diversitas-osc.org

iLEAPS Newsletter Issue No. 7 ◆ June 2009 33 Mike Tosca is a graduate student researcher at the University of California, Irvine, working with Dr. James Randerson and Dr. Charles Zender. Mike is studying the climate effects of biomass burning aerosols in south-eastern equatorial Asia. He uses a combination of remote sensing data and global climate models (GCM). Before coming to Irvine, Mike earned his BSc at the University of Connecticut in Storrs, Connecticut, in mathematics-statistics.

Mike Tosca Department of Earth System Science, University of California, Irvine, California, USA El Niño and fire in equatorial Asia

There now exists enough satellite evidence of hydrophobic (water-repellent) and hy- to link fire and drought induced by El Niño drophilic (affinity to water) black carbon (BC) (a global coupled ocean-atmosphere phe- and organic carbon (OC) aerosols was the nomenon causing important climate same as in [9]. anomalies worldwide) in equatorial Asia We forced (used as input) CAM3 with (EAS) [1]. Reduced precipitation in EAS is well monthly biomass burning emissions of BC accepted as a consequence of the eastward and OC from the Global Fire Emissions Data- relocation of convection during El Niño [2]. base, version 2 (GFEDv2) [10]. Total carbon However, the potential role of drought-in- emissions were calculated from satellite- duced fire in enhancing and modulating El derived estimates of burned area and from Niño dynamics has not been systematically fuel loads and combustion completeness investigated. factors obtained from a biogeochemical The four most recent El Niños (1997– model. 1998, 2002–2003, 2004–2005 and 2006– In one set of simulations with CAM3, we 2007) were all characterised by heightened prescribed GFEDv2 fire emissions from 1997 levels of EAS fire aerosol emissions. Increased to represent a high-fire (El Niño) year. In fire activity and subsequently high aerosol another set of simulations, we prescribed fire emissions in the fall of 1997 coincided with emissions from 2000 to represent a low-fire one of the strongest El Niño events on (control) year. Total carbon emissions in EAS record. This was due in part to the positive were 821 Tg (C) yr-1 in 1997 and 47 Tg (C) yr-1 relation between El Niño strength and the in 2000. During 1997, the sum of OC and BC spatial extent of EAS drought [3]. Because of were 9.5 Tg (C) yr-1 and 1.2 Tg (C) yr-1, respec- increased human presence in the region tively. and poor land use management, El Niño- induced drought leads to fires more fre- quently now than two decades ago [4, 5, 6]. Figure 1. Observed climate forcing and simulated (CAM3) response to fire emissions in south-eastern We assessed the influence of fire aerosols Equatorial Asia (90°E-120°E, 5°S-5°N). a) observed on climate in equatorial Asia using the fire emissions from the Global Fire Emissions Data- Community Atmosphere Model, version 3.1 base (GFED), b) simulated aerosol optical depth, (CAM3) [7], to which we coupled the SNow c) simulated net clear-sky shortwave radiation at ICe And Radiation (SNICAR) model [8]. CAM3 the surface and through the troposphere (surface – 200 mbar) (W m-2), d) simulated sea surface was run using a slab ocean model (“simpli- temperatures (°C), and e) simulated evapotran- fied ocean”, SOM) with varying surface layer spiration (ET, light line) and precipitation (PPT, dark depths. Prognostic transport and deposition line) (mm d-1).

34 iLEAPS Newsletter Issue No. 7 ◆ June 2009 We performed two forty-year simula- 2. Bjerknes J 1969. Atmospheric teleconnections tions with the above-described GFEDv2 from the equatorial Pacific. Monthly Weather fluxes for 1997 and 2000, repeating them for Review 97, 163–172. each of the 40 years. Monthly emissions 3. Lyon B 2004. The strength of El Niño and the spa- were interpolated to match the time-step tial extent of tropical drought, Geophysical Re- resolution of the model [7, 11]. We then in- search Letters 31, L21204. jected the emissions into the surface layer 4. Malingreau JP, Stephens G, and Fellows L 1985. because many of the fires in this region are Remote sensing of forest fires in Kalimantan and in low-temperature smoldering peatlands North Borneo in 1982–83. Ambio 14, 314–321. [12]. The relative wetness of peatlands pre- 5. Nichol J 1997. Bioclimatic impacts of the 1994 vents fires from being too hot, thus confin- haze event in southeast Asia, Atmospheric Envi- ing their plumes close to the surface. ronment 31, 1209–1219. We determined the climate response to 6. Heil A and Goldammer JG 2001. Smoke-haze pol- the aerosol forcing by constructing a mean lution: a review of the 1997 episode in Southeast Asia. Regional Environmental Change 2, 24–37, annual cycle from the last thirty years of Figure 2. Relation between GFED (Global Fire Emis- doi:10.1007/s101130100021. each simulation. The first ten years were ex- sions Database)-predicted emissions and average 7. Collins WD, Rasch PJ, Boville BA, Hack JJ, McCaa JR, cluded to allow for SOM spin-up. We calcu- precipitation rates during the three consecutive Williamson DL, Kiehl JT, and Briegleb B 2004. lated anomalies by subtracting the low-fire months of lowest rainfall for southern Borneo. The Description of the Community Atmosphere Model (control) simulation from the high-fire (El arrow pointing left indicates a fire-induced 13% -1 (CAM 3.0). Technical Report NCAR TN– 464+STR. Niño) simulation. For analysis of climate ef- decrease in El Niño precipitation, from 71 mm d to 62 mm d-1. This corresponds to a 46% increase in National Center for Atmospheric Research. fects, our focus domain was a sub-region of optimised emissions (upward pointing arrow) from 8. Flanner MG, Zender CS, Randerson JT, and Rasch PJ EAS bound by 90°E-120°E and 5°S-5°N that -1 -1 73.1 mm d to 106.5 mm d . 2007. Present-day climate forcing and response included most of Sumatra and Borneo. from black carbon in snow. Journal of Geophysical Fig. 1 shows simulation results for several and cooling from decreased condensation Research 112, D11202. climate parameters. Elevated fire aerosol combined with the SST cooling to aid in 9. Rasch PJ, Collins WD, and Eaton BE 2001. Under- concentrations coincided with a reduction in reducing precipitation by 10 mm month-1. standing the Indian Ocean Experiment (INDOEX) convection and precipitation (0.9 mm d-1) for Because the decrease in precipitation coin- aerosol distributions with an aerosol assimilation. the region of analysis in EAS [13]. This is be- cided with a decrease of evapotranspiration Journal of Geophysical Research 106, 7337–7355. cause fire aerosols reduced surface insola- (Fig. 1), favourable conditions for fire were 10. van der Werf GR, Randerson JT, Giglio L, Collat GT, tion during August–October by 20 W m-2 enhanced. Thus, accidental anthropogenic Kasibhatla PS, and Arellano Jr. AS 2006. Interannual (10%) in the same region. The reduced inso- burning in the region may intensify drought variability in global biomass burning emissions lation cooled sea surface temperatures (SSTs) during El Niños, in a positive feedback loop. from 1997 to 2004. Atmospheric Chemistry and and 2-m air temperatures by 0.5 and 0.3°C, Data from [1] show a near-exponential Physics 6, 3423–3441. respectively, during these months. relationship between dry-season precipita- 11. Collins WD, Rasch PJ, Eaton BE, Fillmore DW, and Previous studies have linked sea surface tion and fire emissions in southern Borneo. Kiehl JT 2002. Simulation of aerosol distributions cooling with increased surface pressure and Using data from the Tropical Rainfall Measur- and radiative forcing for INDOEX: Regional climate impacts. Journal of Geophysical Research 107, decreased surface convergence (the conflu- ing Mission (TRMM) we estimated that the 8028, doi:10.1029/ 2000JD000032. ence of air at the surface which causes uplift southern Borneo precipitation during a and convection) [14]: cooler SSTs and the moderate El Niño (2002, 2004, 2006) was 62 12. Page SE, Siegert F, Rieley JO, Boehm HD, Jaya A, and -1 Limin S 2002. The amount of carbon released from resulting decreased surface wind speeds can mm month . Assuming that our simulations peat and forest fires in Indonesia during 1997. combine to limit surface convergence as in accurately model the response of climate to Nature 420, 61–65, doi:10.1038/nature01131. [15]. Lower surface wind speeds over the smoke, a 13% August-October rainfall reduc- 13. Tosca MG, Randerson JT, Zender CS, Flanner MF western Pacific have been observationally tion in southern Borneo would indicate that and Rasch PJ 2009. Do biomass burning aerosols linked to reduced convection [16], and this is biomass burning aerosols had decreased the moderate El Niño precipitation by 9 mm intensify drought in Equatorial Asia during El Niño? consistent with our study. The established re- Atmospheric Chemistry and Physics (submitted). lationship between convection and conver- month-1 (71 to 62 mm month-1;13%). 14. Graham NE and Barnett TP 1987. Sea surface tem- gence explains why elevated fire aerosol According to Figure 5 in [1], this reduction would increase regional fire emissions by perature, surface wind divergence, and convection concentrations led to decreased precipita- over tropical oceans. Science 238, 657–659. tion in the modelled study region [14, 17]. 46% (Fig. 2). ■ 15. Chelton DB, Schlax MG, Freilich MJ, and Milliff RF Tropospheric heating from BC absorp- [email protected] 2004. Satellite measurements reveal small-scale tion averaged 26 W m-2 (31%) and was bal- features in ocean winds. Science 303, 978–983, anced by a simultaneous decrease in latent 1. van der Werf GR, Dempewolf J, Trigg SN, doi:10.1126/science.1091901. heating (reduction in water vapour conden- Randerson JT, Kasibhatla PS, Giglio L, Murdiyarso D, 16. Raymond DJ 1995. Regulation of moist convection sation throughout the column). BC is dark Peters W, Morton DC, Collatz GJ, and DeFries RS over the West Pacific warm pool. Journal of Atmos- and absorbs solar radiation, which in turn 2008. Climate regulation of fire emissions and pheric Science 52, 3945–3958. warms the atmosphere. A warmer atmos- deforestation in equatorial Asia. Proceedings of the 17. Chung CE and Ramanathan V 2003. South Asian phere is less able to support condensation. National Academy of Sciences 105(51), 20350– haze forcing: remote impacts with implications to The combination of heating from absorption 20355. ENSO and AO. Journal of Climate 16, 1791–1805.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 35 Christine Wiedinmyer is a scientist in the Biosphere- Atmosphere Interactions group at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. She received a PhD in Chemical Engineering from the University of Texas in Austin in 1999. Her research focuses on the emissions of trace gases and particles from vegetation and the influence of these emissions on air quality and climate. Christine Wiedinmyer has worked on the development of the Model of Emis- sions of Gases and Aerosols from Nature (MEGAN), and more recently led the development of a model to predict trace gas and particle emissions from fires. She is an Associate Editor of Journal of Geophysical Re- search and a member of the leadership board of the international Earth Science Women’s Network (ESWN).

Christine Wiedinmyer, Peter Harley and Alex Guenther National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA Exchange of organic compounds between the biosphere and the atmosphere

Emissions of volatile organic compounds Antropogenic (VOC) from the terrestrial biosphere to the 138 Tg atmosphere are significant, with estimates Biomass on the order of 1200 Tg (C) yr-1 [1]. Burning Compared to total global VOC emissions 49 Tg from anthropogenic sources, biogenic Other Biogenic sources dominate the inventory (Fig. 1), Nonreactive particularly in non-urban areas. These often VOCs highly reactive compounds have long been 260 Tg known to play a key role in the oxidation chemistry of the troposphere, giving rise to reaction products such as formaldehyde and carbon monoxide, in part controlling the at- Other Biogenic mospheric lifetime of methane, and contrib- Reactive uting significantly to ozone formation. VOCs In many regions, biogenic VOCs (BVOC) 260 Tg Biogenic are a key component of the chemical mix Isoprene that controls air quality (e.g. [2]). 600 Tg More recently, BVOC and their less vola- tile reaction products have been recognised to play a potentially large role in formation and growth of secondary organic aerosol (formed in the atmosphere by gas-to-parti- Biogenic cle conversion), with implications for cloud Monoterpenes 130 Tg processes and climate. This biogenic secondary organic aerosol (BSOA), combined with primary emissions of particles from the biosphere, contributes Figure 1. Global estimates of non-methane VOC from different sources [1, 5, 16].

36 iLEAPS Newsletter Issue No. 7 ◆ June 2009 substantially to the atmospheric burden of organic aerosol [3]. These atmospheric aerosols can affect air quality and visibility and alter climate directly (by scattering incoming radiation) and indi- rectly (by influencing cloud characteristics). The indirect effect has potential feedbacks to terrestrial ecosystems via changes in radia- tion and precipitation [4]. Our current understanding of biogenic emissions and atmospheric chemistry has reached the point where we can begin to use BVOC emission models in conjunction with atmospheric chemistry and transport models to address scientifically interesting and societally relevant issues such as the in- fluence of large-scale deforestation due to bark beetle infestation on BVOC emissions and regional chemistry or the possible inter- actions among BVOC emissions, aerosol loading and properties, clouds, and climate. Figure 2A. Areas infested by mountain pine beetles in the central Rocky Mountain The Model of Emissions of Gases and region of the western US (red). The infestations are resulting in large diebacks Aerosols from Nature (MEGAN; [5]) estimates of forests; this may result in large changes in BVOC emission estimates. emissions of over 100 compounds from the terrestrial biosphere at a horizontal resolu- tion of 1 km2, applicable for input to both regional and global models. The MEGAN framework, based on meas- urements made from the leaf level to the canopy scale, consists of maps of species- specific emission fluxes that are scaled to environmental controlling variables: current and past temperature, current and past light, leaf area index (LAI, sum of leaf surface area per unit ground area), leaf age, and soil mois- ture. Using emission estimates from MEGAN, we can model the influence of biogenic emissions on atmospheric chemical proc- esses; furthermore, we can begin to assess the effect of global change on these proc- esses. For example, incorporating biogenic sesquiterpene emissions within the MEGAN framework revealed that BSOA from these compounds contribute significantly to or- ganic aerosol in the continental USA [6]. Figure 2B. The percent reduction in predicted biogenic α-pinene emissions The magnitude and chemical speciation caused by a dieback of trees because of the insect infestation, of BVOC emissions, their pathways and fate assuming a short-term cessation of emissions. in the atmosphere, and the possible indirect feedbacks on the terrestrial biosphere are critical components of the Earth System and expected to change dramatically in the Our ability to project future changes in need to be well constrained. future, particularly for those regions suscep- BVOC emissions is limited, however, by our Although elements of these compo- tible to rapid changes in temperature or inadequate understanding of how atmos- nents have been extensively studied and our precipitation. pheric variations, such as changes in concen- understanding has come a long way, there Climate change will clearly alter BVOC trations of carbon dioxide and ozone and in remain many key issues to be addressed. emissions, but land-use changes can also nitrogen deposition, affect productivity and Since BVOC emissions are controlled by the have a dramatic influence on predicted species composition of global landscapes. type and density of the vegetation as well as BVOC emissions with concomitant changes That stresses and other disturbances can by climatic variables such as temperature, in important trace gases such as tropo- result in large changes in BVOC emissions is radiation, and water availability, they are spheric ozone [7,8]. also becoming more evident. Considering

iLEAPS Newsletter Issue No. 7 ◆ June 2009 37 disturbances such as fire and insect epi- The influence of land-use change is of 6. Sakulyanontvittaya T, Guenther A, Helmig D, demics in land-atmosphere and climate critical importance to the rate and magni- Milford J, and Wiedinmyer C 2008. Secondary or- models is necessary in order to accurately tude of BVOC emissions. With the imple- ganic aerosol from sesquiterpene and monoter- simulate energy, water, and carbon transfer mentation of new plantation species and ex- pene emissions in the United States. Environ- [9]. This is also true for BVOC emissions. tensive development of biofuels, these al- mental Science & Technology 42, 8784–8790; doi: It is suspected that large disturbances, tered landscapes will directly impact the 10.1021/es800817r. such as the current bark beetle epidemic in amount of BVOCs emitted. 7. Jiang X, Wiedinmyer C, Yang Z-L, Chen F, and North America [10], will alter BVOC emis- This is one of the topics highlighted in Chun-Fung Lo J 2008. Predicted impacts of cli- sions in several ways: the NERC OP3 project where measurements mate and land-use change on surface ozone in above an oil palm plantation in Borneo the Houston area. Journal of Geophysical Re- 1) emission of VOC in direct response to search 113, D20312, doi:10.1029/2008JD009820. the infestation may occur; highlight the atmospheric importance of these huge monocultures from local to re- 8. Wiedinmyer C, Tie X, Guenther A, Neilson R, and 2) as forests die as a result of insect infesta- gional scale (www.es.lancs.ac.uk/op3/index.html). Granier C 2006. Future changes in biogenic iso- tion, emissions will decrease, or cease al- prene emissions: how might they affect regional The significance of BVOC emissions to together (Fig. 2); and and global atmospheric chemistry? Earth Inter- the Earth System is clear; in conjunction with actions 10(3), 1–19, DOI: 10.1175/EI174.1. 3) as forests regrow and the distribution of the incorporation of BVOC emissions into 9. Running SW 2008. Climate change - ecosystem plant species and density changes, bio- Earth System Models, there is a concurrent disturbance, carbon, and climate. Science 321, genic emissions will change, too. need for further research to better constrain 652–653. the emissions, to elucidate biological and For instance, if aspen replaces lodgepole 10. Kurz WA, Dymond CC, Stinson G, Rampley GJ, physical controls over the emissions, and to pine in currently devastated regions of the Neilson ET, Carroll AL, Ebata T, and Safranyik L better understand the oxidation pathways Rocky Mountains, the current regime domi- 2008. Mountain pine beetle and forest carbon and fate of BVOCs in the atmosphere. ■ nated by methyl butenol and monoterpenes feedback to climate change. Nature 452, 987–990, will be replaced by isoprene-dominated [email protected] doi:10.1038/nature06777. BVOC emissions. Despite the recognition 11. Karl T, Guenther A, Turnipseed A, Patton EG, and that emissions can be altered both in quan- Jardine K 2008. Chemical sensing of plant stress at tity as well as in the particular chemical spe- the ecosystem scale. Biogeosciences 5, 1287– 1294. cies, current emissions models do not yet 1. Guenther A, Hewitt CN, Erickson D, Fall R, Geron C, include these effects. Graedel T, Harley P, Klinger L, Lerdau M, McKay WA, 12. Kesselmeier J and Staudt M 1999. Biogenic Improved land-use classification and Pierce T, Scholes B, Steinbrecher R, Tallamraju R, volatile organic compounds (VOC): An overview emission factor estimates are necessary to Taylor J, and Zimmerman P 1995. A global model on emission, physiology and ecology. Journal of better constrain regional and global BVOC of natural volatile organic compound emissions. Atmospheric Chemistry 33(1), 23–88. emissions. Additional compounds are con- Journal of Geophysical Research 100, 8873–8892. 13. Calfapietra C, Mugnozza GS, Karnosky DF, Loreto F, tinuously being discovered either in emis- 2. Chameides WL, Lindsay RW, Richardson J, and and Sharkey TD 2008. Isoprene emission rates under elevated CO and O3 in two field-grown sion measurements or in the ambient air. For Kiang CS 1988. The role of biogenic hydrocarbons 2 aspen clones differing in their sensitivity to O . example, methyl salicylate was recently iden- in urban photochemical smog: Atlanta as a case 3 tified in the atmosphere above a walnut study. Science 241, 1473–1475. New Phytologist 179, 55–61. plantation [11]; how much of this com- 3. Heald CL, Henze DK, Horowitz LW, Feddema J, 14. Pegoraro E, Rey A, Abrell L, Vanharen J, and Lin GH pound, associated with plant stress, is re- Lamarque JF, Guenther A, Hess PG, Vitt F, Seinfeld 2006. Drought effect on isoprene production and leased in different landscapes and what fac- JH, Goldstein AH, and Fung I 2008. Predicted consumption in Biosphere 2 tropical rainforest. Global Change Biology 12, 456–469. tors control its emission is unclear. change in global secondary organic aerosol 15. Carlton AM, Wiedinmyer C, and Kroll J 2009. A We also need to characterise the effects concentrations in response to future climate, emissions, and land use change. Journal of review of Secondary Organic Aerosol (SOA) of vegetation stress on emissions. Herbivory formation from isoprene. Atmospheric Chemistry [12], ozone deposition [13], and water stress Geophysical Research 113, D05211, doi:10.1029/ 2007JD009092. & Physics Discussion 9, 8261–8305. [14] can lead to enhanced emissions of 16. Olivier JGJ, Van Aardenne JA, Dentener F, BVOC from plants. However, the compounds 4. Barth M, McFadden J, Sun J, Wiedinmyer C, Chuang P, Collins D, Griffin R, Hannigan M, Karl T, Ganzeveld L, and Peters JAHW 2005. Recent emitted, the controlling variables, and the trends in global greenhouse gas emissions: magnitude of these emissions must be de- Kim S-W, Lasher-Trapp S, Levis S, Litvak M, Mahowald N, Moore K, Nandi S, Nemitz E, Nenes regional trends and spatial distribution of key termined. Moreover, our current lack of un- A, Potosnak M, Raymond T, Smith J, Still C, and sources. In: Non-CO Greenhouse Gases (NCGG-4), derstanding prevents any quantitative pre- 2 Stroud C 2005. Coupling between land ecosys- A. van Amstel (coord.), 325–330. Millpress, diction of emissions controlled by stress tems and the atmospheric hydrologic cycle Rotterdam, ISBN 90 5966 043 9. factors. through biogenic aerosol pathways, Bulletin of Further requirements for the estimation the American Meteorological Society 86, 1738– of BVOC emissions and the prediction of 1742. their chemical and physical paths in the at- 5. Guenther A, Karl T, Harley P, Wiedinmyer C, Palmer mosphere include more constrained chemi- PI, and Geron C 2006. Estimates of global terres- cal oxidation pathways and a better under- trial isoprene emissions using MEGAN (Model of standing of the heterogeneous reactions for Emissions of Gases and Aerosols from Nature). At- key BVOC species, such as isoprene [15]. mospheric Chemistry and Physics 6, 3181–3210.

