Sujay V. Kumar Scientists Have Made Great Strides in Modeling Physical
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Chemical Transport Modelling
Chemical Transport Modelling Beatriz M. Monge-Sanz and Martyn P. Chipperfield Institute for Atmospheric Science, School of Environment, University of Leeds, U.K. [email protected] 1. Introduction Nowadays, a large community of modellers use chemical transport models (CTMs) routinely to investigate the distribution and evolution of tracers in the atmosphere. Most CTMs use an ‘off-line’ approach, taking winds and temperatures from general circulation models (GCMs) or from meteorological analyses. The advantage of using analyses is that the CTM simulations are then linked to real meteorology and the results are directly comparable to observations. Reanalyses extend this advantage into the past, allowing us to perform long-term simulations that provide valuable information on the temporal evolution of the atmospheric composition and help understand the present and predict the future. CTMs therefore rely on the quality of the (re)analyses to obtain accurate tracers distributions. And, in its turn, this reliance makes CTMs be a powerful tool for the evaluation of the (re)analyses themselves. In this paper we discuss some of the main issues investigated by off-line CTMs and the requirements that these studies have for future (re)analyses. We also discuss tests performed by CTMs in order to evaluate the quality of the (re)analyses, to show in particular the recent improvements achieved in terms of stratospheric transport when the new ECMWF reanalysis winds are used for long-term simulations. 2. Past and present CTMs experiences with (re)analyses 2.1. Long-term ozone loss and stratospheric transport The ozone loss detected over the past 25 years has important implications, given the strong interactions between stratospheric ozone, UV radiation, circulation, tropospheric chemistry, human and natural activities. -
Curriculum Vitae ROBERT JEFFREY TRAPP Department of Atmospheric
Curriculum Vitae ROBERT JEFFREY TRAPP Department of Atmospheric Sciences University of Illinois at Urbana-Champaign 105 S. Gregory Street Urbana, Illinois 61801 [email protected] EDUCATION The University of Oklahoma, Ph.D. in Meteorology, 1994 Dissertation: Numerical Simulation of the Genesis of Tornado-Like Vortices Principal Advisor: Prof. Brian H. Fiedler Texas A&M University, M.S. in Meteorology, 1989 Thesis: The Effects of Cloud Base Rotation on Microburst Dynamics-A Numerical Investigation Principal Advisor: Prof. P. Das University of Missouri-Columbia, B.S. in Agriculture/Atmospheric Science, 1985 APPOINTMENTS Professor, University of Illinois at Urbana-Champaign, Department of Atmospheric Sciences, August 2014-current. Professor, Department of Earth and Atmospheric Sciences, Purdue University, August 2010- July 2014. Associate Professor, Department of Earth and Atmospheric Sciences, Purdue University, August 2003-August 2010 Research Scientist, Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Severe Storms Laboratory, July 1996-July 2003 Visiting Scientist, National Center for Atmospheric Research, Mesoscale and Microscale Meteorology Division, August 1998-December 2002 National Research Council Postdoctoral Research Fellow, at the National Severe Storms Laboratory, July 1994-June 1996 GRANTS AND FUNDING Principal Investigator, Modulation of convective-draft characteristics and subsequent tornado intensity by the environmental wind and thermodynamics within the Southeast U.S, NOAA, $287,529, 2017-2019 (pending formal approval by NOAA Grants Officer). Principal Investigator, Collaborative Research: Remote sensing of electrictrification, lightning, and mesoscale/microscale processes with adaptive ground observations during RELMPAGO, NSF-AGS, $636,947, 2017-2021. Co-Principal Investigator, Remote sensing of electrification, lightning, and mesoscale/microscale processes with adaptive ground observations (RELMPAGO), NSF-AGS, $23,940, 2016–2017. -
Evaluation of Global Observations-Based Evapotranspiration Datasets and IPCC AR4 Simulations B
Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations B. Mueller, S. Seneviratne, C. Jiménez, T. Corti, M. Hirschi, G. Balsamo, P. Ciais, P. Dirmeyer, J. Fisher, Z. Guo, et al. To cite this version: B. Mueller, S. Seneviratne, C. Jiménez, T. Corti, M. Hirschi, et al.. Evaluation of global observations- based evapotranspiration datasets and IPCC AR4 simulations. Geophysical Research Letters, Amer- ican Geophysical Union, 2011, 38 (6), pp.n/a-n/a. 10.1029/2010GL046230. hal-02929017 HAL Id: hal-02929017 https://hal.archives-ouvertes.fr/hal-02929017 Submitted on 28 Oct 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L06402, doi:10.1029/2010GL046230, 2011 Evaluation of global observations‐based evapotranspiration datasets and IPCC AR4 simulations B. Mueller,1 S. I. Seneviratne,1 C. Jimenez,2 T. Corti,1,3 M. Hirschi,1,4 G. Balsamo,5 P. Ciais,6 P. Dirmeyer,7 J. B. Fisher,8 Z. Guo,7 M. Jung,9 F. Maignan,6 M. F. McCabe,10 R. Reichle,11 M. Reichstein,9 M. Rodell,11 J. Sheffield,12 A. J. Teuling,1,13 K. -
Reanalyses As Predictability Tools
Reanalyses as predictability tools Kiyotoshi Takahashi, Yuhei Takaya and Shinya Kobayashi Japan Meteorological Agency (JMA) Tokyo, Japan [email protected] Abstract Reanalysis data have been used for research actively in meteorology, climatology and environmental studies. They are currently used in the operational climate monitoring and seasonal forecasting systems as well. Major advantage of reanalysis data is its homogeneity in time. Hindcast experiments based on homogeneous analyses give a measure of forecast predictability and predictable signals. In JMA, its own reanalysis (JRA-25) data have been widely used in works related to climate services as the fundamental data. Growing use of reanalysis data both in research and operational communities would enforce the feedbacks between them. JMA as an operational weather center will continue the reanalysis activity to support the climate and weather services. Recently JMA just has started the new project of reanalysis, JRA-55. The preliminary analysis of JRA-55 shows steady improvement in a field such as typhoon analysis. The better reanalysis product would be applied to assess the past weather disaster and used for disaster prevention in the future. 1. Introduction Reanalysis is to produce analysis data for the past long period by applying the fixed analysis procedures to maximally available observation data. Reanalysis is different from real-time operational analysis in operational weather forecast systems especially in data use and its quality control. Observational data used in reanalysis are composed of mainly three types: conventional data used for operational numerical weather prediction (NWP), delayed data which were not used operationally and data recovered or digitalized later. -
Facility for Weather and Climate Assessments (FACTS)
In Box Facility for Weather and Climate Assessments (FACTS) A Community Resource for Assessing Weather and Climate Variability Donald Murray, Andrew Hoell, Martin Hoerling, Judith Perlwitz, Xiao-Wei Quan, Dave Allured, Tao Zhang, Jon Eischeid, Catherine A. Smith, Joseph Barsugli, Jeff McWhirter, Chris Kreutzer, and Robert S. Webb ABSTRACT: The Facility for Weather and Climate Assessments (FACTS) developed at the NOAA Physical Sciences Laboratory is a freely available resource that provides the science commu- nity with analysis tools; multimodel, multiforcing climate model ensembles; and observational/ reanalysis datasets for addressing a wide class of problems on weather and climate variability and its causes. In this paper, an overview of the datasets, the visualization capabilities, and data dissemination techniques of FACTS is presented. In addition, two examples are given that show the use of the interactive analysis and visualization feature of FACTS to explore questions related to climate variability and trends. Furthermore, we provide examples from published studies that have used data downloaded from FACTS to illustrate the types of research that can be pursued with its unique collection of datasets. https://doi.org/10.1175/BAMS-D-19-0224.1 Corresponding author: Andrew Hoell, [email protected] In final form 18 April 2020 ©2020 American Meteorological Society For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy. AMERICAN METEOROLOGICAL SOCIETY Brought to you by -
Andrew J. Elmore I. Education II. Professional Experience III. Research
