The Yale Interactive Terrestrial Biosphere Model Version 1.0: Description, Evaluation and Implementation Into NASA GISS Modele2
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Geosci. Model Dev., 8, 2399–2417, 2015 www.geosci-model-dev.net/8/2399/2015/ doi:10.5194/gmd-8-2399-2015 © Author(s) 2015. CC Attribution 3.0 License. The Yale Interactive terrestrial Biosphere model version 1.0: description, evaluation and implementation into NASA GISS ModelE2 X. Yue and N. Unger School of Forestry and Environment Studies, Yale University, New Haven, Connecticut 06511, USA Correspondence to: X. Yue ([email protected]) Received: 24 March 2015 – Published in Geosci. Model Dev. Discuss.: 10 April 2015 Revised: 18 July 2015 – Accepted: 21 July 2015 – Published: 5 August 2015 Abstract. The land biosphere, atmospheric chemistry and 1982–2011, with seasonality and spatial distribution consis- climate are intricately interconnected, yet the modeling tent with the satellite observations. We assess present-day of carbon–climate and chemistry–climate interactions have global ozone vegetation damage using the offline YIBs con- evolved as entirely separate research communities. We de- figuration. Ozone damage reduces global GPP by 2–5 % an- scribe the Yale Interactive terrestrial Biosphere (YIBs) model nually with regional extremes of 4–10 % in east Asia. The on- version 1.0, a land carbon cycle model that has been devel- line model simulates annual GPP of 123 ± 1 Pg C and NEE oped for coupling to the NASA Goddard Institute for Space of −2.7 ± 0.7 Pg C. NASA ModelE2-YIBs is a useful new Studies (GISS) ModelE2 global chemistry–climate model. tool to investigate coupled interactions between the land car- The YIBs model adapts routines from the mature TRIFFID bon cycle, atmospheric chemistry, and climate change. (Top-down Representation of Interactive Foliage and Flora Including Dynamics) and CASA (Carnegie–Ames–Stanford Approach) models to simulate interactive carbon assimila- tion, allocation, and autotrophic and heterotrophic respira- 1 Introduction tion. Dynamic daily leaf area index is simulated based on carbon allocation and temperature- and drought-dependent The terrestrial biosphere interacts with the atmosphere prognostic phenology. YIBs incorporates a semi-mechanistic through the exchanges of energy, carbon, reactive gases, wa- ozone vegetation damage scheme. Here, we validate the ter, and momentum fluxes. Forest ecosystems absorb an es- present-day YIBs land carbon fluxes for three increasingly timated 120 Pg C year−1 from the atmosphere (Beer et al., complex configurations: (i) offline local site level, (ii) offline 2010) and mitigate about one-quarter of the anthropogenic global forced with WFDEI (WATCH Forcing Data method- carbon dioxide (CO2) emissions (Friedlingstein et al., 2014). ology applied to ERA-Interim data) meteorology, and (iii) This carbon assimilation is sensitive to human-caused pertur- online coupled to the NASA ModelE2 (NASA ModelE2- bations including climate change and land use change (Zhao YIBs). Offline YIBs has hourly and online YIBs has half- and Running, 2010; Houghton et al., 2012) and is affected by hourly temporal resolution. The large observational database atmospheric pollutants such as ozone and aerosols (Sitch et used for validation includes carbon fluxes from 145 flux al., 2007; Mercado et al., 2009). Over the past 2–3 decades, a tower sites and multiple satellite products. At the site level, number of terrestrial biosphere models have been developed YIBs simulates reasonable seasonality (correlation coeffi- as tools to quantify the present-day global carbon budget in cient R > 0.8) of gross primary productivity (GPP) at 121 out conjunction with available but sparse observations (e.g., Jung of 145 sites with biases in magnitude ranging from −19 to et al., 2009), to understand the relationships between ter- 7 % depending on plant functional type. On the global scale, restrial biospheric fluxes and environmental conditions (e.g., the offline model simulates an annual GPP of 125 ± 3 Pg C Zeng et al., 2005), to attribute drivers of trends in the carbon and net ecosystem exchange (NEE) of −2.5 ± 0.7 Pg C for cycle during the anthropogenic era (e.g., Sitch et al., 2015), Published by Copernicus Publications on behalf of the European Geosciences Union. 