38 iLEAPS Newsletter Issue No. 7 ◆ June 2009 A new starting COST ESSEM Action ES0804: Advancing the integrated monitoring of trace gas exchange between biosphere and atmosphere

This COST Action creates a platform for This Action advances the applicability of analysis, harmonisation, and synthesis, assess- produced data in climate and Earth system ment of future needs and further develop- modelling research and in more operational ment of a European integrated monitoring short- to medium-term forecasting of program for comprehensive trace gas and weather and air quality. aerosol flux observations. Current methodologies, operationality, The existing national and European flux dissemination, and coordination will also be monitoring communities work separately; addressed in this COST Action. Development therefore, networking by means of this COST of common methodologies, data manage- Action creates added value and is crucial for ment systems, and protocols will increase advancing the continuity, scope, and quality the reliability, value and cost-efficiency of of flux monitoring. European flux observations.

The Action has seventeen European mem- WG2 Work towards comprehensive multi- ber countries and two more pending. The species flux monitoring sites. Action consists of four Working Groups (WG) Leader: Klaus Butterbach-Bahl and a Management Committee with maxi- [email protected] mum two representatives of each member WG3 Assessing regional representativeness country. The co-chairs and Working Group of the flux sites in different ecosystems. leaders were selected in the Kick-Off Meet- ing in Brussels, 17–18 February 2009. Leader: Laurens Ganzeveld [email protected] Co-Chairs: Timo Vesala and Almut Arneth [email protected] WG4 Training and capacity building. [email protected] Leader: Janusz Olejnik [email protected] WG1 Analysis and synthesis of the current state of the flux monitoring sites, measure- The Action organises scientific workshops ment techniques, data handling methods that are open to the public. Next workshop and storage of data in Europe. in February 2010 will be announced on the Leader: Dario Papale Action’s web page: [email protected] www.ileaps.org/cost0804

COST is an intergovernmental framework For information on the Action, please see for European Cooperation in Science and the COST website: Technology, allowing the coordination of www.cost.esf.org nationally funded research on a European level. COST does not fund research itself but The latest events of the Action can be provides a platform for European scientists found on: to cooperate on a particular project and ex- www.ileaps.org/cost0804 change expertise.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 39 Benjamin Cook is a Global Change Postdoctoral Scholar at the National Oceanic and Atmospheric Administration (NOAA), based at Lamont-Doherty Earth Observatory and the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies. His research focuses on the interactions among climate, the land surface, and terrestrial eco- systems. Dr. Cook’s current projects include analysis of historical phenology records in the USA, modelling of feedbacks between land surface and drought, and drought forcing of ecosystem processes.

Benjamin I. Cook1,2, Richard Seager1 and Ron L. Miller2 1. Ocean and Climate Physics, Lamont-Doherty Earth Observatory, Palisades, New York, USA 2. National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies, New York, New York, USA Amplification of the North American ‘Dust Bowl’ drought through human- induced land degradation

Recurrent periods of drought are a common Another difference was that the Dust This was the source of the major dust feature of the mid-latitudes, modulated on Bowl drought centre moved from the south- storms and atmospheric dust loading of the interannual and decadal timescales primarily west and Mexico into the Central Great period, on a level unprecedented in the his- by the El Niño Southern Oscillation [1–6]. Plains. Models forced with observed SSTs torical record. We hypothesise that the dust Over North America, drier-than-normal during the 1930s produce a drought [1, 2, 4] storms and the loss of vegetation amplified conditions occur in the south-western and that is centred too far south, and fail to repli- the La Niña -forced drought and caused south-eastern United States when sea cate the near-continental-scale warm anom- the anomalous pattern of temperature and surface temperatures (SST) in the eastern aly of the Dust Bowl centred in the northern precipitation. The importance of land-surface tropical Pacific are lower than normal (‘La United States (Fig. 1, middle panels). This feedbacks during the Dust Bowl has been Niña’ conditions). La Niña conditions, with implies either some deficiencies in the suggested previously [1, 5], but few studies additional forcing from warm Atlantic SST, models or, alternatively, some missing physi- to date have quantitatively tested the im- have been implicated as the initial causes of cal processes. pact of dust aerosols and vegetation loss the 1930s drought known as the ‘Dust Bowl’ One hypothesis regarding the atypical during this period. [1, 2, 4]. Dust Bowl drought pattern invokes large- We used the atmospheric General Circu- The Dust Bowl was a significant disaster scale changes to the land surface during this lation Model (GCM) of the Goddard Institute for the United States, resulting in large eco- time period. During the 1920s, agriculture in for Space Studies (GISS ModelE) to test our nomic and agricultural losses, farm abandon- the United States expanded into the central hypothesis that land degradation during the ment, and massive human migration. The Great Plains. Much of the original, drought- period could explain the anomalous features Dust Bowl, however, differed in important resistant prairie grass was replaced with of the drought. We conducted four suites ways from the canonical La Niña drought drought-sensitive wheat. With no drought of 5-member ensemble simulations using pattern (Fig. 1, left panels): The Dust Bowl plan and few erosion control measures in observed SST from 1932–1939, with each was warmer and drier than would have place, this led to large-scale crop failures at ensemble member starting from different been expected given the modest size of the the initiation of the drought, leaving fields initial conditions. La Niña SST anomaly observed during the devegetated and barren, exposing easily In SST-ONLY, observed global SST (1932– 1930s. eroded soil to the winds. 1939) are used as input (forcing) to the

40 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Temperature (oC) and precipitation (mm (our control) and SST+DUST+CROP (full land served average (for CRU data) or an ensemble aver- day-1) anomalies for the ‘Dust Bowl’ drought from degradation in the form of a Great Plains dust aero- age from a 5-member ensemble run using the Climate Research Unit (CRU) version 2.1 data sol source and crop removal). Anomalies are for the observed SSTs for 1920–1929 (for the model plots). set and two of our model experiments: SST-ONLY period 1932–39, relative to the 1920–1929 ob- model, with no modifications to the land land-surface forcings are included (SST+ The addition of a dust source and the surface. In SST+DUST, we added a dust aero- DUST+CROP), the temperature and precipi- subsequent increase in dust aerosol loading sol source over the Plains over the approxi- tation anomalies are amplified to the ob- reduces net radiation at the top of the mate region of wind erosion during the served level, and the drought is now cor- atmosphere and at the surface largely by period (Fig. 2, top and middle panels). En- rectly centred over the central and northern shortwave reflection. This radiative heat loss semble average net dust emission (emission Great Plains (Fig. 1, right panels). must be balanced to maintain thermal equi- minus deposition) from our Great Plains dust Different mechanisms explain the tem- librium. Within the model, this is accom- source in this simulation was ~369 million perature and precipitation anomalies. Re- plished by enhanced sinking (subsidence) of metric tons per year, a magnitude consistent moval of vegetation reduces total evapo- air over the Great Plains, which warms as it with the limited available estimates of soil transpiration from the land surface by se- sinks. The sinking air, in turn, increases the loss. verely limiting transpiration, the flux of water stability of the atmosphere, suppressing con- In SST+CROP, we simulated vegetation from the soil to the atmosphere through vection and cloud formation, and reducing losses associated with the crop failure by plants during photosynthesis. Decreased precipitation. converting the crop areas over the Great summertime evaporation, mostly compen- The end result is a reduction in precipita- Plains to bare soil (Fig. 2, bottom panel). sated by increased sensible heating, raises tion and a shift of the drought centre north- This led to fractional vegetation reductions the Bowen ratio (ratio of sensible heat flux ward over the central Great Plains, near the of almost 50% in some grid cells. Finally, [heat transport in the form of rising warm centre of the dust aerosol cloud. When the in our SST+DUST+CROP experiment, the air] to latent heat flux [evapotranspiration in effects of dust and crop removal are com- model was forced with observed SST, along energy units]) from 0.52 to 0.59. This leads to bined, feedbacks from the separate experi- with a full representation of crop failure via increased soil and near-surface air tempera- ments act in concert to augment the impact inclusion of both a dust source over the tures. Warming during the summer is carried of SST forcing, simultaneously warming the Plains and vegetation reductions. over into the fall and winter seasons by posi- surface and reducing precipitation (Fig. 1, SST-ONLY produces only a modest tive soil temperature anomalies, when these right panels). drying and warming over the Great Plains warmer soils release this heat to the atmos- Our improved simulation of temperature region (Fig. 1, middle panels). When both phere. and precipitation anomalies, when more

iLEAPS Newsletter Issue No. 7 ◆ June 2009 41 realistic land-surface boundary conditions are included, suggests that land-surface feedbacks from the human-induced land degradation are necessary to explain the Dust Bowl drought. The Dust Bowl drought provides a good example of the complexity in atmosphere- ocean-land interactions that can lead to se- vere droughts. It also illustrates the way SST- forced droughts can be amplified through land-surface feedbacks. Understanding the relative importance of these feedbacks for drought in the future will require integrated model studies, similar to the study presented here. ■ [email protected]

1. Schubert SD, Suarez MJ, Pegion PJ, Koster RD, and Bacmeister JT 2004a. On the cause of the 1930s Dust Bowl. Science 303, 1855–1859. 2. Schubert SD, Suarez MJ, Pegion PJ, Koster RD, and Bacmeister JT 2004b. Causes of long-term drought in the US Great Plains. Journal of Climate 17, 485– 503. 3. Seager R, Kushnir Y, Herweijer C, Naik N, and Velez J 2005. Modeling of tropical forcing of persistent droughts and pluvials over Western North America: 1856-2000. Journal of Climate 18, 4065–4088. 4. Seager R, Kushnir Y, Ting M, Cane M, Naik N, and Miller J 2008. Would advance knowledge of 1930s SSTs have allowed prediction of the Dust Bowl drought? Journal of Climate 21, 3261–3281. 5. Cook BI, Miller RL, and Seager R 2008. Dust and Sea Surface Temperature forcing of the 1930s ’Dust Bowl’ Drought. Geophysical Research Letters 35, doi: 10.1029/2008GL033486. 6. Seager R, Harnik N, Robinson WA, Kushnir Y, Ting M, Figure 2. Dust emission (top, g m-2 yr-1) and dust ONLY for 1932–1939. The devegetated fraction is Huang HP, and Velez J 2005. Mechanisms of ENSO- aerosol loading (middle, g m-2) from the SST+DUST identical in the SST+DUST+CROP experiment, and forcing of hemispherically symmetric precipitation experiment and devegetated fraction (bottom, %) the dust emissions and loading are similar. variability. Quarterly Journal of the Royal Meteoro- from the SST+CROP experiment, relative to SST- logical Society 131, 1501–1527.

42 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Annual monoterpene emissions (mg (C) m-2 yr-1) for five time slices between the Last Glacial Maximum (21000 yrs B.P.) and present-potential (0 yrs B.P.).

Guy Schurgers, Thomas Hickler, Paul Miller and Almut Arneth Department of Physical Geography and Ecosystems Analysis, Lund University, Lund, Sweden Tree species composition and emissions of volatile organic compounds in Europe during the Holocene

Biogenic volatile organic compounds (BVOC) temperatures as the most important driver such as isoprene and monoterpenes (part for plant physiology and terpenoid produc- of the terpenoid family) are reactive com- tion. However, isoprene emissions have also pounds emitted from vegetation into the been observed to be stimulated by low (gla- atmosphere. They affect the concentrations cial) CO2 concentrations [5]. This enhance- of the main atmospheric oxidants ozone (O3) ment was incorporated in our model [3], and the hydroxyl radical (OH) and act as but it could not offset the lower emission precursors for biogenic aerosol particles. rates at the LGM caused by the climate. 1. Smith B, Prentice IC, and Sykes MT 2001. Represen- On the European scale, current emission The gradual increase in emissions since tation of vegetation dynamics in the modelling of estimates are often based on tree species the LGM particularly in northern, western, terrestrial ecosystems: comparing two contrasting inventories representing a present-day distri- and southern Europe (Fig. 1) was a response approaches within European climate space. Global Ecology and Biogeography 10, 621–637. bution of species. In this study, we applied a to higher temperatures and a more abun- dynamic vegetation model which enabled dant vegetation. However, in eastern Europe 2. Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, us to assess the changes in emissions in re- monoterpene emissions declined (Fig. 1) be- Cramer W, Kaplan JO, Levis S, Lucht W, Sykes MT, sponse to changes in species composition cause of a change from monoterpene-emit- Thonicke K, and Venevsky S 2003. Evaluation of ecosystem dynamics, plant geography and terres- and vegetation productivity since the Last ting coniferous forests to predominantly iso- trial carbon cycling in the LPJ dynamic global veg- Glacial Maximum (LGM, 21000 years B.P.). prene-emitting temperate broadleaf forests. etation model. Global Change Biology 9, 161–185. We performed simulations for Europe The simulations presented here that ap- 3. Arneth A, Niinemets Ü, Pressley S, Bäck J, Hari P, Karl with the dynamic vegetation model frame- plied species rather than plant functional T, Noe S, Prentice IC, Serça D, Hickler T, Wolf A, and work LPJ-GUESS [1, 2] in which we incorpo- types represent an important step forward Smith B 2007. Process-based estimates of terres- rated process-based algorithms for isoprene in the realistic simulation of BVOC emissions. trial ecosystem isoprene emissions: incorporating and monoterpene production and emission Because species grouped within one plant the effects of a direct CO2-isoprene interaction. [3,4]. The model was driven with climate functional type can differ considerably in Atmospheric Chemistry and Physics 7, 31–53. anomalies from general circulation model their BVOC emission characteristics, local 4. Schurgers G, Arneth A, Holzinger R, and Goldstein (GCM) simulations and with ice core-derived changes in emissions can only be repre- A 2009. Process-based modelling of biogenic CO2 concentrations. Twenty important Euro- sented with accurate species information. monoterpene emissions: sensitivity to temperature pean tree species and generic functional Given the high reactivity of these com- and light. Atmospheric Chemistry and Physics types were distinguished. pounds, these local effects are particularly Discussions 9, 271–307. ■ In the simulations, total European emis- important for atmospheric chemistry. 5. Possell M, Hewitt CN, and Beerling DJ 2005. The sions of isoprene and monoterpenes in- effect of glacial atmospheric CO2 concentrations creased after the LGM. This was primarily and climate on isoprene emissions by vascular caused by a change in climate, with higher [email protected] plants. Global Change Biology 11, 60–69.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 43 Cindy Morris is a plant pathologist and microbial ecologist and currently the Director of the Plant Pathology Research Unit at Institut National de la Recherche Agronomique (INRA) centre in Avignon, France. She obtained her PhD in 1985 at the University of Wisconsin-Madison, USA. There she worked on the adaptation of Pseudomonas syringae to the leaf sur- face habitat in a team which had discovered ice nu- cleation activity of this bacterium a few years previ- ously. Dr. Morris spent four years as a post-doctoral researcher at Beijing Agricultural University in China working on aerial dissemination of bacterial plant pathogens and on the role of ice-nucleation-active bacteria in post-harvest decay of Chinese cabbage. Since 1989, her work as a research scientist at INRA in Avignon has focused on the ecology of plant-patho- genic bacteria, and in particular on P. syringae that causes a devastating disease in cantaloupe across France.