Andrew J. Elmore Associate Professor University of Maryland Center for Environmental Science http://www.umces.edu/al Appalachian Laboratory Tel: (301) 689-7124 301 Braddock Road Fax: (301) 689-7200 Frostburg, MD 21532 [email protected] I. Education 1997 B. Sc., Purdue University, Applied Physics 1999 M. Sc., Brown University, Geological Sciences 2003 Ph. D., Brown University, Geological Sciences II. Professional Experience 2003-2004 Postdoctoral Research Associate, Carnegie Institution for Science, Stanford, CA 2004-2005 Senior Research Associate, Dartmouth College, Hanover, NH 2005-2006 Research Assistant Professor, Dartmouth College, Hanover, NH 2006-2012 Assistant Professor, UMCES Appalachian Laboratory, Frostburg, MD 2012-present Associate Professor, UMCES Appalachian Laboratory, Frostburg, MD III. Research A. Area of professional expertise Applications of remote sensing time series to scientific questions at the interface of ecology, geology, and the human sciences. Particular emphasis has been placed on understanding (1) the impact of water resource use and climate variability on arid and semi-arid ecosystem functioning and services; (2) the impact of urbanization on hydrologic and biologic resources in temperate forests; and (3) landscape pattern in the response of ecosystems to climate change and variability. B. Publications 1. Peer-reviewed publications Elmore, AJ, JP Julian, SM Guinn, MC Fitzpatrick (2013) Potential stream density in mid- Atlantic U.S. watersheds. PLOS One, 8(8):e74819:1-15 Vest, KR, AJ Elmore, JM Kaste, GS Okin, Junran Li (2013) Estimating Total Horizontal Flux within shrub-invaded groundwater dependent meadows using empirical and mechanistic models. JGR-Earth Surface, 118:1132-1146 Craine, JM, N Fierer, KK McLauchlan, and AJ Elmore. -
Classifications of Winter Euro-Atlantic Circulation Patterns: An
1OCTOBER 2017 S T R Y H A L A N D H U T H 7847 Classifications of Winter Euro-Atlantic Circulation Patterns: An Intercomparison of Five Atmospheric Reanalyses JAN STRYHAL Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Prague, Czech Republic RADAN HUTH Department of Physical Geography and Geoecology, Faculty of Science, Charles University, and Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic (Manuscript received 1 February 2017, in final form 19 June 2017) ABSTRACT Atmospheric reanalyses have been widely used to study large-scale atmospheric circulation and its links to local weather and to validate climate models. Only little effort has so far been made to compare reanalyses over the Euro-Atlantic domain, with the exception of a few studies analyzing North Atlantic cyclones. In particular, studies utilizing automated classifications of circulation patterns—one of the most popular methods in synoptic climatology—have paid little or no attention to the issue of reanalysis evaluation. Here, five reanalyses [ERA-40; NCEP-1; JRA-55; Twentieth Century Reanalysis, version 2 (20CRv2); and ECMWF twentieth-century reanalysis (ERA-20C)] are compared as to the frequency of occurrence of cir- culation types (CTs) over eight European domains in winters 1961–2000. Eight different classifications are used in parallel with the intention to eliminate possible artifacts of individual classification methods. This also helps document how substantial effect a choice of method can have if one quantifies differences between reanalyses. In general, ERA-40, NCEP-1, and JRA-55 exhibit a fairly small portion of days (under 8%) classified to different CTs if pairs of reanalyses are compared, with two exceptions: over Iceland, NCEP-1 shows disproportionately high frequencies of CTs with cyclones shifted south- and eastward; over the eastern Mediterranean region, ERA-40 and NCEP-1 disagree on classification of about 22% of days. -
Books and Monographs Refereed Journal Articles