Cindy E. Morris1,2, David C. Sands2 and Anne-Marie Delort3 1. Plant Pathology Research Unit, Institut National de la Recherche Agronomique (INRA), Avignon, Montfavet, France 2. Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, Montana, USA 3. Laboratoire de Synthèse et Etude de Systèmes à Intérêt Biologique, Université Blaise Pascal / Centre National de la Recherche Scientifique (CNRS), Clermont-Ferrand, France Microbiological Meteorology: investigating atmospheric processes at the cross-roads of biological and physical sciences

The abundance of micro-organisms in the biology, atmospheric physics and chemistry, the environment of our planet. One of these atmosphere has been known since the environmental modelling, and agronomy— goals is to understand the effects of anthro- insightful experiments of Spallanzani in the to create a field that we have christened pogenic sources of airborne micro-organ- 18th century and Pasteur in the 19th century. “Microbiological Meteorology” [1]. isms on atmospheric processes and to deter- These first observations of atmospheric The research contributing to this para- mine how they could buffer or mitigate cli- microflora were crucial for refuting the digm shift has four main branches, analo- mate change. theory of spontaneous generation and in es- gous to research on atmospheric aerosols: Classical microbiology is at the heart of tablishing microbiology as a veritable scien- 1) identification of potential atmospheric the idea that micro-organisms could have an tific discipline. Today, studies of the microbi- influence of micro-organisms based on influence on the atmosphere. A century of ology of the atmosphere are on the verge of their behaviour in laboratory studies; studies on microbial behaviour has revealed contributing to another paradigm shift: that 2) quantification of the abundance of these properties that can be crucial in atmospheric airborne micro-organisms contribute to micro-organisms in air, clouds, and pre- processes. The most striking example is that processes influencing atmospheric chemis- cipitation; certain bacteria and fungi can catalyse freez- try, planetary albedo, and precipitation in ing of super-cooled water at temperatures similar and even more varied ways as aero- 3) estimation of the influence of airborne near 0°C. micro-organisms on atmospheric proc- sol particles. For bacteria, this property is conferred by esses based on laboratory and field ob- an unusual, highly folded protein produced These potential roles of micro-organisms servations coupled to modelling and have been inferred from properties of their on the cell surface. This property was discov- 4) characterisation of the sources of micro- cells that can take part in radiative forcing, in ered in the search for the cause of plant frost bial aerosols and elucidation of proc- the formation of cloud droplets and ice crys- damage and of ice crystal formation leading esses involved in their formation; and tals, or in metabolism of chemical compo- to snow [2]. transport in the atmosphere. nents of aerosols. During the past few years, Lively speculation still takes place about we have been working to bring together The goals of these studies are particu- the ability of these biological ice nucleators different fields of scientific expertise—micro- larly pertinent to contemporary changes in to influence precipitation [3, 4].

44 iLEAPS Newsletter Issue No. 7 ◆ June 2009 The continuing discussion on this sub- micro-organisms, has overwhelmingly been have effects on atmospheric processes is ject can be followed at: the realm of plant pathologists attempting currently circumstantial or indirect. The com- http://bio-ice.forumotion.com/forum.htm. to follow the flight of drying, UV-stressed ing decades will see great progress in ob- Bacterial cells also seem capable of act- propagules (bacterial cells or parts of fungi taining more solid evidence. Biological ice ing as cloud condensation nuclei (particles or yeasts) of plant pathogens such as fungal nucleators have been found in clouds around which cloud droplets form by con- spores, single cells of bacteria, or yeasts on [14,20], and, compared to other substrates, densation of atmospheric water vapour) [5, their way to distant cropped fields. The deci- freshly fallen snow has been observed to 6], most probably because of the hygro- sive work of Stackman [10] and of Gregory contain an enriched concentration of ice-nu- scopic (moisture-absorbing) polysaccharides [11] on aerial dissemination of spores that cleation-active strains of certain bacteria [21]. on their cell surface. Some bacteria also pro- spread rusts and other plant diseases set the Under simulated cloud conditions, these duce strong surfactants (wetting agents that stage for decades of similar pursuit. This bacteria can induce ice crystal formation lower the surface tension of a liquid allowing research has nourished the literature with [22,23] and, under certain conditions in easier spreading) (bio-surfactants). This can data on the occurrence and abundance of simulated numerical models, they can have be an advantage on waxy hydrophobic (wa- fungi, bacteria, yeasts, and viruses in the air. an effect on precipitation [3,24]. ter-repellent) plant surfaces where they help In the early 1900’s, microbiologists ac- Likewise, the roles of micro-organisms in these bacteria to degrade plant tissue (and companied Charles Lindberg on flights to atmospheric chemistry have been studied hence to access food resources) [7]. assess the abundance of micro-organisms in mostly in laboratory reactors [13,14] to esti- Furthermore, by enhancing the conden- the upper atmosphere [11]. mate potential kinetics for subsequent use sation of atmospheric water across a large In the late 1970’s scientists in the Soviet in atmospheric models. Attempts have been number of airborne particles that might oth- Union used meteorological rockets to assess made to evaluate the overall metabolic ac- erwise be hydrophobic, bio-surfactants of the presence of micro-organisms at farther tivity of the whole complex of micro-organ- airborne bacteria could favour the persist- reaches of Earth’s atmosphere to define the isms in cloud water directly in fresh samples ence of fog. In other words, surfactants limits of the biosphere [12]. via incorporation of radioactive isotopes un- der super-cooled conditions [16] or by as- would enhance the formation of numerous But only recently has there been an at- sessing growth without nutrient supplemen- very small water drops that could remain tempt to characterise the microflora of tation [25]. suspended in air (fog) rather than formation clouds per se, where they are set to play im- of large droplets apt to precipitate [8]. portant roles. Micro-organisms that can be Similarly, by determining the concentra- tion of adenosine triphosphate (ATP) in Studies of microbial metabolism for di- cultured are present at about 103–105 cloud samples, we have revealed that the verse purposes such as industrial processes, propagules ml-1 of cloud water [13–16] and vast majority of micro-organisms in these bioremediation (detoxifying pollutants by include dozens of species of bacteria and samples has maintained metabolic activity micro-organisms), and deciphering plant- fungi and several yeasts among which are [26]. microbe interactions have revealed the strains capable of metabolising atmospheric capacity of micro-organisms to metabolise organic compounds under laboratory condi- The major gap in knowledge about the (break down organic material to obtain en- tions [14]. interaction of micro-organisms and atmos- pheric processes concerns microbial emis- ergy and form cell material), for example, Overall, data on names and numbers of sions. The few published measurements of dicarboxylic acids, methane, isoprene, and micro-organisms is accumulating. That oce- microbial flux into the atmosphere were re- longer chained alkanes and phenols that anic sources – as well as plants – also con- ported 15 to 20 years ago [27–30]. Plants are constitute the bulk of dissolved organic tribute to the microflora of clouds is also considered to be one of the major sources carbon or major pollutants in atmospheric becoming clear [17]. aerosols. The significance of these capacities of micro-organisms in the atmosphere. Many However, there is a great need for assess- of the micro-organisms cited as potential for atmospheric chemistry is being explored ing the in situ state of these micro-organisms actively [9]. actors in atmospheric processes are typical to better evaluate whether they are indeed inhabitants of plant surfaces and some of In addition to the direct roles that micro- in a physiological condition necessary for in- these are bona fide plant pathogens. As a organisms could play in atmospheric proc- fluencing atmospheric processes. A signifi- source, leaf surfaces represent over 109 km2 esses, there are exciting questions to con- cant step in this direction is the recently de- of microbial habitat and likely harbour 1024– sider about feedbacks. Micro-organisms are veloped technique to quantify biological ice 1026 total bacteria [31] and so far unesti- metabolically active with dynamic biological nucleators directly from environmental sam- mated numbers of fungi and yeasts. properties, many of which are likely main- ples without culturing the microbial compo- At present, we do not know what frac- tained also in the atmosphere. nents of the sample [18, 19]. tion of these micro-organisms take off into Hence, the microbial traits that lead to This has revealed that up to 69–100% of the atmosphere and in what state – single their potential effects on the atmosphere are the ice nuclei in fresh snowfall can be of cells and spores, or clumps of micro-organ- due to capacities that vary with metabolism, biological origin. In over 45% of these sam- isms and debris. Factors determining the gene expression, the distribution of charges ples, biological ice nuclei were sensitive to source strength of plant canopies are likely across the cell wall, and with other cellular lysozyme (an enzyme that specifically de- to be complicated by the plant species characteristics. These capacities wax and grades components of bacterial cell walls) involved – different species and cultivars wane as a function of the local environment suggesting that they were associated with harbour widely different quantities of micro- and as cells mature and senesce. bacteria [18]. organisms that potentially can influence the The study of aerobiology, with regard to Evidence that micro-organisms indeed atmosphere [32, 33] – and by the local land

iLEAPS Newsletter Issue No. 7 ◆ June 2009 45 scape through its influence on micro-climate. 11. Gregory PH 1961. The Microbiology of the Atmos- 23. Ward PJ and DeMott PJ 1989. Preliminary experi- Renewed efforts to install field platforms phere. Interscience Publishers, Inc., New York, 251 p. mental evaluation of Snomax snow inducer, Pseu- for assessment of microbial flux into the at- 12. Imshenetsky AA, Lysenko SV, and Kazakov GA domonas syringae, as an artificial ice nucleus for mosphere [34] are necessary to achieve the 1978. Upper boundary of the biosphere. Applied weather modification. Journal of Weather Modifi- long term goals of Microbiological Meteorol- and Environmental Microbiology 35, 1–5. cation 21, 9–13. ogy. If in fact microbes are involved in at- 13. Amato P, Menager M, Sancelme M, Laj P, Mailhot G, 24. Phillips VTJ, Andronache C, Morris CE, and Sands mospheric processes, there are exciting and Delort A-M 2005. Microbial population in DC 2008. Impacts from ice nucleating bacteria on questions to address about the leverage of cloud water at the Puy de Dôme: Implications for continental deep convection: a potential micro- agronomy and land use practices – via, for the chemistry of clouds. Atmospheric Environment climate feedback? Biogeosciences Discussion 5, example, grazing, crop varietal selection, rota- 39, 4143–4153. 1035–1067. tions, and intercropping – on these proc- 25. Amato P, Demeer F, Melaouhi A, Fontanella S, Mar- ■ 14. Amato P, Parazols M, Sancelme M, Laj P, Mailhot G, esses. Delort A-M 2007. Microorganisms isolated from tin-Biesse A-S, Sancelme M, Laj P, and Delort A-M 2007. A fate for organic acids, formaldehyde and [email protected] the water phase of tropospheric clouds at the Puy de Dôme: major groups and growth abilities at methanol in cloud water: their biotransformation low temperatures. Federation of European Micro- by micro-organisms. Atmospheric Chemistry and biological Societies (FEMS) Microbiology Ecology Physics 7, 4159–4169. 59, 242–254. 26. Amato P, Parazols M, Sancelme M, Mailhot G, Laj P, 1. Morris CE, Sands DC, Bardin M, Jaenicke R, Vogel B, and Delort A-M 2007. An important oceanic Leyronas C, Ariya PA, and Psenner R 2008. Micro- 15. Bauer H, Kasper-Giebl A, Löflund M, Giebl H, source of micro-organisms for cloud water at the biology and atmospheric processes: an upcoming Hitzenberger R, Zibuschka F, and Puxbaum H 2002. Puy de Dôme (France). Atmospheric Environment era of research on bio-meteorology. Biogeo- The contribution of bacteria and fungal spores to 41, 8253–8263. sciences Discussion 5, 191–212. the organic carbon content of cloud water, precipi- tation and aerosols. Atmospheric Research 64, 27. Lighthart B 1984. Microbial aerosols: estimated 2. Upper CD and Vali G 1995. The discovery of bacte- 109–119. contributions of combine harvesting to an airshed. rial ice nucleation and its role in the injury of Applied and Environmental Microbiology 47, 430– plants by frost. In: Lee Jr. RE, Warren GJ, and Gusta 16. Sattler B, Puxbaum H, and Psenner R 2001. Bacte- 432. LV Eds. Biological Ice Nucleation and its Applica- rial growth in supercooled cloud droplets. Geo- tions. St. Paul: APS Press. pp. 29–41. physical Research Letters 28, 239–242. 28. Lighthart B and Shaffer BT 1994. Bacterial flux from chaparral into the atmosphere in mid-summer at 3. Möhler O, Demott PJ, Vali G, and Levin Z 2007. 17. Marinoni A, Laj P, Sellegri K, and Mailhot G 2004. a high desert location. Atmospheric Science 28, Microbiology and atmospheric processes: the role Cloud chemistry at the Puy de Dôme: variability 1267–1274. of biological particles in cloud physics. Biogeo- and relationships with environmental factors. At- sciences 4,1059–1071. mospheric Chemistry and Physics 4, 715–728. 29. Lighthart B 1997. The ecology of bacteria in the alfresco atmosphere. Federation of European 4. Morris CE, Georgakapolous D, and Sands DC 2004. 18. Christner BC, Morris CE, Foreman CM, Cai R, and Microbiological Societies (FEMS) Microbiology Ice nucleation active bacteria and their potential Sands DC 2008. Ubiquity of biological ice nu- Ecology 23, 263–274. role in precipitation. Journal de Physique IV France cleators in snowfall. Science 319, 1214. 121, 87–103. 19. Christner BC, Rongman C, Morris CE, McCarter KS, 30. Lindemann J, Constantinidiou HA, Barchet WR, and Upper CD 1982. Plants as source of airbone bacte- 5. Franc GD and DeMott PJ 1998. Cloud activation Foreman CM, Skidmore ML, Montross SN, and ria, including ice nucleation-active bacteria. Applied characteristics of airborne Erwinia carotovora cells. Sands DC 2008. Geographic location, season, and and Environmental Microbiology 44, 1059–1063. Journal of Applied Meteorology 37, 1293–1300. precipitation chemistry influence on the abun- dance and activity of biological ice nucleators in 31. Morris CE and Kinkel LL 2002. Fifty years of 6. Snider JR, Layton RG, Caple G, and Chapman D rain and snow. Proceedings of the National Acad- phyllosphere microbiology: Significant contribu- 1985. Bacteria as condensation nuclei. Journal de emy of Sciences of the United States of America tions to research in related fields. In: Lindow SE, Recherches Atmospheriques 19, 139–145. (PNAS) 105, 18854–18859. Hecht-Poinar EI, and Elliot V, Eds. Phyllosphere 7. Hildebrand PD, Laycock MV, and Thibault P 1990. 20. Sands DC, Langhans VE, Scharen AL, and de Smet Microbiology. Minneapolis, APS Press, pp. 353–363. Biosurfactant production by pectolytic fluorescent G 1982. The association between bacteria and rain 32. Georgakapoulos DG and Sands DC 1992. Epiphytic pseudomonads and its role in broccoli head rot. and possible resultant meteorological implications. populations of Pseudomonas syringae on barley. Canadian Journal of Plant Pathology 12, 334. Quarterly Journal of the Hungarian Meteorological Canadian Journal of Microbiology 38, 111–114. 8. Ahern HA, Walsh KA, Hill TCJ, and Moffett BF 2007. Service 86, 148–152. 33. Lindow SE, Arny DC, and Upper CD 1978. Distribu- Fluorescent pseudomonads isolated from Hebri- 21. Morris CE, Sands DC, Vinatzer BA, Glaux C, Guilbaud tion of ice nucleation-active bacteria on plants in dean cloud and rain water produce biosurfactants C, Buffière A, Yan S, Dominguez H, and Thompson nature. Applied and Environmental Microbiology but do not cause ice nucleation. Biogeosciences 4, BM 2008. The life history of the plant pathogen 36, 831–838. 115–124. Pseudomonas syringae is linked to the water cycle. 34. Leyronas C, Marloie O, and Morris CE 2008. Meas- 9. Deguillaume L, Leriche M, Amato P, Ariya PA, Delort International Society for Microbial Ecology (ISME) urement of bacterial flux over a wheat crop and A-M, Pöschl U, Chaumerliac N, Bauer H, Flossmann Journal 2, 321–334. characterization of particles transporting bacteria. AI, and Morris CE 2008. Microbiology and atmos- 22. Möhler O, Georgakopoulos DG, Morris CE, Benz S, Applied Aspects of Aerobiology 89, 31–36. pheric processes: Chemical interactions of primary Ebert V, Hunsmann S, Saathoff H, Schnaiter M, and biological aerosols. Biogeosciences 5, 1073–1084. Wagner R 2008. Heterogeneous ice nucleation ac- 10. Stackman E and Christensen CM 1946. Aerobiol- tivity of bacteria: new laboratory experiments at ogy in relation to plant disease. Botanical Review simulated cloud conditions. Biogeosciences 5, 12, 205–253. 1445–1435.

46 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Early Career Scientist Workshop 20–22 August 2009, Melbourne

Early Career Scientist Workshop (ECSW) is Keynote sessions: organised by iLEAPS in collaboration with ● GEWEX, hosted by the University of Mel- Land-atmosphere interactions bourne. ● Satellite sensors and remotely sensed We welcome early career scientists to products participate in this lively event to interact ● Local-to-regional and regional-to-global with other students, scientists and expert interfaces (upscaling/downscaling issues) senior scientists! The workshop is structured around comprehensive keynote presenta- ● Interaction of biogeochemical, water, and tions and related training and discussion energy cycles sessions on the topics outlined below. The ● Land-ocean interface - the coastal zone participants are invited to present their work ● in the form of posters accompanied by an Data-model assimilation optional 2-minute oral summary. ● Science-to-applications interface

Invited speakers and tutors: Training and discussion sessions: ● ● Will Steffen (ANU, Australia) Remote sensing applications ● ● Diego Fernandez (ESA, Italy) Data fusion in remote sensing applications ● William Lahoz (NILU, Norway) ● Data-model assimilation ● Mike Raupach (CSIRO, Australia) ● Q & A session with experts ● Jenni Metcalfe ● (Econnect Communication, Australia) Communication and presentation skills – preparing a 2-minute ● Susannah Eliott (AUSSMC, Australia) oral summary of posters ● Lindsay Hutley (CDU, Australia) ● Communicating science to media and policy makers

Please see www.ileaps.org/ecsw for more information.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 47 Carlos Jimenez graduated in engineering at the Telecommunication Engineering School (ETSIT), Technical University of Madrid, Spain, and got his MSc in environmental measurement techniques and his PhD in environmental science at Chalmers University, Gothenburg, Sweden. He is currently a researcher at the Laboratory for the Study of Radiation and Matter in Astrophysics (LERMA), Paris Observatory, working on the characterisation of the land surface from multi- wavelength satellite observations. His group has a long experience in exploiting global satellite datasets to characterise continental surfaces, including the production of a continental atlas of microwave emissivities directly estimated from satellite observa- tions, and the first global estimations of inundated (flood-covered) areas over several years.

Carlos Jimenez1, Catherine Prigent1 and Filipe Aires2 1. Laboratoire d’Etude du Rayonnement et de la Matière en Astrophysique (LERMA), l’Observatoire de Paris, Paris, France 2. Laboratoire de Météorologie Dynamique (LMD), Institut Pierre Simon Laplace (IPSL), Université Paris VI, Paris, France Combining multi-satellite observations and land surface models to estimate land-surface heat fluxes

Land-surface heat fluxes are essential com- to be indirectly estimated from satellite ob- land surface models (where the satellite ponents of the water and energy cycles and servations containing information about the observations are directly incorporated into govern the interactions between the Earth surface and atmospheric properties that the model). The problem is that the current surface and the atmosphere [1]. Over land, control the fluxes (for instance, surface and flux estimates at a global scale from different energy balance and flux partitioning (divi- air temperature and humidity). schemes can still differ considerably. sion of outgoing energy into fluxes of latent How to merge the information coming Contributing towards the goal of pro- heat (evapotranspiration) and sensible heat from the satellite observations to derive the ducing global land-surface heat fluxes, we (rising of warm air)) are complex mecha- fluxes is not straightforward. Acknowledging have evaluated the potential of a suite of nisms that vary strongly in both space and these difficulties, the Global Energy and satellite observations to estimate the latent time and across climates and ecosystems Water Cycle Experiment (GEWEX) Radiation and sensible heat fluxes over snow-free con- depending on the physical properties of the Panel (GRP) launched the LANDFLUX activity tinents. We used a methodology based on surface. to develop the necessary capabilities to pro- calibrating a statistical method that links the Land-surface heat fluxes are measured duce a complete, physically consistent, glo- satellite observations to the fluxes [2]. The during field experiments and by some flux bal, multi-decadal land-surface heat flux data statistical model (SM, based on neural net- tower networks. However, in order to obtain product. works) learns the global relationship be- global, consistent estimates of the surface Different schemes to produce the fluxes tween satellite data and fluxes, and is then heat fluxes, a transition to satellite remote already exist. They range from simple physi- used to map the satellite observations into sensing is necessary. cal formulations (having as inputs the heat fluxes. The challenge is that fluxes cannot be surface and atmospheric properties derived The satellite observations were selected remotely detected. Therefore, the fluxes have from the satellite observations) to complex for their known sensitivity to the surface

48 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Example of the original LSM GSWP multi- this specific period as one of the satellite inputs latent heat flux; bottom right: the estimated SM model and corresponding estimated satellite-de- was not available. Top left: the original LSM GSWP latent heat flux. rived SM monthly mean fluxes for August 1995. sensible heat flux; top right: the estimated SM sensi- The fluxes were not estimated over central Asia for ble heat flux; bottom left: the original LSM GSWP properties that affect the fluxes (soil mois- The LSM fluxes and satellite data were the scheme more robust to the lack of one ture, surface temperature and its diurnal cy- gridded with a spatial resolution of 0.25˚x specific observation. cle, vegetation) as well as for their global 0.25˚ and used as monthly averages for the We evaluated the quality of the original coverage and their availability over many 1993–1995 period. Independent SMs for LSM fluxes and the SM estimates. Compared years. They covered a broad range of wave- each combination of satellite observations to one another, the three LSMs and the lengths from the visible to the microwaves, and specific LSM were set and calibrated NCEP/NCAR reanalysis considered here pro- including visible and near-infrared reflect- with 4 months of fluxes and observations in duced sometimes quite different fluxes in ances (Advanced Very High Resolution Radi- 1993. some regions both in terms of magnitude ometer, AVHRR), radiative fluxes and thermal Once calibrated, the SMs were used to and spatial structures. This was true espe- infrared surface skin temperature and its map the satellite observations into fluxes for cially for the sensible heat fluxes, even when diurnal cycle (International Satellite Cloud the remaining months in 1993–1995. For the three LSMs shared the same forcing Climatology Project, ISCCP), active microwave this period, the SMs reproduced the LSM (meteorological inputs), as did the multi- backscatter (European Remote Sensing sat- fluxes on a global scale with theoretical root model, ISBA, and ORCHIDEE. Obviously, hav- ellite system, ERS scatterometer), and passive mean square (RMS) errors < 25 W m-2, prov- ing been trained with the LSMs, the SMs microwave emissivities (Special Sensor Mi- ing that the satellite data contained relevant cannot remove existing biases like these at crowave Imager, SSM/I). information for flux estimation. the global scale but for specific regions Because in situ flux measurements are In general, the spatial and temporal pat- where there is a departure from global rela- very scarce in space and time, we calibrated terns of the LSM fluxes were well captured tionship, they can potentially produce local the SMs with fluxes calculated from land sur- in the satellite-derived fluxes produced by fluxes that are more consistent with the face models (LSM) which we regarded as the SM (see an example with the GSWP learned global relationships. the most reliable estimates of land-surface multi-model fluxes in Fig. 1). For instance, the comparison between heat fluxes at the global scale. Three Global the original LSM fluxes and the SM-esti- Soil Wetness Project (GSWP) version 2 [3] These SMs were calibrated with all the mated fluxes at the end of 1995 revealed an estimates of the fluxes were selected (the satellite observations as inputs, but SMs cali- anomaly in the LSM heat fluxes related to an fluxes estimated by the multi-model analysis, brated only with individual satellite observa- anomaly in the radiative fluxes used to force and the two participating LSMs ISBA and tions (for instance, only with AVHRR and the model. Fig. 2 shows these anomalous ORCHIDEE), along with the National Centers ISCCP data) were also tested, and they could heat fluxes around the Tapajos National For- for Environmental Prediction (NCEP) / the not yield such results. est station in Brazil. This scheme can thus National Center for Atmospheric Research The synergetic use of various wave- help diagnose specific problems with the (NCAR) reanalysis NCEP/NCAR (a retroactive lengths with complementary sensitivity LSMs, though any discrepancies between record of more than 50 years of global clearly improved the ability to reproduce the original and estimated fluxes have to be atmospheric analyses produced by a frozen fluxes for all types of environments. The use evaluated also in the context of possible global data assimilation). of multiple satellite information also made observation artefacts or errors introduced by

iLEAPS Newsletter Issue No. 7 ◆ June 2009 49 Figure 2. Averaged fluxes in a 2ox2o box around the bottom right: the SM latent heat flux. Fluxes the station over the 2002–2006 period (black, with Tapajos National Forest station near Santarém in displayed correspond to the three LSMs: multi- thin solid lines plotting the tower monthly maxi- Brazil (3oS 55oW). Top left: the original LSM sensible model analysis (red), ISBA (green), ORCHIDEE (blue), mum and minimum fluxes for that period). heat flux; top right: the SM sensible heat flux; the NCEP/NCAR reanalysis (yellow), and an annual bottom left: the original LSM latent heat flux; and climatology built by averaging the tower fluxes at

the SM itself. The scheme is general and other regions remains very challenging in can be applied to other LSM variables (for the absence of validation data, and the instance, to modelled soil moisture [4]). arguable better accuracy of the satellite- A quantitative assessment of the accu- derived SM fluxes in those regions remains racy of both original and estimated fluxes is to be demonstrated. very difficult because of the lack of valida- Data assimilation is the incorporation of tion data. We did collect flux-tower measure- observations into a numerical model with ments and compared them with the original the purpose of providing the model with LSM and the SM-estimated fluxes but the the best estimate of the current state of a comparison was rather limited because: system. In that sense, the proposed method- 1) the geographical coverage of the tower ology can be considered similar in nature to data was largely limited to mid-latitude an assimilation scheme as the LSM fluxes are environments, which are not the regions merged with the satellite observations with 1. Betts A, Ball J, Beljaars A, Miller M, and Viterbo PA, where the largest differences among the the objective of providing a better estimate 1996. The land surface-atmosphere interaction: LSM fluxes are observed; of the fluxes. a review based on observational and global modeling perspectives. Journal of Geophysical This also means that the satellite-derived 2) flux point measurements (towers) were Research 101, 7209–7226. SM fluxes will always be related to a specific compared with fluxes averaged over LSM flux, and the method cannot then de- 2. Jimenez C, Prigent C, and Aires F 2009. Toward an large areas (LSMs); and rive independent land-surface heat fluxes estimation of global land heat fluxes from multi- satellite observations. Journal of Geophysical Re- 3) there were hardly any tower data for the from satellite observations. Nevertheless, the search, 114, D06305, doi:10.1029/2008JD011392. years considered during the GSWP exer- fact that independent satellite observations cise, so the comparison had to be based can be related to LSM fluxes with a sufficient 3. Dirmeyer P, Gao AX, Zhao M, Guo Z, Oki T, and on a climatology of the tower flux meas- level of accuracy is already a positive sign for Hanasaki N 2006. GSWP-2: Multimodel analysis and implications for our perception of the land urements derived from the later 2000– relating these observations to the real-world surface. Bulletin of the American Meteorological 2006 period. fluxes, and the proposed methodology can Society 87, 1831–1397. Although some examples tended to be considered as a pragmatic step forward in the search of reliable methodologies for 4. Aires F, Prigent C, and Rossow W 2005. Sensitivity show that the SM fluxes were closer to the of satellite microwave and infrared observations to flux estimation at a global scale. ■ flux tower climatologies when the differ- soil moisture at a global scale: 2. Global statistical ences between the LSM and tower fluxes relationships. Journal of Geophysical Research 110, were large (see for instance Fig. 2), a sys- D11103, doi: 10.1029/2004JD005094. tematic comparison with all the available 5. Aires F and Prigent C 2006. Toward a new genera- stations (mostly at mid-latitudes with the tion of satellite surface products? Journal of Geo- AmeriFlux network) did not statistically physical Research 111, D22S10, doi: 10.1029/ prove it. The extension of the exercise to [email protected] 2006JD007362.

50 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Water in a Changing Climate: Progress in Land-Atmosphere Interactions and Energy / Water Cycle Research iLEAPS and GEWEX International Science Conferences in parallel in Melbourne, Australia 24–28 August 2009

Joint iLEAPS/GEWEX sessions: Joint iLEAPS-GEWEX session A. Land in the climate system keynote speakers: B. Aerosol, cloud, precipitation Piers J. Sellers (NASA, USA) and climate interactions John Thwaites (Monash Sustainability C. Future generation of integrated Institute, Australia) observation and modelling systems Paulo Artaxo (University of São Paulo, Brazil) iLEAPS sessions: Roger R. Pielke, Jr. (Center for Science and Techhnology Policy Research, USA) 1. Surface exchange processes from leaf level to Earth system scale Invited speakers in other sessions: 2. Progress in land-atmosphere interactions Meinrat O. Andreae (Max Planck Institute and climate change 3. The role of atmospheric boundary layer for Chemistry, Germany) processes in modulating surface Jason Beringer (Monash University, Australia) exchanges Gordon Bonan (NCAR, USA) 4. Aerosols from the land surface and their Hugh Coe (University of Manchester, UK) interactions with the climate system Paul Dirmeyer (COLA, USA) Harm Jonker (Delft University Scientific program of Technology, Netherlands) committee is led by Thomas Karl (NCAR, USA) Prof. Pavel Kabat ([email protected]) David Lawrence (NCAR, USA) Prof. Soroosh Sorooshian ([email protected]) Scot Martin (Harvard University, USA) Belinda Medlyn (Macquarie University, Australia) Local organizing Teruyuki Nakajima (University of Tokyo, Japan) committee is led by Colin Prentice (University of Bristol, UK) Prof. Christian Jakob Peter Rayner (LSCE, France) ([email protected]) Mike Raupach (CSIRO, Australia) Contact information Danny Rosenfeld (Hebrew University, Israel) Leon Rotstayn (CSIRO, Australia) iLEAPS IPO ([email protected]), Adrian Simmons (ECMWF, UK) www.ileaps.org Kevin Trenberth (NCAR, USA) GEWEX IPO Timo Vesala (University of Helsinki, Finland) ([email protected]), Dennis Baldocchi (University of California, USA) www.gewex.org Lina Mercado (Centre for Ecology & Hydrology, UK)

More information on Melbourne events also at: www.ileaps.org/science_conf_2009

iLEAPS Newsletter Issue No. 7 ◆ June 2009 51 Siikaneva wetland in southern Finland. Photo: Lauri Laakso. Bruno Ringeval1, Bertrand Decharme2, Shilong Piao3, Pierre Friedlingstein1, Philippe Ciais1, Catherine Prigent4 and Nathalie de Noblet-Ducoudré1 1. Laboratoire des Sciences du Climat et de l’Environnement (LSCE), Gif-sur-Yvette, France 2. Centre National de Recherches Météorologiques, Météo-France, Toulouse, France 3. Department of Ecology, Peking University, Beijing, China 4. Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique, Observatoire de Paris, Centre National de la Recherche Scientifique (CNRS), Paris, France Wetland extent under climate change and its potential role on future methane emissions

The feedbacks between wetland emissions present-day conditions and to validate it us- sensed wetland area observations during and the climate change have been previ- ing data from multiple satellite observations the period 1993–2000 [5]. Relative wetland ously hypothesised [1] but their existence [4]. The second aim was to estimate wetland extent, seasonality, and interannual variability and strength remain uncertain [2]. Climate extent under future climate conditions and were reproduced with good agreement in

variability influences methane (CH4) sources to quantify the potential role of this wetland several regions. from wetlands via changes in methane flux area modification on methane emissions. Next, to calculate future changes in po- and via changes in wetland areas in re- To compute wetland extent, we inte- tential wetland extent, we used outputs of sponse to surface hydrological processes. grated a TOPMODEL [5] approach in the glo- one climate system model (IPSL-CM4) Previous studies [3] have shown that bal vegetation model ORCHIDEE [6]. Using obtained under the economic scenario (de- wetland area variations must be taken into sub-grid topography and soil water content, scription of possible future levels of emis- account in order to understand the variabil- TOPMODEL calculated the water-saturated sions and environmental variables) A2 pub-

ity in current CH4 emissions from wetlands. fraction of each pixel [7, 8]. Wetland extent lished by the Intergovernmental Panel on The first aim of this study was to simu- was then calculated based on the saturated Climate Change (IPCC) in 2000. The A2 sce- late, in a very simple way, wetland extent for fraction and compared to the remotely- nario describes a very heterogeneous world

52 iLEAPS Newsletter Issue No. 7 ◆ June 2009 1. IPCC 2001: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linder PJ, Dai X, Maskell K, and Johnson CA (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881 pp. 2. Gedney N, Cox PM, and Huntingford C 2004. Climate feedback from wetland methane emis- sions. Geophysical Research Letters 31, L20503, doi:10.1029/2004GL020919. 3. Ringeval B, de Noblet-Ducoudré N, Ciais P, Bousquet P, Prigent C, and Papa F 2009. An Figure 1. Annual methane emissions for each future flux densities and current wetland extent. attempt to quantify the impact of changes in latitude band using different combinations of flux The relative position among DPEP, DFEF and DFEP for wetland extent on methane emissions at the densities (D)/wetland extent (E). The subscripts P each latitude band indicates the influence of seasonal and interannual time scales. Global and F refer to Present and Future. For example, D E wetland extent changes on CH emissions. F P 4 Biogeochemical Cycles (submitted). means that CH emissions were computed using 4 4. Prigent C, Papa F, Aires F, Rossow WB, and Matthews E 2007. Global inundation dynamics in- ferred from multiple satellite observations, 1993– with continuously increasing global popula- Our results showed that in the boreal 2000. Journal of Geophysical Research 112, tion and comparatively slow economic regions the seasonality of wetland extent D12107, doi:10.1029/2006JD007847. growth (http://sedac.ciesin.columbia.edu/ changes: because of hotter summers and 5. Beven KJ and Kirkby MJ 1979. A physically based ddc/sres). In order to remove systematic bi- milder winters, the maximum summer ex- variable contributing area model of basin hydrol- ases of the IPSL model, we also used current tent of wetlands will decrease although the ogy. Hydrological Science Bulletin 24, 43–69. observed climatological fields of the Univer- maximum extent lasts longer. This leads to a 6. Krinner G, Viovy N, de Noblet-Ducoudré N, Ogee J, sity of East Anglia’s Climate Research Unit [9]. slower increase in CH emissions than pre- 4 Polcher J, Friedlingstein P, Ciais P, Sitch S, and According to our results, the changes in dicted previously even though the total an- Prentice IC 2005. A dynamic global vegetation annual wetland extent were minor in each nual wetland extent increases. On the con- model for studies of the coupled atmosphere-bio- latitude band except in boreal regions trary, the increased wetland extent in the sphere system. Global Biogeochemical Cycles 19, where the annual wetland area increased by tropics can explain 25% of the predicted in- GB1015, doi:10.1029/2003GB002199. crease in CH emissions in this region. about 20%. We also calculated CH4 flux den- 4 7. Habets F and Saulnier GM 2001. Sub-grid runoff sities under the current and future climates; To conclude, predicting the variations parameterization. Physics and Chemistry of the our results predicted that CH4 emissions in wetland extent is necessary for reliable Earth 26, 455–459. would increase in the future in each latitude simulations of changing methane emissions 8. Decharme B, Douville H, Boone A, Habets F, and band, with large variations from one latitude under the changing climate. ■ Noilhan J 2006. Impact of an exponential profile of band to another. saturated hydraulic conductivity within the ISBA Finally, using different combinations of LSM: simulations over the Rhone Basin. Journal of Hydrometeorology 7(1), 61–80. wetlands extent/CH4 flux to compute CH4 emissions (Fig. 1), we analysed the role the 9. Climatic Research Unit (CRU), surface plays in future CH4 emissions. [email protected] www.cru.uea.ac.uk/

iLEAPS Newsletter Issue No. 7 ◆ June 2009 53 Catherine Van den Hoof is currently a research scien- tist at the Belgian Nuclear Research Centre, studying the role of vegetation in the dispersion of radio- nuclides in the ecosystem. She was trained as an agronomist at the Catholic University of Leuven (K.U. Leuven, Belgium) and completed further studies in geographic information systems and remote sensing at the Wageningen Agricultural University (the Neth- erlands), where she then participated in the STEREO HyECO’04 campaign. The purpose of this project was to link biochemical and biophysical variables derived from imaging spectrometers to ecological models. In September 2004, she started a PhD on the influence of crop production on land-atmosphere interactions at the Department of Meteorology, University of Reading (UK).

Catherine Van den Hoof1,2 and Pier Luigi Vidale1 1. Department of Meteorology, University of Reading, Reading, UK 2. Belgian Nuclear Research Centre, Mol, Belgium Process-based crop growth within the land-surface model JULES

It is estimated that approximately 18% of the land surface is used for crop production [1]. The increasing demand for food and for- est products, in conjunction with the climate change, is expected to significantly alter the terrestrial ecosystem and, by consequence, the energy, water, and carbon fluxes be- tween land and the atmosphere [2]. In addition, the availability of resources such as water further constrains agricultural production in many regions. In order to eval- Figure 1. The available soil moisture within the field (red) simulated with JULES over a single grid uate the sustainability issues that we will depth of 3 m on a grassland (green) and a wheat cell in France (47°51’N, 2°41’E) for the year 1995. face in the near future, we need to under- stand the relationships between crop pro- duction, land-surface characteristics, and the resulting model was denoted JULES- the model over a single grid in France energy and water cycles. SUCROS. JULES-SUCROS incorporates crops (47°51’N, 2°41’E) for the growing season of In this study, these relationships are ana- and natural vegetation within the same bio- 1995. So far the study has been restricted to lysed using the Joint UK Land Environment geochemically consistent numerical frame- wheat, the most abundant crop type world- Simulator (JULES) [3]. JULES was originally work. wide. Wheat is also cultivated extensively designed to represent the land surface in Prior to any model adaptation, however, throughout Europe. meteorological and climate models devel- we investigated the sensitivity of JULES to The conversion from natural grassland oped in the UK. Its scheme includes the full morphological and physiological differences to cropland in JULES resulted in a distinct hydrological cycle and vegetation effects on between natural vegetation and crops by overall increase in annual soil moisture energy, water, and carbon fluxes. However, reparameterising a natural grass into a crop. content (Fig. 1). JULES simulates land surface processes only To this end, we forced (used as input) In the simulation, the soil retained more in natural ecosystems. JULES with observed time series of the crop’s water after harvest because the transpiration To represent crop growth, development, LAI (leaf area index, the area of leaf surface by plants ceased on the bare crop field; this and harvest, we added crop modules to per unit ground area), height, and rooting difference in soil moisture (~70 kg m-2 in JULES. Since most of the crop modules were depth. To better understand the physics be- autumn) was significant when compared to derived from the crop model SUCROS [4], hind the surface exchange processes, we ran the seasonal variability (~200 kg m-2).