Books and monographs Keim, B.D., and R.A. Muller. 2009. Hurricanes of the Gulf of Mexico. Louisiana State University Press: Baton Rouge, Louisiana, 232 pp. Zielinski, G.A., and B.D. Keim. 2003. New England Weather, New England Climate. University Press of New England: Hanover, New Hampshire, 296 pp. Faiers, G.E., B.D. Keim, and R.A. Muller. 1997. Rainfall Frequency/Magnitude Atlas for the South-Central United States. Geoscience Publications: Baton Rouge, Louisiana, 40 pp. Refereed Journal Articles 62. Lewis, A.B., and B.D. Keim. In Press. History and Applications of Manual Synoptic Classification. Earth Systems and Environmental Sciences. 61. Needham, H.F., B.D.Keim, and D. Sathiaraj. In Press. A Review of Tropical Cyclone- Generated Storm Surges: Global Data Sources, Observations and Impacts. Reviews of Geophysics. 60. Powell, E.J., and B.D. Keim. 2015. Trends in Daily Temperature and Precipitation Extremes for the Southeastern United States: 1948-2012. Journal of Climate 28:1592-1612. DOI: http://dx.doi.org/10.1175/JCLI-D-14-00410.1 59. Lewis, A.B., and B.D. Keim. In Press (available online). A Hybrid Procedure for Classifying Synoptic Weather Types for Louisiana. International Journal of Climatology. DOI: 10.1002/joc.4283 58. Allard, J.M., C.R. Thompson, and B.D. Keim. 2015. How Robust is the Pre-1931 National Climatic Data Center - Climate Divisional Dataset? Examples from Georgia and Louisiana. Theoretical and Applied Climatology 120(1-2):323-330. DOI 10.1007/s007. 57. Needham, H.F., and B.D. Keim. 2014. Correlating Storm Surge Heights with Tropical Cyclone Winds at and before Landfall. -
DART/CAM: an Ensemble Data Assimilation System for CESM Atmospheric Models
6304 JOURNAL OF CLIMATE VOLUME 25 DART/CAM: An Ensemble Data Assimilation System for CESM Atmospheric Models KEVIN RAEDER,JEFFREY L. ANDERSON,NANCY COLLINS, AND TIMOTHY J. HOAR IMAGe, CISL, National Center for Atmospheric Research,* Boulder, Colorado JENNIFER E. KAY AND PETER H. LAURITZEN CGD, NESL, National Center for Atmospheric Research,* Boulder, Colorado ROBERT PINCUS University of Colorado, and NOAA/Earth System Research Laboratory, Boulder, Colorado (Manuscript received 14 July 2011, in final form 2 April 2012) ABSTRACT The Community Atmosphere Model (CAM) has been interfaced to the Data Assimilation Research Testbed (DART), a community facility for ensemble data assimilation. This provides a large set of data assimilation tools for climate model research and development. Aspects of the interface to the Community Earth System Model (CESM) software are discussed and a variety of applications are illustrated, ranging from model development to the production of long series of analyses. CAM output is compared directly to real observations from platforms ranging from radiosondes to global positioning system satellites. Such com- parisons use the temporally and spatially heterogeneous analysis error estimates available from the ensemble to provide very specific forecast quality evaluations. The ability to start forecasts from analyses, which were generated by CAM on its native grid and have no foreign model bias, contributed to the detection of a code error involving Arctic sea ice and cloud cover. The potential of parameter estimation is discussed. A CAM ensemble reanalysis has been generated for more than 15 yr. Atmospheric forcings from the reanalysis were required as input to generate an ocean ensemble reanalysis that provided initial conditions for decadal prediction experiments. -
NASA and National Reanalysis Program
Reanalysis: Data Assimilation for Scientific Investigation of Climate Richard B. Rood1 and Michael G. Bosilovich2 1University of Michigan, Ann Arbor, MI, USA, [email protected] 2NASA Goddard Space Flight Center, MD, USA, [email protected] 1 Introduction Reanalysis is the assimilation of long time series of observations with an unvarying assimilation system to produce datasets for a variety of applications; for example, climate variability, chemistry-transport, and process studies. Reanalyses were originally proposed for atmospheric observations as a method to generate “climate” datasets from “weather” observations. As the satellite records of chemical, land and oceanic parameters build with time, “reanalyses” are being developed for other types of observations. Coupled reanalyses, for example atmospheric-ocean reanalyses, are possible. In addition, very long reanalyses that use no satellite observations are being planned (e.g. Compo et al. 2006). Reanalysis datasets have become one of the most important datasets for scientific and application communities. As of July 2009, the Kalnay et al. (1996) paper, which describes one of the first reanalysis datasets, has