54 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 2. a) Leaf area index (LAI) and b) latent heat simulated with JULES (‘static’) and a more dynamic (black)) with crop emergence at +30 days (red), (energy needed for a change of phase e.g. energy cropland simulated with JULES-SUCROS (‘dynamic’), and –30 days (green) compared to control (black). released during evapotranspiration) on a cropland and their anomalies (departures from the control The arrows represent the emergence days.

The soil moisture increase remained Therefore, the emergence time had a strong simulations without a dynamic crop-growth through the autumn. The higher water effect on the evapotranspiration (evapora- structure might strongly bias the effects of content of the soil limited the infiltration tion from surfaces and transpiration by changes in atmospheric conditions on the capacity of the soil during the winter (more plants), and by consequence on the hydro- land surface. run-off). As already indicated by Twine in his logical cycle. On the other hand, because In the near future, we will couple JULES- study on the Mississippi Basin [5], the the dynamic crop adapted its growth and SUCROS back to the UK climate model and changes in the energy and water balance development to new environmental condi- study the feedbacks between crop growth after the grass-to-crop conversion were tions, it matured always at roughly the same and the climate system. mainly due to the changes in the growing time of the year regardless of emergence However, we first need to test JULES- season length and timing, and in particular time. Hence, the influence of dynamic-crop SUCROS on other sites for several consecu- the evaporative seasons, not to the physi- emergence on the land surface and fluxes tive years to evaluate its sensitivity to ological differences between the vegetation was less significant (Fig. 2). changes in environmental conditions, crop types. The ability of the dynamic crop to adapt type, and inter-annual variability. To achieve Having shown that JULES was indeed to a changing environment was noted also this, the data collected in the framework of sensitive to grass-to-crop conversion, we fur- under climate change conditions. At the FLUXNET and CarboEurope projects will be ther converted the static cropland into the level of the individual organs, the influence very useful. ■ more dynamic cropland of JULES-SUCROS. of changed environmental conditions varied. [email protected] The timing of the dynamic crop emergence For example, under changed climate the depends on the prevailing meteorology and dynamic crop produced less total biomass 1. United Nations Food and Agricultural Organisation crop requirements. The development rate of (~-20%) because of the shorter develop- (FAO) 2002. Crops and drops: Making the best use the dynamic crop is determined by tem- ment time (result of faster development rate of water for agriculture. Technical report, Food and perature, and the growth rate of each organ under higher temperatures) and the lower Agriculture Organization. United Nations, Rome. (root, stem, leaf, and storage organs) is a water availability. Grain production, however, 2. Foley J, DeFries R, Asner GP, Barford C, Bonan G, function of phenological stage, partitioning did not suffer from the new conditions Carpenter SR, Chapin FS, Coe MT, Daily GC, Gibbs of assimilates to organs, and environmental simply because the faster development rate HK, Helkowski JH, Holloway T, Howard EA, Kucharik conditions. The biophysical parameters LAI, moved the grain filling period earlier in the CJ, Monfreda C, Patz JA, Prentice IC, Ramankutty N, crop height, and rooting depth, which link year when the water stress was smaller. and Snyder PK 2005. Global consequences of land use. Science 309, 4570–574. the vegetation and the land surface, are dy- JULES-SUCROS is still under develop- namic and consistent with the growth and ment but we can already conclude that the 3. Cox PM, Huntingford C, and Harding RJ 1998. A development of the crop organs. canopy conductance and photosynthesis model influence of crop growth and development for use in a GCM land surface scheme. Journal of Next, we compared the effect of different on energy and water fluxes is important be- Hydrology 212, 79–94. crop emergence times (control, +30 days, cause of the strong interactions between 4. Goudriaan J and van Laar HH 1994. Modelling po- and –30 days) on the crop growth and de- crops, land surface, and the atmosphere. tential crop growth processes. Kluwer Academic velopment, and surface fluxes for the static A change in the length and timing of Publishers,Dordrecht, 238 pp. and the dynamic crops (Fig. 2). the growing season has an important effect 5. Twine ET, Kucharik CJ, and Foley JA 2004. Effects of Since its phenological cycle is prescribed, on the hydrological cycle. This, in turn, might land cover change on the energy and water bal- the static crop developed at an equal rate influence weather and climate and feed ance of the Mississippi River Basin. Journal of regardless of the timing of crop emergence. back to the crop’s life cycle. Therefore, Hydrometeorology 5, 640–655.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 55 Alexis Berg1,2, Benjamin Sultan1 and Nathalie de Noblet-Ducoudré2 1. Laboratoire d’Océanographie et du Climat: Expérimentation et Approches Numériques (LOCEAN), Paris, France 2. Laboratoire des Sciences du Climat et de l’Environnement (LSCE), Gif-sur-Yvette, France Including tropical croplands in a terrestrial biosphere model: application to West Africa

Studying the large-scale relationships be- and yield when tested at an experimental with FAO data was significant for some tween climate and agriculture raises two station in Senegal (Fig. 1). We then applied countries (R=0.51 for Niger, 0.48 for Burkina coupled questions: the influence of climate the model over West Africa, forced by the Faso). on crops, and the potential feedbacks to NCC dataset (NCEP [National Centers for As the next step, we analysed how the climate from croplands through biophysical Environmental Prediction] reanalysis Cor- simulated land surface fluxes were influ- and biogeochemical processes. rected by CRU [Climatic Research Unit] enced by the explicit accounting for crop- A consistent framework to address this monthly data) over 1965–2000. lands. We compared the 36-year simulation twofold issue in an integrated way is to First, we compared the simulated yield at by ORCH-mil with one by ORCHIDEE which extend existing Dynamic Global Vegetation national scale with data from the Food and represents croplands as grasslands. Models (DGVM), which simulate vegetation Agricultural Organisation of the United Significant differences appeared, mainly on a global scale and can be coupled to Nations (FAO) database. Because the model at the end of the rainy season: contrary to climate models, explicitly to croplands. So simulates a highly productive variety sowed grasslands, croplands are then harvested and far, most of the DGVM only approximate at high density, which corresponds to experi- replaced by bare soil. Thus, on average, croplands by grasslands. mental conditions but not to local on-farm latent heat fluxes (evapotranspiration) in Following this approach for tropical situations, it largely overestimates average ORCH-mil were smaller (by up to 25% annu- croplands, we included in the IPSL (Institut yields. This problem should be corrected in ally) whereas sensible heat fluxes (warm air Pierre-Simon Laplace) land-surface model further model developments. rising) and albedo were higher. ORCHIDEE [1] processes and parameteri- However, in terms of interannual variabil- These differences in land surface fluxes sations taken from an existing crop model, ity, the model already captures the relation- between grasslands and croplands may be SARRAH [2], which is routinely used by ship between crop yields and rainfall (which, reflected also in the monsoon system, agronomists for millet in West Africa. The in the context of tropical rainfed agriculture, mainly during the retreat of monsoon rains. resulting version of ORCHIDEE, called ORCH- is the main climatic forcing) correctly. The Coupling ORCH-mil to an atmospheric mil [3], realistically simulates millet growth positive correlation (R) of the model results model should enable us to investigate such a question. ■ [email protected]

1. Krinner G, Viovy N, de Noblet-Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S, and Prentice IC 2005. A dynamic global vegetation model for studies of the coupled atmosphere- biosphere system. Global Biogeochemical Cycles 19, GB1015. 2. Dingkuhn M, Baron C, Bonnal V, Maraux F, Sarr B, Sultan B, Clopes A, and Forest F 2003. Decision- support tools for rain-fed crops in the Sahel at the plot and regional scale. In: Struif-Bontkes TE, Wopereis MCS (Eds.). A practical guide to decision- support tools for agricultural productivity and soil fertility enhancement in sub-Saharan Africa. An In- ternational Center for Soil Fertility & Agricultural Development (IFDC), Muscle Shoals, USA, pp 127– 139. Figure 1. Comparison between standard version of area on unit ground area), (b) total biomass, (c) leaf 3. Berg A, Sultan B, and de Noblet-Ducoudré N 2009. ORCHIDEE (dotted line), the crop model SARRAH biomass, (d) root biomass, (e) stem biomass, and (f) Including tropical croplands in a terrestrial bio- (full line), and ORCH-mil (dashed lines) for fruit biomass, for year 1997 in Bambey, Senegal sphere model: application to West Africa. Climatic simulations of (a) leaf area index (LAI, sum of leaf (biomasses are in g (C) m-2). Change (submitted).

56 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Katherine D. Corbin1,2, A. Scott Denning1, Erandi Y. Lokupitiya1, Kenneth J. Davis3, Natasha Miles3, Scott Richardson3 and Ian T. Baker1

1. Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA 2. Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marine and Atmospheric Research, Aspendale, Australia 3. Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA

Effects of agricultural production on regional CO2 fluxes and concentrations

To investigate regional carbon fluxes and the CO2 for the summer. The mid-continental re- This study showed that corn and mechanisms driving them, the North Ameri- gion was a sink of CO2, and the northern half soybean are highly productive crops that can Carbon Program (NACP) launched a of the continent was also a moderate sum- significantly influence both regional CO2 Mid-Continent Intensive (MCI) Campaign in mertime sink. fluxes and concentrations. ■ 2007 centred over the Midwestern United The average distribution of CO concen- 2 [email protected] States [1]. As part of the MCI campaign, tration matched the carbon fluxes, with high high-precision atmospheric carbon dioxide concentrations in the South East and low

(CO2) concentrations were sampled at five concentrations in the North. This large-scale communications towers throughout the re- concentration gradient over the mid-conti- gion [2]. nent was strong, with differences of over 4

In this study, we analysed CO2 fluxes and ppm in the total column and over 40 ppm concentrations from June through August near the surface between North and South. 1. Ogle S, Davis K, Andrews A, Gurney K, West T, Cook 2007 using the coupled ecosystem-atmos- Average wind flow shifted this large-scale R, Parkin T, Morisette J, Verma S, and Wofsy S 2006. phere model SiB3-RAMS [3,4]. gradient from time to time and the effect Science Plan: Mid-Continent Intensive Campaign of was evident in the CO concentrations ob- To improve the simulation of CO2 fluxes 2 the North American Carbon Program. Prepared for over the mid-continent region, we coupled served at the MCI measuring sites in the the carbon cycle Science Steering Group and the SiB3-RAMS to a crop phenology model that mid-continent. Interagency Working Group on carbon (http:// calculated the leaf area index (LAI), the frac- During southerly winds, the high south- www.carboncyclescience.gov). tion of photosynthetically active radiation ern concentrations created differences of 2. Richardson S, Miles N, Davis K, Crosson E, Denning (FPAR), and the net ecosystem exchange over 30 ppm among the measuring towers S, Zupanski D, and Uliasz M 2007. The second “Ring

(NEE) of CO2 for both corn and soybean [5]. ~300 km apart; however, during northerly of Towers”: over-sampling the Mid-Continent In- As a result, we obtained more realistic fluxes winds, the large-scale gradient shifted to tensive region CO2 mixing ratio? Earth Observing at local scale for these two crops compared the southwest and smaller differences were System (EOS) Transactions, American Geophysical with observations. observable. Union (AGU) 88(52), Fall Meeting Supplement 2007 Abstract B43D-1592R. This coupling approach also dramatically Comparing the modelled CO2 concentra- altered the simulated regional fluxes over tions with the tower data collected during 3. Corbin K, Denning S, Lu L, Wang J-W, and Baker I the central mid-continent, increasing the the MCI campaign revealed that the simu- 2008. Possible representation errors in inversions average summertime uptake from ~ 1–2 lated CO2 concentrations over the MCI re- of satellite CO2 retrievals. Journal of Geophysical µmol m-2 s-1 to more than 6 µmol m-2 s-1. gion improved dramatically when the crop Research 113, D02301, doi:10.1029/2007JD008716. Because of this increased uptake of carbon, model was included, reducing the squared 4. Wang J-W, Denning S, Lu L, Baker I, Corbin K, and the average total column CO2 concentration differences between the observations and Davis K 2007. Observations and simulations of decreased by more than 1 ppm over the the model by nearly half. synoptic, regional, and local variations in atmos- region; concentrations near the surface Including the crop phenology model pheric CO2. Journal of Geophysical Research 112, decreased by more than 20 ppm. also improved the simulated synoptic vari- D04108, doi:10.1029/2006JD007410.

During summer 2007, the south-eastern ability in CO2 concentrations, as well as the 5. Lokupitiya E, Denning S, Paustian K, Baker I, US experienced both a heat wave and a simulated North-South concentration gra- Schaefer K, Verma S, Meyers T, Bernacchi C, Suyker drought. These climatic conditions stressed dient that could be compared with the A, and Fischer M 2009. Incorporation of crop the plants and significantly reduced the observed concentrations at the towers. Con- phenology in Simple Biosphere Model (SiBcrop) to photosynthesis while increasing the respira- centrations lower than 340 ppm were improve land-atmosphere carbon exchanges from tion. As a result, the south-eastern region of observed during July and August in both croplands. Biogeosciences Discussions 6, 1903– the United States became a large source of the model results and in the observations. 1944.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 57 Rita Wania is Research Associate at the Climate Mod- her thesis on modelling methane emissions from elling Laboratory at the University of Victoria, Canada. northern peatlands, she worked on the European Rita started as a plant physiologist studying the Union project HYMN (Hydrogen, Methane and Nitrous nitrogen cycle in the canopy of tropical forests in Costa Oxide: Trend variability, budgets and interactions with Rica as part of her diploma thesis at the University of the biosphere). Now, she is working on implementing Vienna, Austria. She slipped into the world of vege- the terrestrial nitrogen cycle into the UVic (University tation modelling during her PhD thesis under the of Victoria) Earth System Climate Model. supervision of Professor Colin Prentice. After finishing

Rita Wania1, Matthew Jolleys2 and Wouter Buytaert3 1. School of Earth and Ocean Sciences, University of Victoria, Victoria, British Columbia, Canada 2. Department of Earth Sciences, University of Bristol, Bristol, United Kingdom 3. School of Geographical Sciences, University of Bristol, Bristol, United Kingdom A previously neglected methane source from the Andean páramo?

Anaerobic production in wetlands has tradi- bution of methane emissions from plants in páramo, occur in the Andes of Venezuela, tionally been considered the primary natural that area as suggested by [1]. Colombia, Ecuador, and Peru (8°N to 11°S), at

source of methane (CH4) in the world. How- We postulated that high-altitude wet- altitudes between 3200 and 5000 m above ever, recently a new source of methane lands in the tropical Andes had been ne- sea level. emission was discovered: the photochemical glected in the wetland maps used in [6] and The páramo extends over an area of production of methane from plants under that they could be (in part) responsible for around 35000 to 77000 km2 [7]. Páramo aerobic conditions and UV light [1, 2]. In their the high atmospheric concentrations of vegetation is characterised by wet grass- first publication, Keppler et al. [1] suggested methane over the north-western part of lands, with patches of peat bogs, forests and -1 that plants may emit 62–236 Tg yr of CH4, South America. Those wetlands, part of a shrublands; in other words, an ideal habitat i.e., 24–163% of global natural CH4 emissions tropical alpine ecosystem locally known as for methane production. The climate is wet as given by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) [3]. Even though the upper limit of methane emissions from plants was later scaled down to 85 Tg yr-1 [4], it is still uncertain if and how much the photochemi-

cal production contributes to the global CH4 budget. This example shows that natural methane sources are still poorly quantified. Around the same time as the new meth- ane source was discovered [1], Frankenberg et al. [5] published the first satellite-derived information on atmospheric methane mix- ing ratios. The SCIAMACHY satellite instru- ment on board of European Space Agency (ESA)-operated ENVISAT observed very high concentrations of atmospheric methane over the north-western part of South America (Fig. 1). Wetland maps used for an- other study could not explain the high at- mospheric methane concentrations above Colombia and Venezuela, especially from Oc- Figure 1. Atmospheric methane concentrations SCIAMACHY on board of the ENVISAT satellite [5]. tober to December [6]. Bergamaschi et al. [6] (mean column mixing ratio, ppb) averaged from The inset shows the páramo distribution in South pointed towards a potential aerobic contri- January 2003 to December 2004 as observed by America [7].

58 iLEAPS Newsletter Issue No. 7 ◆ June 2009 (annual precipitation from 600 to more than significant anaerobic methane emission 3000 mm) and relatively cold with mean rates, higher than from peatlands in the annual temperatures around 8°C. northern hemisphere [8], although the total We were not aware of any measure- emissions are relatively small because of the ments of methane emissions conducted in areal constraint of the páramo. the Andean páramo. Therefore, we used a Clearly, more work on methane emis- modelling approach to estimate anaerobic sions from this part of the world is necessary. methane emissions from the páramo region. However, our main aim was to show that In order to first determine the potential area methane sources other than aerobic meth- of the páramo ecosystem, we used the ane emissions from plants may exist and National Oceanic and Atmospheric Adminis- that they may help to explain the high tration (NOAA) National Geophysical Data methane concentrations observed in the Center’s (NGDC) ETOPO2v2 2' gridded to- SCIAMACHY data. Our results warn us pography dataset (www.ngdc.noaa.gov). against making hasty conclusions based on We used elevation (as a proxy for tem- incomplete knowledge of ecosystems. ■ perature) and precipitation to identify trop- [email protected] ical alpine wetland areas: all grid cells be- tween 3000 and 4500 m above sea level 1. Keppler F, Hamilton JTG, Brass M, and Roeckmann with annual precipitation >600 mm were T 2006. Methane emissions from terrestrial plants considered potential páramo area. The re- under aerobic conditions. Nature 439, 187–191. sulting map shown as insert in Fig. 1 was 2. Vigano I, van Weelden H, Holzinger R, Keppler F, used as a mask to run LPJ-WHyMe (de- and Roeckmann T 2008. Effect of UV radiation and scribed further below). temperature on the emission of methane from However, when using only altitude and plant biomass and structural components. Bio- precipitation as boundary conditions for the geosciences 5, 937–947. occurrence of the páramo, the resulting area 3. IPCC 2007: Climate Change 2007: The physical sci- was at least four times too large compared ence basis. Contribution of Working Group I to the to best estimates. We therefore applied a fur- Fourth Assessment Report of the Intergovernmen- ther mask based on the topographic index tal Panel on Climate Change. Solomon S, Qin D, Figure 2. Methane emissions from the páramo. (a measure of landscape steepness) to limit Manning M, Chen Z, Marquis M, Averyt KB, Tignor the páramo ecosystem to the less steep M, and Miller HL (Eds.). Cambridge University Press, parts of the area, which we assumed to be methane production: wet conditions provide United Kingdom. the wetter ones and therefore the more im- ideal conditions for methane production, 4. Houweling S, Rockmann T, Aben I, Keppler F, Krol portant ones in terms of methane emissions. and high net primary production provides M, Meirink JF, Dlugokencky EJ, and Frankenberg C 2006. Atmospheric constraints on global emissions Based on field observations in Ecuador and organic substrate that can be utilised by the of methane from plants. Geophysical Research Colombia, we classified areas with a topo- methane-producing microbes. Letters 33, L15821. graphic index of 9 or 10 as wetlands. This Soil temperature did not exhibit a clear 5. Frankenberg C, Meirink JF, Bergamaschi P, Goede way, we obtained a páramo area of 56750 north-south gradient. Annual methane APH, Heimann M, Korner S, Platt U, van Weele M, and 32320 km2, respectively, close to current -2 -1 emission rates exceeded 250 g (CH4) m yr and Wagner T 2006. Satellite chartography of at- estimates. in the páramo, about 50% higher than in the mospheric methane from SCIAMACHY on board LPJ-WHyMe is a dynamic global vegeta- northern high-latitude peatlands [8]. The rea- ENVISAT: Analysis of the years 2003 and 2004. tion model that simulates wetland hydrol- son was the constant temperature through- Journal of Geophysical Research 111, D07303. ogy, peatland plant functional types and out the year. 6. Bergamaschi P, Frankenberg C, Meirink JF, Krol M, methane emissions [8]. To run LPJ-WHyMe, We estimated that total annual methane Dentener F, Wagner T, Platt U, Kaplan JO, Korner S, we used air temperature and precipitation emissions from the Andean páramo lie Heimann M, Dlugokencky EJ, and Goede A 2007. climatology data (1950–2000) at 2' resolu- between 1.4 and 2.4 Tg, depending on the Satellite chartography of atmospheric methane tion that were derived from the WorldClim topographic index used to limit the páramo from SCIAMACHY on board ENVISAT: 2. Evaluation (www.worldclim.org) project. Cloud data area. Previously, methane emissions from the based on inverse model simulations. Journal of were taken from the CRU CL1.0 (Climate whole of South America were estimated to Geophysical Research 112, D02304. Research Unit Climatology data, University of be between 29.3 Tg yr-1 [9] and 38 – 44.2 Tg 7. Buytaert W, Celleri R, De Bievre B, Cisneros F, Wyseure G, Deckers J, and Hofstede R 2006. East Anglia) data set and interpolated to 2' yr-1 [6]. Both studies excluded areas above Human impact on the hydrology of the Andean resolution. 500 m above sea level in their methane páramos. Earth-Science Reviews 79, 53–72. emission estimates. LPJ-WHyMe showed a clear north-south 8. Wania R 2007. Modelling northern peatland land gradient in methane emissions (Fig. 2), with According to [6], matching model results surface processes, vegetation dynamics and meth- higher annual emission rates in the northern to SCIAMACHY observations in the north- ane emissions. PhD thesis, University of Bristol, UK. areas of Colombia and Ecuador and lower western part of South America was difficult, 9. Melack JM, Hess LL, Gastil M, Forsberg BR, emission rates in Peru. This pattern was the especially from October to December. This is Hamilton SK, Lima IBT, and Novo EMLM 2004. result of either wetter conditions and/or exactly the region where large areas of wet Regionalization of methane emissions in the higher net primary production in the north. páramo occur. Our first estimates of meth- Amazon Basin with microwave remote sensing. Both of these conditions enhance anaerobic ane emissions from the páramo indicated Global Change Biology 10, 530–544.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 59 Figure 1. Scheme of the methodology proposed to retrieve actual daily evapotranspiration (latent heat flux LE) at a regional scale, integrating remote sens- ing data and ground meteorological information. Description of all the variables and parameters can be found in [4].

Juan M. Sánchez, Vicente Caselles, Enric Valor and César Coll Department of Earth Physics and Thermodynamics, University of Valencia, Valencia, Spain Monitoring the surface energy balance using remote sensing

Anomalies in the global energy balance play teorological, climatological, and hydrological scale. Because of its particular significance in an important role in the global climate studies. Traditional local models to estimate the water cycle, we focussed on the retrieval change. A good knowledge of the surface- LE cannot be applied at regional nor global of daily LE. atmosphere interactions, and particularly of scales as required in climate assessment. The model is based on a two-source the water and energy cycles, is essential to Remote sensing techniques allow us to patch representation of the soil-canopy-at- help the scientific community in this regard. obtain information on surface variables with mosphere system [2]. The feasibility of the Also, the different terms of the surface en- a global coverage. This includes regions of model at a local scale has been explored ergy balance may be used to evaluate land- special interest such as, for example, boreal using data collected over different ecosys- surface models embedded within climate forests which occupy about 11% of the total tems. In this work we focus on two of them: models. terrestrial surface, representing an important a maize (corn) crop in Maryland, USA, and a The latent heat flux (LE), or evapotrans- contribution to global energy balance [1]. boreal forest in Finland. piration (evaporation from surfaces and tran- In this study, we developed a physical In the corn crop, the energy balance (net spiration by plants), is the least understood model for estimating local surface energy radiation ≈ soil heat flux + LE + sensible heat process of both the water and energy cycles. fluxes that can be operationally used to- flux) was governed by LE [2] whereas in the However, its determination is crucial for me- gether with satellite images at a regional boreal forest LE was less significant [3].

60 iLEAPS Newsletter Issue No. 7 ◆ June 2009 abc

0 1.6 3.2 4.8 6.4 8

Figure 2. Actual daily evapotranspiration i.e. daily eas, generally produced the highest LEd. On the -1 latent heat flux, LEd (mm day ) over maps of the other hand, the lowest LEd values were usually Basilicata region (100x100 km2 approximately) in found in sparsely vegetated areas, arable lands, and southern Italy for three Landsat scenes correspond- pastures. Because of the phenological stage of the ing to different dates: (a) 26 Sep 1999, (b) 14 Jun vegetation, overall the highest LEd was observed in 2002, (c) 25 May 2004. Coniferous and broad-leaf May 2004 and the lowest one in September 1999. forests, together with fruit trees and agriculture ar- Figure reproduced from [4].

Comparison of the results with ground It should be noted that the spatial reso- 1. Baldocchi DD, Vogel CA, and Hall B 1997. Seasonal measurements indicated errors between lution of some satellite sensors, especially variation of energy and water vapour exchange ±15 and ±60 W m-2 for the retrieval of net those with a daily overpass frequency, may rates above and below a boreal jack pine forest radiation, soil heat flux, and sensible and la- be too coarse to discriminate between dif- canopy. Journal of Geophysical Research 102 tent heat fluxes at both sites [2,3]. According ferent land uses, depending on the field pat- (D24), 28939–28951. to a sensitivity analysis of typical uncertain- tern size. In order to improve the applicabil- 2. Sánchez JM, Kustas WP, Caselles V, and Anderson ties in the required input parameters at a ity of the surface energy model in these MC 2008. Modelling surface energy fluxes over regional scale, the model was most sensitive cases, some procedures can be applied to maize using a two-source patch model and radio- to surface and air temperatures. estimate subpixel energy fluxes [6]. ■ metric soil and canopy temperature observations. Remote Sensing of Environment 112, 1130–1143. For regional scale, we developed a de- tailed methodology to apply the model to 3. Sánchez JM, Caselles V, Niclòs R, Coll C, and Kustas WP 2009. Estimating energy balance fluxes above Landsat satellite imagery in [4]. The different a boreal forest from radiometric temperature ob- surface cropland features were characterised servations. Agricultural and Forest Meteorology according to the CORINE Land Cover [5] 149, 1037–1049. maps, and the required meteorological vari- 4. Sánchez JM, Scavone G, Caselles V, Valor E, ables were obtained by interpolating the Copertino VA, and Telesca V 2008. Monitoring daily data of a network of agro-meteorological evapotranspiration at a regional scale from stations distributed within the region of in- Landsat-TM and ETM+ data: application to the terest (Fig. 1). Basilicata region. Journal of Hydrology 351, 58–70. We applied the methodology to three 5. Bossard M, Feranec J, and Otahel J 2000. CORINE different Landsat scenes corresponding to land cover technical guide - Addendum 2000. different dates covering the whole Basilicata Technical report No 40, European Environment region (southern Italy). As a result, we ob- Agency, Copenhagen, pp 105. tained maps of the different surface fluxes 6. Anderson MC, Norman JM, Mecikalski JR, Torn RD, including daily LE (Fig. 2). Comparison of the Kustas WP, and Basara JB 2004. A multi-scale re- results with ground measurements revealed mote sensing model for disaggregating regional that the accuracy of the model was close to fluxes to micrometeorological scales. Journal of ±30 W m-2. [email protected] Hydrometeorology 5, 343–363.

iLEAPS Newsletter Issue No. 7 ◆ June 2009 61 Working group chairs: Juliette Lathière, Dominick Spracklen Working Group report on Land-atmosphere feedbacks

The aim of this working group was to find should be conducted both in the laboratory nitrogen-phosphorus cycles in plants and answers to the following two questions: and in the field to achieve a better under- soil. For example, determining the magni- ● What are the important potential standing of the oxidation processes. The tude of nitrogen (N) fixation in different feedbacks between land and atmos- hydrological cycle also has an important ecosystems and the variety and functional phere that have not already been effect on aerosol dynamics via cloud forma- groups of organisms participating in the N studied? tion, precipitation, and indirectly through fixation is crucial for understanding carbon- ● What type of experiments need to be plant productivity and, therefore, VOC nitrogen interactions. Plant roots influence designed to illustrate and quantify emissions. the physical, chemical, and biological them? By scattering, aerosols can reduce the conditions of the soil. The biogeochemical amount of photosynthetically active radia- reactions induced by micro-organisms affect The discussion in the group was lively tion reaching the Earth’s surface and change the availability of nutrients to plants and and produced multiple candidates for the relationship of direct and diffuse light. microbes. feedbacks that have so far not been This effect is not considered in current However, because of insufficient under- addressed in climate modelling. climate models and it could dramatically standing of soil-plant interactions, models Here, we summarise some of the main change the simulated biogenic emissions, are still incapable of fully describing the points. both directly, by modifying the radiation carbon, nitrogen, and phosphorus cycling in The role of micro-organisms in atmos- available for the synthesis of biogenic VOCs, the soil. Reactive nitrogen has a key role in pheric chemistry such as aerosol formation and indirectly, by its effect on plant produc- the atmosphere and soil because it controls and photochemical processes came up early tivity. nitrogen availability and hence, for instance, on in the conversation. Bioprecipitation is The importance of the chemical compo- carbon sequestration of forest ecosystems. related to bacteria that participate to super- sition of the atmosphere and soil in the The use and development of remote cold cloud formation. Evidence of bio- development of ecosystems was pointed sensing for both wet and dry nitrogen depo- precipitation has been obtained at several out in the conversation. There are already sition studies is of great importance in order locations in the USA and also in Brazil. studies about ozone but we need a better to understand larger-scale interactions of However, although the group felt this understanding about the influence of acid nitrogen and ecosystem functioning. phenomenon is important for understand- deposition (wet and dry) and other pollut- Land-use change is a crucial factor that ing cloud formation, the number of micro- ants and particles on ecosystems and the has many potential effects in terms of trace organisms with the necessary properties is carbon cycle. A good example is China gas emissions, albedo, evapotranspiration, small. Most of these micro-organisms are ac- with its industrial development. Important energy, and atmospheric chemistry. Yet tive only in cool temperatures and will substances in this regard are, for example, another aspect are the feedbacks among probably become less active in the warming sulphuric acid, dissolved organic carbon dust, ice nuclei, and surface meteorology. So climate. (DOC), and total dissolved nitrogen (TDN) far, these processes have only been taken Interactions between biogenic trace gas which are currently missing in climate stud- into account on large scale. emissions and atmospheric chemistry have ies. The human influence on these com- However, they also influence ecosystems an influence on aerosol dynamics and on pounds can be great. Remote sensing can on a local level (fertilisation effect, change in ozone formation. Volatile organic com- be used for monitoring sulphur dioxide the availability of nutrients for plants). This

pounds (VOC) such as isoprene and (SO2). could be studied mainly in the laboratory: monoterpenes are emitted from vegetation The influence of global warming on aerosols in different solutions can be used to and oxidised in the atmosphere by ozone wetlands is an important consideration. The study how much is soluble (solubility of iron - for example) at different pH. Extending (O3), the hydroxyl radical (OH ) and the melting of permafrost can become a new experiments like these to the field would be nitrate radical (NO3). The oxidised products source of wetlands in the future. One are less volatile and can condense on small important feedback is the coupling of difficult. aerosol particles and grow them to climati- methanotrophy (methane consumption) Finally, the group mentioned that cally relevant sizes (> 80–100 nm in diam- and methanogenesis (methane emission) in wildfires are not very well detailed in models eter) where the particles can act as cloud wetland ecosystems and forests in response so far (height of injection). We need better condensation nuclei (CCN) and, eventually, to increasing loads of reactive nitrogen (all understanding of the influence of wildfires form clouds. Aerosol particles cool the atmospheric nitrogen except N2) species on aerosol formation, clouds, the radiative/ climate also by scattering incoming sunlight from the atmosphere. For example, more energy budget, and convection. Satellite back to space. research is necessary on gaseous losses and observations are a good way to detect ■ New VOC are constantly being discov- uptake of N such as nitrous oxide (N20) wildfires. ered, and more information on their role in consumption in ecosystems and on N20 the formation of climate-cooling aerosol export from rivers. particles is necessary for better modelling of We need more information about the [email protected] the Earth’s radiative balance. Experiments human influence on the linked carbon- [email protected]

62 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Deforested landscape in Rondonia, Brazil. Photo: Andi Andreae.

Tom Osborne1 and Katherine Corbin2 1. NCAS (National Centre for Atmospheric Science)-Climate, University of Reading, Reading, UK 2. Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marine and Atmospheric Research, Aspendale, Australia Working Group report on Land use

We were tasked with two objectives: firstly, It was noted that several modelling groups An alternative view was that progress to assess how we can properly account for throughout the world are currently devel- was slower because more validation was be- land use in climate models; and secondly, to oping global cropland parameterisations. ing conducted for croplands than was done determine what datasets are required for However, compared to the development of during the development of natural vegeta- this that do not currently exist. Several land- DGVMs, progress is slow, and the group tion models, possibly because of the avail- use processes are currently missing from the discussion focussed on the possible reasons. ability of datasets on crop yield. This led to land surface/vegetation component of One possible explanation is an overall the question: is it appropriate to validate climate models that should be included. lack of a common objective. Crop para- crop yield simulations when we are more The two main points of discussion were meterisations have been included in some interested in simulating carbon and physical ● including land-use transitions; land-surface models to improve the simula- fluxes correctly? This question is even more ● representing croplands. tion of seasonal carbon fluxes, in others to valid considering that many non-climatic better represent biophysical feedbacks to factors can influence crop yield, such as vari- Land-use transitions are an important the atmosphere, and in others to provide ability in inputs (e.g. fertilisers) and choice of consideration as they determine whether estimates of crop yield. So far, these various crop variety. However, it was also noted forest within a grid box is primary (old- objectives have been met using different that these factors affect the growth of the growth) or secondary (recovering from pre- approaches. crop and therefore influence the biogeo- vious human land-use activities). Forests in Related to the objectives, another point physical feedbacks we are interested in. these two land types have different growth raised was that crop parameterisations were A wish list of datasets for representing rates that lead to large differences in simu- perhaps too complex for inclusion in DGVMs land use in climate models included details lated carbon budgets and in physical given the small proportional area of crop- on crop management (sowing dates, ferti- feedbacks between the land and the atmos- lands and the extent to which current crop liser inputs, tillage practices), irrigation (not phere. growth parameterisations differ from exist- just area, but volume applied, efficiencies, It was noted that all dynamic vegetation ing DGVM growth models. Additionally, the sources), and fire suppression. It was noted models contributing to the 5th assessment large number of dynamic crop models, that integrated assessment models (IAM, report of the Intergovernmental Panel on many of which are crop-specific, was specu- used to produce future world scenarios for Climate Change (IPCC) would need to in- lated to have hindered progress towards a IPCC) should provide details on crop area, clude land-use transitions in the simulations. single generic parameterisation for all crops fertiliser use and irrigation volume; however, Therefore, discussion and debate arose also globally. it was thought unlikely that this information ■ on the issue of how current Dynamic Global These factors, combined with the com- would be crop-specific. Vegetation Models (DGVM) would represent puting costs of DGVMs, suggest that it may transitions. be appropriate to use the existing para- The second major point of discussion meterisations of natural vegetation as much [email protected] concerned representing croplands in DGVMs. as possible. [email protected]

iLEAPS Newsletter Issue No. 7 ◆ June 2009 63 Forrest M. Hoffman1 and Martial Mancip2 1. Computational Earth Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA 2. Institut Pierre Simon Laplace (IPSL), Paris, France Working Group report on Terrestrial biosphere model evaluation