more than 6600 recorded citations. In this chapter discussion will be drawn from the experience of atmospheric reanalysis, and the issues raised are relevant to all types of reanalysis. The provision of reanalyses was advocated by Bengtsson and Shukla (1988) and Trenberth and Olson (1988) in order to provide homogeneous datasets for climate applications and to encourage research in the use of satellite observations without the operational constraints of Numerical Weather Prediction. Trenberth and Olson (1988) calculated derived products, such as the Hadley circulation, from assimilation analyses used in operational weather forecasting. -
Patricia M. Parker (Née Lawston), Ph.D
Patricia M. Parker (née Lawston), Ph.D. Assistant Research Scientist (effective 07/01/2020) Postdoctoral Research Associate Earth System Science Interdisciplinary Center (ESSIC), University of Maryland NASA Goddard Space FliGht Center Code 617.0, BldG 33, Room H104 Greenbelt, MD 20771 Email: [email protected]; Tel: 301-614-5319 EDUCATION 2017 Ph.D. ClimatoloGy, University of Delaware, Newark, DE 2013 M.S. GeoGraphy, University of Delaware, Newark, DE 2010 B.S. MeteoroloGy, Mathematics minor, Millersville University, Millersville, PA PROFESSIONAL APPOINTMENTS 7/2020–Present Assistant Research Scientist, Earth System Science Interdisciplinary Center (ESSIC) at NASA Goddard Space FliGht Center 1/2017–7/2020 Postdoctoral Associate, Earth System Science Interdisciplinary Center (ESSIC) at NASA Goddard Space FliGht Center PEER-REVIEWED PUBLICATIONS In Review (2020 expected) Shepherd, M., A. Thomas, J.A. Santanello, P.M. Lawston, J. Yoo: Warm core structure maintenance over land: A case study analysis of Cyclone Kelvin. Submitted to Journal of Southern Hemisphere Earth Systems Science 6/11/19 (preparinG for 2nd review). (2020 expected) Yoo, J., J. A. Santanello, M. Shepherd, S. V. Kumar, P. M. Lawston, A. M. Thomas: Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification over Land. Submitted to Journal of Hydrometeorology 9/13/19 (under 3rd review). (2020 expected) Shellito, P. J., S. V. Kumar, J. A. Santanello, P. M. Lawston Parker, John D. Bolten, Michael H. Cosh, David D. Bosch, Chandra D. Holifield Collins, Stan LivinGston, John Prueger, Mark Seyfried, Patrick J. Starks: AssessinG the Impact of Soil Layer Specification on the Observability of Modeled Soil Moisture and BriGhtness Temperature. -
An Idealized Physical Model for the Severe Convective Storm
Generated using the official AMS LATEX template—two-column layout. FOR AUTHOR USE ONLY, NOT FOR SUBMISSION! J OURNALOFTHE A TMOSPHERIC S CIENCES An idealized physical model for the severe convective storm environmental sounding Accepted in Journal of the Atmospheric Sciences 2020-10-26, there may still be copy-editing errors DANIEL R. CHAVAS* Purdue University, Department of Earth, Atmospheric, and Planetary Sciences, West Lafayette, IN DANIEL T. DAWSON II Purdue University, Department of Earth, Atmospheric, and Planetary Sciences, West Lafayette, IN ABSTRACT This work develops a theoretical model for steady thermodynamic and kinematic profiles for severe con- vective storm environments, building off of the two-layer static energy framework developed in Agard and Emanuel (2017). The model is phrased in terms of static energy, and it allows for independent variation of the boundary layer and free troposphere separated by a capping inversion. An algorithm is presented to apply the model to generate a sounding for numerical simulations of severe convective storms, and the model is compared and contrasted with that of Weisman and Klemp. The model is then fit to a case-study sounding associated with the 3 May 1999 tornado outbreak, and its potential utility is demonstrated via idealized nu- merical simulation experiments. A long-lived supercell is successfully simulated with the historical sounding but not the analogous theoretical sounding. Two types of example experiments are then performed that do simulate a long-lived supercell: 1) a semi-theoretical experiment in which a portion of the theoretical sound- ing is modified to match the real sounding (low-level moisture); 2) a fully-theoretical experiment in which a model physical parameter is modified (free-tropospheric relative humidity).