About 15 of the iLEAPS-Marie Curie work- metrics should be based on comparison istics. The group felt it was important to de- shop attendees from Africa, Europe, and the against measurements of processes such as velop metrics that would consider model United States participated in a lively discus- photosynthesis and phenology instead of, performance across all relevant scales. sion focussed on the evaluation of terrestrial for instance, global CO2 fluxes with multiple Recommendations from the group dis- models typically run within general circula- error sources. cussion were to tion models (GCMs). The task was to recom- Moreover, because there are many ways ● write a review paper on the current state mend the best methods for thoroughly to get “the right answer for the wrong rea- of best available data sets for model evaluating scientific model performance. Ini- son,” a comprehensive evaluation of model evaluation; tially, group members identified a variety of processes must include comparisons of a ● encourage the development and shar- difficulties that impede such evaluations, in- wide array of model variables. Also discussed ing of “best” data sets by the community; cluding was the importance of combining many ● better document model processes to im- 1) the mismatch between the spatial and data sets of similar observations for compari- prove understanding of evaluation re- temporal scales of measurements and son with model results and of processing sults; models, data sets in a consistent manner. ● encourage closer collaboration between 2) limits of model assumptions, and The group constructed lists of forcing modelling groups; 3) the dangers of tuning models for specific and evaluation data sets, and group mem- ● encourage closer collaboration between geographic regions / forcing (input) data bers described many of the strengths and measurement and modelling communi- / execution modes (offline or coupled). weaknesses of these data. Commonly used ties; and meteorological forcing data sets include The group formulated a list of elements ● establish a mailing list to continue the NCEP/NCAR reanalysis (National Center for important for organised and methodical model evaluation discussion and invite Environmental Prediction/National Center for model-data comparisons. These elements are others in the research community to Atmospheric Research, 1948–2004), CRU (Cli- ● an experimental protocol designed to participate. Interested researchers can mate Research Unit of the University of East elucidate model performance under subscribe to this mailing list at: Anglia, 1850–present), NCC (NCEP Corrected past, present, and future climates across www.climatemodeling.org/mailman/ with CRU, 1949–2000), and ERA-interim (Eu- all relevant space and time scales; listinfo/land-eval ropean Centre for Medium-Range Weather ● metadata standards to simplify manipu- Forecasts reanalysis, 1989–2007). In conclusion, the group reiterated the lation and analysis of model results, in- Sources of observational data identified importance of confronting models with ob- cluding standardising biome and carbon were the FLUXNET and AmeriFlux sites for servations and that this should be done pool types; surface energy and carbon flux measure- early and often. Models must be tested and ● evaluation metrics based on comparison ments, Free-Air Carbon Dioxide Enrichment evaluated in offline, partially coupled, and of model results with best available (FACE) sites for vegetation response to in- fully coupled modes over short and long satellite- and ground-based observa- time scales and over small and large spatial creases in CO2, river gauge and GRACE (Grav- tional data sets; ity Recovery and Climate Experiment) satel- scales. Experiments should include historical, ● standardised diagnostics supporting all lite observations for hydrological measure- present-day, and future time periods. metric comparisons; ments, NOAA (National Oceanic and Atmos- Finally, everyone agreed that these are ● a scoring methodology based on a com- pheric Administration) flasks for records of challenging and time-consuming tasks, but munity-developed weighting of model that we should work together to take ad- the CO2 seasonal cycle, National Aeronautics performance on metrics, taking into ac- and Space Administration (NASA) MODIS vantage of one another’s efforts and exper- count importance and data uncertainty; (Moderate Resolution Imaging Spectro- tise. An international model evaluation effort and radiometer) and other satellite products for focusing on models to be used in the ● open distribution of model results, sup- phenology and carbon fluxes, and tree rings upcoming IPCC (Intergovernmental Panel on porting related research by the wider and other proxies for climate and distur- Climate Change) Fifth Assessment Report community. bance. could be the first step in building such a ■ The group thought it important that In addition, an effort was made to char- wide collaboration. models should be evaluated based, as much acterise the spatial (small to large) and tem- as possible, on our understanding of indi- poral (short to long) scales of a variety of [email protected] vidual processes. Therefore, performance individual processes and variables/character- [email protected]

64 iLEAPS Newsletter Issue No. 7 ◆ June 2009 iLEAPS Newsletter Issue No. 7 ◆ June 2009 65 Yellow River in tropical Darwin. Photo: Tanja Suni. Marjut Nyman iLEAPS International Project Office, University of Helsinki, Helsinki, Finland Workshop report: 12–17 January 2009, Khon Kaen, Thailand NASA-LCLUC meeting on land-cover and land-use change in Monsoon Asia

More than a hundred participants gathered the spiciest food in the country. The close nomic changes. The economy of China has in Khon Kaen, Thailand, for a workshop to connection between land-use practices grown significantly during the last thirty transfer knowledge, to strengthen coopera- and the atmosphere was clearly demon- years. Economic growth, urbanisation, diet tion, and to find regional priorities in land- strated by the yellow haze above the area. structure changes, and population growth cover and land-use change (LCLUC) research The haze is caused by the smog rising from affect land-use practices in several ways. in the South-East Asia region. biomass burning in the surrounding sugar Population growth causes urban expansion This NASA-LCLUC (National Aeronautics cane fields. and deforestation. and Space Administration - Land-Cover and The meeting was divided into keynote More than two-thirds of the world’s Land-Use Change) Science Team Joint Meet- lectures, thematic presentations, program- megacities are located in developing coun- ing was hosted by Mekong Institute and matic presentations, working group discus- tries. In the next 20 years, the most intensive included sions, and poster sessions. We had a possi- growth rate and mega-urban development ❏ MAIRS (Monsoon Asia Integrated bility to visit the Khoen Kaen University and processes are predicted to take place in East Regional Study, www.mairs-essp.org), the Mekong Institute. Asia, South Asia, and Africa. Indeed, mega- cities and their effects on the environment ❏ GOFC/GOLD (Global Observation of A one-day field trip was organised to are among the most important research Forest and Land Cover Dynamics, the village of Kham Muang in the Khao questions for SEA. www.gofc-gold.uni-jena.de), and Suan Kwan district. There we had an oppor- tunity to explore how the traditional land- Other questions are, for example, the in- ❏ SEA START (South-East Asia SysTem for use system is coping under economic de- crease in the cultivation of commodity crops, Analysis, Research and Training, velopment pressures and climate change. such as rubber and palm, at the expense of www.start.or.th) programmes. The field trip was led by Dr. Patma Vityakon food crop production. Deforestation is a seri- Most of the participants came from from Khon Kaen University. ous issue that is linked to carbon budgets as Thailand, USA, and China. Other countries Additionally, a one-day practical training well. The extensive changes in land use and represented were Cambodia, Indonesia, session about LCLUC and climate change land cover affect the atmosphere and can Vietnam, Laos, Malaysia, Myanmar, the took place and offered a review on geo- have an effect on the regional climate. The Philippines, South Korea, Switzerland, spatial technologies, methods, and appli- need to involve socio-economic compo- Canada, India, Japan, and Finland. cations. nents in climate modelling was stressed in Khon Kaen is Thailand’s fourth largest The theme of the meeting is highly im- the meeting outcome. city with 200 000 inhabitants; it is located in portant for the South-East Asia (SEA) region The meeting also encouraged the re- the North-East province of Isaan which has which is going through many socio-eco- gional actors to share information and to

66 iLEAPS Newsletter Issue No. 7 ◆ June 2009 Figure 1. Cropland distribution in monsoon Asia in land-use data based on fine-scale remotely sensed most of South Asia. Maps published by courtesy of 1900 and 2000 represented as percentage within data and historical archives [3]. From 1900 to 2000, Dr. Hanqin Tian and the Ecosystem Dynamics and grid cell. These data sets were generated from croplands increased considerably in the north-east- Global Ecology Laboratory at Auburn University. HYDE 3 [2] and China’s reconstructed historical ern region of East Asia, in South-East Asia, and in actively network to find synergies and share resources in the LCLUC and climate change research which will eventually lead to prob- lem solving. The material and the presentations for this meeting can be found at: www.lcluc.hq.nasa.gov An extended description of the meeting ■ ? can be found in [1]. [email protected] In the next issue 1. O’Neal K, Gutman G, and Justice C 2009. Emerging on Permafrost and the Arctic—for example: science themes from the LCLUC Science Team meeting on Land-Cover/Land-Use Change (LCLUC) Anja Engel, Eva-Maria Nöthig Processes in the Monsoon Asia region. Earth Observer 21(2), 22–24. Future carbon cycling in the Arctic Ocean http://eospso.gsfc.nasa.gov/eos_homepage/ John E. Walsh for_scientists/earth_observer.php Recent and future Arctic regional climate variations 2. Goldewijk KK, Van Drecht G, and Bouwman AF 2007. Mapping contemporary global cropland and Vladimir Kattsov, Kathy Hibbard, Annette Rinke, grassland distributions on a 5 x 5 minute resolu- Vladimir Romanovsky, and Diana Verseghy tion. Journal of Land Use Science 2(3), 167–190. Terrestrial permafrost carbon in the changing climate 3. Liu M and Tian H 2009. China’s land-cover and land-use change from 1700 to 2005: estimations Guest Editor: from high-resolution satellite data and historical Professor Torben R. Christensen archives. Global Biogeochemical Cycles (submit- GeoBiosphere Science Centre, Lund University, Sweden ted).

iLEAPS Newsletter Issue No. 7 ◆ June 2009 67 Figure 1. Two moderately sized cumulus clouds in the western Amazon separated by 100 km provid- ing a striking example of aerosol effects on precipi- tation. Left: raining cloud in pristine air; right: visible smoke entering cloud and suppressing rainfall.. Anni Reissell iLEAPS International Project Office, University of Helsinki, Finland Workshop report: 6–8 April 2009, International Space Science Institute, Bern, Switzerland ACPC Steering Committee/ ISSI Team meeting

The interactions between aerosols, clouds The ACPC Steering Committee (SC) is ❏ initiate and plan focussed, coordinated and precipitation in the climate system are also an International Space Science Institute observational and modelling campaigns the largest uncertainties in the estimation of (ISSI) Team (www.issibern.ch). The SC to study the aerosol-cloud-precipitation anthropogenic climate forcing and climate comprises representatives from the three interactions. sensitivity. international research organisations iLEAPS In the third and last ISSI Team meeting, Recent developments in process under- (3), IGAC (3), and GEWEX (4). The members the ACPC SC finalised the SP&IS for external standing, modelling, and observational capa- are Meinrat O. Andreae (co-chair), Bjorn review, to be published before the iLEAPS bilities make it now possible to address Stevens (co-chair), Graham Feingold, Sandro and GEWEX Parallel Science Conferences in long-standing and fundamental questions in Fuzzi, Markku Kulmala, William K. Lau, Ulrike Melbourne, Australia, 24–28 August 2009. Lohmann, Daniel Rosenfeld, and Pier this field. The Aerosols, Clouds, Precipitation, The SP&IS outlines ACPC’s scientific ap- Siebesma. Climate (ACPC) program has been estab- proach which is based on the selection of a lished to facilitate and enable international Three ISSI Team/ACPC Steering Commit- number of precipitating cloud regimes. and interdisciplinary research in this field. tee meetings took place in Bern: 28–30 These regimes represent key environments ACPC was jointly initiated by the IGBP January 2008, 7–9 October 2008, and 6–8 for cloud formation and precipitation with (International Geosphere-Biosphere Pro- April 2009. The aim of the meetings was to: strong indication of aerosol-cloud-precipita- gramme) core projects iLEAPS, IGAC (Inter- ❏ finalise and publish the workshop report tion interactions. The regimes include some national Global Atmospheric Chemistry from the Boulder iLEAPS-IGAC-GEWEX of the major convective and precipitating project), and the WCRP (World Climate Re- ACPC Specialist Workshop, 8–10 October environments such as the monsoon systems, search Programme) core project GEWEX 2007 [1]; organised deep convective systems over (Global Energy and Water Cycle Experiment). land, tropical cyclones, and shallow and deep ❏ The goal of the ACPC research program is to write a peer-reviewed science article [2]; marine cumulus convection. Other regimes obtain a quantitative understanding of the ❏ outline the program’s scientific aims, im- have been selected because they are suit- interactions between the aerosol, clouds and plementation strategy, timeline, and or- able for investigation of key processes, e.g. precipitation, and their role in the climate ganisation as the ACPC Science Plan and orographic clouds, diurnally variable convec- system. Implementation Strategy (SP&IS) [3]; tion over land, and mixed-phase clouds,

68 iLEAPS Newsletter Issue No. 7 ◆ June 2009 including those that produce lightning and hail. The coordinated interdisciplinary ACPC program strategy includes the following ele- Issue 6 errata ments: The iLEAPS Newsletter production team apologises for the mistakes! 1. a focus on regimes with strong indica- tion of aerosol-cloud-precipitation inter- actions; The correct author list for the Workshop re- port Biogenic secondary organic aerosols: Ob- 2. an emphasis on statistical characterisa- servations to global modelling, 1-4 July 2007, tion of aerosol-cloud-precipitation inter- Hyytiälä, Finland (p. 41-42), is as follows: actions; 3. the development of approaches that lev- Tatu Anttila, Finnish Meteorological Institute, erage past and ongoing activities; Finland; Jaana Bäck, University of Helsinki, 4. thorough integration of modelling and Finland; Kelley Barsanti, University Center for observational activities; Atmospheric Research, USA; Merete Bilde, 5. a hierarchical approach to both model- ling and data collection/analysis; University of Copenhagen, Denmark; 6. continued development of measure- Michael Boy, University of Helsinki, Finland; ment techniques. Ann Marie Carlton, Environmental Protec- tion Agency, USA; Annica Ekman, Stockholm The first ACPC field experiments will start in Barbados and India in 2010. The program University, Sweden; Juliane Fry, Reed College, essentially also includes capacity building, USA; Marianne Glasius, University of Aarhus, knowledge transfer and training, and so, for Denmark; Gannet Hallar, Storm Peak Labora- example, a winter school in the Alps is The correct author list for the Workshop re- tory, USA; Colette Heald, Colorado State Uni- ■ planned for 2011. port On the relevance of surface and bound- versity, USA; Christopher Hoyle, University of [email protected] ary layer processes for the exchanges of reac- Oslo, Norway; Kara Huff Hartz, Southern tive and greenhouse gases, 9-12 October 2007, Illinois University, Carbondale, USA; Hannele Wageningen, the Netherlands (p. 34–35) is as Korhonen, University of Kuopio, Finland; follows: ACPC web page: Tuukka Petäjä, National Center for Atmos- www.ileaps.org/acpc/ Laurens Ganzeveld, Department of Environ- pheric Research, USA; Markus Petters, Colo- ACPC mailing list: mental Sciences, Earth System Science, rado State University, USA; Janne Rinne, [email protected] Wageningen University and Research Cen- University of Helsinki, Finland; Thomas tre (WUR), Netherlands & Max Planck Insti- Rosenoern, Harvard University, USA; Guy 1. Stevens B, ACPC Planning Team, and participants tute for Chemistry, Germany, Jordi Vilà- Schurgers, Lund University, Sweden; Allison of ACPC Workshop 2008. Aerosols, Clouds, Precipi- Guerau de Arellano, Department of Environ- Steiner, University of Michigan, USA; Amy tation, Climate (ACPC): Outline for a new joint mental Sciences, Meteorology and Air Qual- Sullivan, Colorado State University, USA; IGBP/WCRP initiative. iLEAPS Newsletter 5, 10–15. ity, WUR, Wageningen, Netherlands, and Cor Birgitta Svenningsson, Lund University, Swe- 2. Rosenfeld D, Lohmann U, Raga GB, O’Dowd CD, Jacobs, Department of Environmental Sci- den; Timothy Van Reken, Washington State Kulmala M, Fuzzi S, Reissell A, and Andreae MO 2008. Flood or drought: How do aerosols affect ences, WUR, Wageningen, Netherlands. University, USA; Christine Wiedinmyer, precipitation? Science 321, 1309–1313. National Center for Atmospheric Research, 3. Andreae MO, Stevens B, Feingold G, Fuzzi S, USA; David Worton, University of California Kulmala M, Lau WK, Lohmann U, Rosenfeld D, at Berkeley, USA; Alessandro Zardini, Univer- Siebesma P, Reissell A, O’Dowd C, Ackerman T, and sity of Copenhagen, Denmark. Raga G 2009. Aerosols, Clouds, Precipitation and Climate (ACPC) Science Plan & Implementation Strategy (in external review).

iLEAPS Newsletter Issue No. 7 ◆ June 2009 69 AMMA - African Monsoon Multidisciplinary Analyses Adaptation to climate change in West Africa. The AMMA WP 3.2 perspective

AMMA aims to improve our ability to fore- cast weather and climate in the West African region as well as our understanding of the effects and adaptive responses of people and the environment. While the complexity and unpredictability of the West African monsoon system provide an intriguing chal- lenge for science, they are potentially devas- tating for the many West African people affected by it. The objective of the AMMA Work Pack- age 3.2 (Human processes, adaptation and evironmental interactions) is to understand and map adaptation strategies and to attempt to determine the importance of Hombori village in Mali. Photo: Françoise Guichard climate factors for local land-use and liveli- and Laurent Kergoat–AMMA. CNRS copyright. hood strategies, decision-making and social relations. Researchers from Senegal, Mali, and a range of other effects to climate adaptation in this region. The field data are Burkina Faso, Niger, Nigeria, and Denmark factors, especially to wind. However, when already organised in a database, and WP 3.2 developed a common questionnaire and in- the questions about changing land use and will try to find funding to keep and develop terview guide that was implemented at 16 problematic livelihood are posed in other it to enable better tracking of adaptive field sites in 5 countries (1350 question- than a climate context, the locals assign options through the years. ■ naires). The sites were selected to represent economic, political, and social rather than the region and were located along north- climatic factors as the main drivers. south and east-west transects, and included We conclude, therefore, that the commu- both agricultural and pastoral areas. More- nities studied have a high awareness of over, in-depth studies took place in several climate issues but that climatic narratives are sites. likely to influence the responses when ques- The results of the WP 3.2 showed that tions refer to climate. Change in land-use farmers in the Sahel have always been sub- and livelihood strategies is driven by adapta- ject to climatic variability at intra-, inter-an- tion to a range of factors of which climate nual, and decadal time scales. While coping does not appear to be the most important. and adaptation strategies have traditionally In the near future, WP 3.2 plans to pub- included crop diversification, mobility, liveli- lish a special issue in a peer-reviewed journal

Highlights hood diversification, and migration, attri- on adaptation to climate change in West ✶ buting the changes directly to climate is Africa. Several papers are foreseen on various www.amma-international.org challenging. Local people are aware of topics from perception of climate change climate variability and identify wind and to pastoralist livelihoods, forest resources, www.ileaps.org occasional excess rainfall as the most gender and social livelihoods, migration, Science and Projects /

Project destructive climate factors. They attribute agriculture, national adaptive policies, and Current Projects / ✶ poor health of livestock, reduced crop yields, conceptual modelling of the future of AMMA

70 iLEAPS Newsletter Issue No. 7 ◆ June 2009 GPWG/FIRE - The Global Palaeofire Working Group on the IGBP Cross-Project Initiative on Fire The influence of human activity and abrupt climate changes on fire frequency

abrupt climate changes in North America, indeed at any time during the deglaciation focussing particularly on the Younger Dryas [2]. This finding casts doubt on the hypoth- interval (12900 to 11700 yrs BP). According esis that a comet impact triggered massive to [2], the abrupt cooling associated with the catastrophic wildfires and caused the onset of the Younger Dryas led to large fires Younger Dryas. ■ in some regions, but a more widespread increase in fire activity occurred during the 1. Marlon J, Bartlein PJ, Carcaillet C, Gavin DG, rapid warming that marked the end of this Harrison SP, Higuera PE, Joos F, Power M, and cold interval. Prentice IC 2008. Climate and human influence on The rapid response of fire regimes to global biomass burning over the past two millenia. abrupt climate changes seems to be related Nature Geosciences, DOI: 10.1038/ngeo313. Sedimentary charcoal records are a valuable to climate-driven fuel availability: transitions 2. Marlon JR, Bartlein PJ, Walsh MK, Harrison SP, resource for documenting past changes in from warm to cold climates increase fuel Brown KJ, Edwards ME, Higuera PE, Power MJ, fire regimes. The Global Palaeofire Working loads because of vegetation dieback, Anderson RS, Briles C, Brunelle A, Carcaillet C, Group has created a database of nearly 800 whereas transitions from cold to warm Daniels M, Hu FS, Lavoie M, Long C, Minckley T, Richard PJH, Scott AC, Shafer DS, Tinner W, individual charcoal records worldwide. Conti- climate increase fuel loads because of Umbanhower CE Jr, and Whitlock C 2009. Wildfire nental- to global-scale analyses of these increases in productivity [2]. Despite some responses to abrupt climate change in North records are providing challenges to our increase in fire activity at the onset of the America. Proceedings of the National Academy current understanding of fire behaviour and Younger Dryas, no evidence was found for of Sciences (PNAS) 106, DOI/10.1073/pnas. the controls on fire regimes, as well as stimu- continent-wide wildfires at that time or 0808212106. lating a critical evaluation of methods to predict future changes in fire regimes. A GPWG analysis of over 400 records worldwide spanning the last two millennia [1] revealed a clear link between human activity and decreasing fire frequency. The first finding was that global fire activity declined in parallel with the global cooling trend between 1 AD and ca 1750 AD (Fig. 1), despite the rise in human population during this interval. The fire records showed centen- nial-scale variability similar to that shown by Figure 1. ➤ Global fire activity climate. A marked increase in fire occurred during the last two millennia. after 1750 AD but, surprisingly, the charcoal records showed a downturn in fire activity from the late 19th century through the 20th century [1]. This downturn, which was opposite to the simultaneous changes in climate, prob- ably reflected landscape fragmentation and the global expansion of intensive grazing ✶ and agriculture. Both of these processes Project decrease the frequency of fire because they reduce fuel load and connectivity and thus

limit the ability of fires to spread across the

➤ landscape. This inadvertent suppression of Figure 2. Fire activity and ✶ fire has occurred on most continents and temperature in North America Highlights around the Younger Dryas reflects the only unequivocal evidence of interval (12900 to 11700 yrs BP). human influence on global fire regimes during the past two millennia. A second GPWG study (Fig. 2) [2] addressed the response of fire regimes to www.bridge.bris.ac.uk/projects/QUEST_IGBP_Global_Palaeofire_WG

iLEAPS Newsletter Issue No. 7 ◆ June 2009 71 POLARCAT - POLar study using Aircraft, Remote sensing, surface measurements and models of Climate, chemistry, Aerosols, and Transport Intensive campaigns during the International Polar Year 2007–2008

arctic haze, anthropogenic pollution in gen- POLARCAT-GRACE eral, stratosphere-troposphere exchange, The main objective of POLARCAT-GRACE and sunrise photochemistry. The summer (Greenland Aerosol and Chemistry Experi- deployment was focused more on boreal ment) was to investigate the influence of forest fires, stratosphere-troposphere ex- emissions from boreal forest fires and change, and summertime photochemistry. anthropogenic sources on the chemical NOAA ICEALOT composition and particles in the tropo- sphere of the European sector of the Arctic. As part of POLARCAT, NOAA (National The Falcon performed 18 local flights from Oceanic and Atmospheric Administration) Kangerlussuaq, Greenland, covering the conducted a 6-week ICEALOT (International latitudes 58°–82°N. More than 40 pro- Chemistry Experiment in the Arctic LOwer nounced pollution plumes could be meas- At least thirty institutes from over ten na- Troposphere) research cruise in an ice-free ured at altitudes from 4–10 km originating tions contributed to the major airborne and region of the Arctic during March and April mainly from boreal forest fires and fossil fuel ship-based POLARCAT campaigns during of 2008. The study area included the Green- combustion sources in Canada, Siberia, and the International Polar Year (IPY) in March land Sea, the Norwegian Sea, and the eastern Asia. ■ 2007 – March 2009. It is too early for a Barents Sea. Scientific issues addressed in- balanced report on the scientific results but cluded springtime sources and transport of a few publications on the first results have pollutants to the Arctic, evolution of aerosols already appeared. A data analysis and inte- and gases into and within the Arctic, and gration workshop will be held in Durham, climate impacts of haze and ozone in the New Hampshire, USA, on 2–5 June 2009. Arctic. ASTAR 2007 NOAA ARCPAC ASTAR 2007 (Arctic Study of Tropospheric In March–April 2008, NOAA conducted the Aerosols, Clouds, and Radiation) was the first airborne field measurement ARCPAC (Aero- POLARCAT campaign conducted already in sol, Radiation, and Cloud Processes affecting spring 2007. An ASTAR journal special issue Arctic Climate) campaigns in Fairbanks, was recently opened for submission of pa- Alaska along with the NASA campaign ARCTAS. The aim was to improve under- Figure 1. Flight and cruise tracks of the various pers in Atmospheric Chemistry and Physics. POLARCAT campaigns during the International One of the highlights of the campaign were standing of Arctic climate processes driven Polar Year 2007–2008. layers with high concentrations of sulphur by short-lived forcing agents such as aero- dioxide and aerosols but with little oxidised sols. The measurements took place in the nitrogen or carbon monoxide found around Alaskan Arctic and were closely coordinated Svalbard. These findings are evidence of im- with remote sensing and in situ observa- 1. Warneke C, Bahreini R, Brioude J, Brock CA, de portant local sources of pollution (probably tions at ground sites in the vicinity of Barrow, Gouw JA, Fahey DW, Froyd KD, Holloway JS, industrial plumes from northern Russia) in Alaska. The first peer-reviewed publication Middlebrook A, Miller L, Montzka S, Murphy DM, the Arctic. resulting from this campaign has just ap- Peischl J, Ryerson TB, Schwarz JP, Spackman JR, and peared [1] and describes how fires burning Veres P 2009. Biomass burning in Siberia and NASA ARCTAS in agricultural areas in Asia and in the boreal Kazakhstan as an important source for haze over ARCTAS (Arctic Research of the Composition forest can have an extensive influence on the Alaskan Arctic in April 2008. Geophysical of the Troposphere from Aircraft and Satel- the measurements taken over and close to Research Letters 36, L02813. Alaska. Highlights lites) was conducted as two 1-month aircraft ✶ deployments, in March-April and June-July POLARCAT FRANCE 2008. It involved the NASA (National Aero- nautics and Space Administration) DC-8 air- The French ATR aircraft was based in Kiruna, For more details of the campaigns, please craft as its primary platform, with the P3-B Sweden, during spring 2008 and, together see the POLARCAT webpage:

Project and B-200 aircrafts as specialised secondary with the German Falcon, in Kangerlussuaq ✶ platforms. The spring deployment targeted (Greenland) during summer 2008. www.polarcat.no

72 iLEAPS Newsletter Issue No. 7 ◆ June 2009 VOCBAS – Volatile Organic Compounds in the Biosphere-Atmosphere System Drought breaks down the temperature dependence of isoprene emission

has recovered from stress and cannot be 1. Fortunati A, Barta C, Brilli F, Centritto M, Zimmer I, further stimulated by temperature. Schnitzler J-P, and Loreto F 2008. Isoprene emission The discovery of transient yet wide- is not temperature-dependent during and after spread decoupling of isoprene emission severe drought-stress: a physiological and bio- from temperature should lead to further chemical analysis. The Plant Journal 55, 687–697, refining of current algorithms and models of doi: 10.1111/j.1365-313X.2008.03538.x. isoprene emission, especially when applied to areas that are prone to recurrent drought events. As a result, the expected patterns of isoprene emission in the atmosphere in response to climate change may change considerably. ■ Isoprene, one of the most abundant bio- genic volatile organic compounds in the at- mosphere, is mainly emitted by deciduous trees in the world’s forests. Isoprene is an important precursor of ozone (O3) and also reacts with OH to produce aerosol particles. The dependence of isoprene emission on temperature has been reported in many published studies. It is the cornerstone of all algorithms modelling the emission of this important volatile compound from vegeta- tion to the atmosphere. However, a VOCBAS study by Fortunati et al. [1] revealed for the first time that a very common stressor, drought, may break this dependency and lead to unexpectedly high isoprene emis- sions. Drought is a recoverable stress to which most plants are transiently but recurrently exposed, and this work considered the ef- fects of such a globally important phenom- enon to the emission of isoprene. According to [1], the temperature dependency vanishes because sources of carbon alternative to photosynthesis are activated when drought

stress is severe. These alternative sources ✶ disappear rapidly when the stress is relieved, Project but they may transiently increase isoprene emission to levels higher than those ob- served before stress in leaves that recover

from drought. ✶

The temperature independence of iso- Highlights prene emission lasts at least two weeks after Figure 1. Exposure to severe drought stress breaks www.esf.org/activities the drought ends (Fig. 1). This is possibly be- the ubiquitous dependence of isoprene emission on temperature. This effect lasts 15 days after cause isoprene synthase activity (the bio- recovery from the stress. Photosynthesis (A) and chemical factor driving isoprene tempera- isoprene emission (B) in leaves maintained at 25 www.ileaps.org ture dependency) is maximal after the plant (blue lines) and 35°C (red lines). Science and Projects/Current Projects/VOCBAS

iLEAPS Newsletter Issue No. 7 ◆ June 2009 73 Meetings

Open seminar COST Action ES0804 Kick-Off Meeting, Third ACPC Steering Committee/ISSI by Prof. Bjorn Stevens (ACPC), COST Office, Team meeting, University of Helsinki, Helsinki, Finland, Brussels, Belgium, International Space Science Institute, 27 January 2009 17–18 February 2009 Bern, Switzerland, 6–8 April 2009

A new COST ESSEM (Earth System Science and Environmental Management) Action ES0804: Advancing the integrated monitoring of trace gas exchange between biosphere and atmosphere started in this Kick-Off Meeting by the election of Chair, Co-Chair, and Working group leaders: ● Co-Chairs: Prof Timo Vesala, Finland, Prof Almut Arneth, Sweden ● WG1: Analysis and synthesis of the current state of the flux monitoring sites, measurement techniques, data handling methods and storage of data in Europe. ACPC Steering Committee meeting at ISSI in Leader: Dario Papale, Italy Bern, from left: Bill Lau, Danny Rosenfeld, ● WG2: Work towards comprehensive Andi Andreae, Graham Feingold, Sandro multi-species flux monitoring sites. Fuzzi, Bjorn Stevens, Ulrike Lohmann. Leaders: Klaus Butterbach-Bahl, Germany, (Markku Kulmala absent from photo). and Nina Buchmann, Switzerland Photo: Anni Reissell. ● WG3: Assessment of regional representa- University of Helsinki, Kumpula Campus. tiveness of the flux sites in different The Aerosols, Clouds, Precipitation, Climate Photo: Ida Pimenoff. ecosystems. Leaders: Laurens Ganzeveld, (ACPC) Program Steering Committee (SC) is the Netherlands, and Markus Reichstein, also an International Space Science Institute The iLEAPS International Project Office and Germany (ISSI) Team (www.issibern.ch). In Bern, the the Division of Atmospheric Sciences and ● WG4: Training and capacity building. ACPC SC finalised the ACPC Science Plan Geophysics, Department of Physics, at the Leader: Janusz Olejnik, Poland. and Implementation Strategy (SP&IS) for ex- ternal review. University of Helsinki hosted a seminar by COST is an intergovernmental frame- Prof. Bjorn Stevens on “Towards a macro- work for European Cooperation in Science The SP&IS outlines ACPC’s scientific scopic theory of precipitation”. and Technology. approach which is based on the selection of a number of precipitating cloud regimes. Bjorn Stevens is new Director at the Max It attempts to reduce the fragmentation These regimes represent key environments Planck Institute for Meteorology in Hamburg, in European research investments and to for cloud formation and precipitation with Germany. Prof. Stevens came to Hamburg open the European Research Area to coop- strong indication of aerosol-cloud-precipi- from the University of California in Los Ange- eration worldwide. les (UCLA), USA, where he was Professor for tation interactions. See a more detailed Atmospheric Sciences. He has published description of the ACPC SC / ISSI Team ground-breaking research papers dealing meetings on pages 58–59 of this issue. with the theory, modelling and observation The first ACPC field experiments will start of “low” clouds, which is one of the most in Barbados and India in 2010. important problems in meteorology and climate research. Bjorn Stevens is co-chair in the Steering Committee of ACPC (Aerosol, Cloud, Precipi- For information on the Action, please see the ACPC web page: tation, Climate), an international research COST website: www.ileaps.org/acpc/ program initiated by iLEAPS in collaboration www.cost.esf.org/ with international research organisations and the Action website: ACPC mailing list: IGAC and GEWEX (WCRP). www.ileaps.org/cost0804 [email protected]

74 iLEAPS Newsletter Issue No. 7 ◆ June 2009 European Geosciences Union ESA-iLEAPS Scientific Advanced Aerosol Training Course, General Assembly 2009, Consultation Workshop, Hyytiälä Forestry Station, Finland, Vienna, Austria, Austrian Academy of Sciences, 9–15 May 2009 19–24 April 2009 Vienna, Austria, 20 April 2009 iLEAPS-sponsored/co-sponsored/related The European Space Agency (ESA) and the The course focussed on measurements of sessions: iLEAPS International Project Office organised atmospheric aerosols: aerosol physics, sam- ● AS1.5 Aerosols-clouds-precipitation- a consultation workshop for planning a new pling and measurement techniques. 28 climate. Conveners: M.O. Andreae, collaborative tender, the Atmosphere-LANd students from Finland, Italy, China, Greece, U. Lohmann, D. Rosenfeld Integrated Study (ALANIS). Austria, Pakistan, Brazil, Lithuania, Sweden, Slovenia, the Netherlands, Switzerland, ● CL20 Land-climate interactions from ALANIS aims at: France, Germany, Russia, Austria, and models and observations: Implications ● advancing the development and Denmark took part in the course that from past to future climate. Conveners: validation of novel advanced Earth required an advanced knowledge of atmos- S. Seneviratne, P. Ciais, B. van den Hurk Observation -based multi-mission pheric aerosols. ● BG2.2 Land-Atmosphere-Cryosphere products, improved data sets, and The target group included PhD students, Interactions in Northern Eurasia. Conven- enhanced applications; early-career scientists, and personnel from ers: P. Groisman, A. Reissell, I. Sokolik ● to use these to respond directly to the aerosol measuring stations involved in ● CL44 Shifting Seasons: Phenological specific scientific requirements of the iLEAPS community with a special EUSAAR (European Supersites for Atmos- evidence from observations, reconstruc- pheric Research), EUCAARI (European Inte- tions, measurements and models. attention to the Northern Eurasian Earth Science Partnership Initiative (NEESPI) grated Project on Aerosol Cloud Climate and Conveners: T. Rutishauser, A. Menzel, Air Quality Interactions), ACCENT (Atmos- J. Weltzin area; ● pheric Composition Change – the European ● AS1.14 African Monsoon improving the observation, understand- ing and prediction of land-atmosphere Network of Excellence), GAW (Global Atmos- Multidisciplinary Analysis (AMMA). phere Watch), and EMEP (European Monitor- Conveners: C. Taylor, S. Janicot, processes in boreal ecosystems at different spatial and time scales; ing and Evaluation Program). The course was H. Kunstmann taught in English. ● ● setting up a solid scientific basis for BG2.3 Synthesis Efforts From the Global Lecturers were Prof. Dr. Kaarle Hämeri, Network of Ecosystem-Atmosphere CO , further ESA activities in support of the 2 iLEAPS community. University of Helsinki, Finland, Dr. Jean- Water and Energy Exchange (FLUXNET). Philippe Putaud, Joint Research Centre, Italy, Conveners: M. Reichstein, D. Baldocchi, The project will be funded by ESA’s Sup- and Prof. Dr. Alfred Wiedensohler, Leibniz D. Papale port to Science Element (STSE) and awarded Institute for Tropospheric Research, Germany. ● BG2.6 From biogenic primary exchange to a consortium of private and public institu- The course was organised within the to atmospheric fluxes of reactive trace tions following an open competitive tender. frame of the EU-projects EUSAAR, EUCAARI gases. Conveners: J. Rinne, J. Kesselmeier, The corresponding invitation to tender is and ACCENT as well as the Nordic Graduate JP Schnitzler planned for the second quarter of 2009. School “Biosphere-Carbon-Aerosol-Cloud- ● CL6 Physical and biogeochemical Climate Interactions” (CBACCI) and Nordic feedbacks in the climate system. Master’s Degree Program “Atmosphere- Conveners: C.D. Jones, V. Alexeev Biosphere-Studies” (ABS) in cooperation with ● CL21 Biospheric feedbacks in the climate NorFA (Nordisk forskarutbildnigsakademi) system in the past, present, and future. Network on Atmospheric Aerosol Dynamics Conveners: M. Claussen, (NAD), iLEAPS and EMEP. V. Brovkin, N. Zeng ● BG1.8 Interactions between the carbon and hydrological cycle and the climate system. Conveners: C. Beer, M. Reichstein Visit for more information on the workshop ● AS3.12 Atmospheric VOC: measurements and the speakers: and interpretation. Conveners: http://dup.esrin.esa.int/STSE/news/news160.asp Pollmann, M. Boy, V. Sinha and www.ileaps.org/alanis www.eusaar.net/files/events/ http://meetings.copernicus.org/egu2009 for ALANIS. NA6_aerosolcourse2009.cfm

iLEAPS Newsletter Issue No. 7 ◆ June 2009 75 [email protected] http://www.ileaps.org

iLEAPS SCIENTIFIC STEERING COMMITTEE

Meinrat O. Andreae (Co-Chair), Biogeochemistry Department, Michael Keller, NEON Inc., Boulder, Colorado, USA Max Planck Institute for Chemistry, Mainz, Germany Markku Kulmala, Dept. Physics, University of Helsinki, Pavel Kabat (Co-Chair), Earth System Science & Climate Change Helsinki, Finland Group, Climate Change and Biosphere Centre, Wageningen Nathalie de Noblet-Ducoudré, Laboratoire des Sciences University and Research Centre, Wageningen, Netherlands du Climat et de l’Environnement (LSCE), Almut Arneth, Dept. Physical Geography and Gif-sur-Yvette cedex, France Ecosystems Analysis, Lund University, Lund, Sweden Andy Pitman, Climate Change Research Centre, Paulo Artaxo, Dept. Applied Physics, Institute of Physics, The University of New South Wales, Sydney, Australia University of São Paulo, São Paulo, Brazil Daniel Rosenfeld, The Hebrew University of Jerusalem, Mary Anne Carroll, Dept. Atmospheric, Jerusalem, Israel Oceanic and Space Sciences, Nobuko Saigusa, Office for Terrestrial Monitoring, Center University of Michigan, Ann Arbor, Michigan, USA for Global Environmental Research, National Institute for Torben R. Christensen, Dept. Physical Geography and Environmental Studies, Tsukuba, Japan Ecosystems Analysis, Lund University, Lund, Sweden Sonia I. Seneviratne, Institute for Atmospheric and John J. Finnigan, CSIRO Centre for Complex System Science, Climate Science, ETH Zurich, Switzerland CSIRO Atmospheric, Canberra, Australia Chandra Venkataraman, Dept. Chemical Engineering, Laurens Ganzeveld, Dept. Environmental Sciences, Indian Institute of Technology Bombay, Mumbai, India Earth System Sciences Group, Wageningen University Xiaodong Yan, Key Lab. Regional Climate-Environmental Research and Research Centre, Wageningen, Netherlands for Temperate East Asia (RCE-TEA), Institute of Atmospheric Physics, Sandy Harrison, School of Geographical Sciences, Chinese Academy of Science, Beijing, China University of Bristol, Bristol, UK

iLEAPS RECOGNIZED PROJECTS

ACPC

iLEAPS- GEIA LUCID

76 iLEAPS Newsletter Issue No. 7 ◆ June 2009