2400 X. Yue and N. Unger: The Yale Interactive terrestrial Biosphere model version 1.0 and to project future changes in the land biosphere and the Koch et al., 2011; Unger, 2011; Shindell et al., 2013b; Miller consequences for regional and global climate change (e.g., et al., 2014). To our knowledge, this study represents the first Friedlingstein et al., 2006). description and validation of an interactive climate-sensitive Emerging research identifies climatically relevant interac- closed land carbon cycle in NASA ModelE2. The impacts of tions between the land biosphere and atmospheric chemistry the updated vegetation scheme on the chemistry and climate (e.g, Huntingford et al., 2011). For instance, stomatal uptake simulations in NASA ModelE2 will be addressed in other is an important sink of tropospheric ozone (Val Martin et al., ongoing research. Section 2 describes the observational data 2014) but damages photosynthesis, reduces plant growth and sets used to evaluate YIBs land carbon cycle performance. biomass accumulation, limits crop yields, and affects stom- Section 3 describes physical parameterizations of the vege- atal control over plant transpiration of water vapor between tation model. Section 4 explains the model setup and simu- the leaf surface and atmosphere (Ainsworth et al., 2012; lations in three configurations. Section 5 presents the results Hollaway et al., 2012). The indirect CO2 radiative forcing of the model evaluation and Sect. 6 summarizes the model due to the vegetation damage effects of anthropogenic ozone performance. increases since the industrial revolution may be as large as C0.4 W m−2 (Sitch et al., 2007), which is 25 % of the magni- YIBs design strategy tude of the direct CO2 radiative forcing over the same period, and of similar magnitude to the direct ozone radiative forc- Many land carbon cycle models already exist (e.g., Sitch et ing. Atmospheric oxidation of biogenic volatile organic com- al., 2015, and references therein; Schaefer et al., 2012, and pound (BVOC) emissions affects surface air quality and ex- references therein). We elected to build YIBs in a step-by- erts additional regional and global chemical climate forcings step process such that our research group has intimate fa- (Scott et al., 2014; Unger, 2014a, b). Fine-mode atmospheric miliarity with the underlying scientific processes, rather than pollution particles affect the land biosphere by changing the adopting an existing model as a “black box”. This unconven- physical climate state and through diffuse radiation fertiliza- tional interdisciplinary approach is important for discerning tion (Mercado et al., 2009; Mahowald, 2011). Land plant the complex mutual feedbacks between atmospheric chem- phenology has experienced substantial changes in the last istry and the land carbon sink under global change. The de- few decades (Keenan et al., 2014), possibly influencing both velopment of the YIBs land carbon cycle model has pro- ozone deposition and BVOC emissions through the exten- ceeded in three main steps. The first step was the implemen- sion of growing seasons. These coupled interactions are often tation of vegetation biophysics, photosynthesis-dependent not adequately represented in current generation land bio- BVOC emissions and ozone vegetation damage that have sphere models or global chemistry–climate models. Global been extensively documented, validated and applied in seven land carbon cycle models often prescribe offline ozone and previous publications (Unger, 2013, 2014a, b; Unger et al., aerosol fields (e.g., Sitch et al., 2007; Mercado et al., 2009), 2013; Unger and Yue, 2014; Yue and Unger, 2014; Zheng and global chemistry–climate models often prescribe fixed et al., 2015). The second step was the selection of the YIBs offline vegetation fields (e.g., Lamarque et al., 2013; Shindell default phenology scheme based on rigorous intercompari- et al., 2013a). However, multiple mutual feedbacks occur be- son of 13 published phenological models (Yue et al., 2015a). tween vegetation physiology and reactive atmospheric chem- This study represents the third step to simulate the closed ical composition that are completely neglected using these climate-sensitive land carbon cycle: implementation of inter- previous offline approaches. Model frameworks are needed active carbon assimilation, allocation, autotrophic and het- that fully two-way couple the land carbon cycle and atmo- erotrophic respiration, and dynamic tree growth (changes in spheric chemistry and simulate the consequences for climate both height and LAI). For this third step, we purposefully change. select the mature, well-supported, well-established, readily Our objective is to present the description and present- available and accessible community algorithms: TRIFFID day evaluation of the Yale Interactive terrestrial Biosphere (Top-down Representation of Interactive Foliage and Flora (YIBs) model version 1.0 that has been developed for the Including Dynamics; Cox, 2001; Clark et al., 2011) and the investigation of carbon–chemistry–climate interactions. The Carnegie–Ames–Stanford Approach (CASA) (Potter et al., YIBs model can be used in three configurations: (i) offline lo- 1993; Schaefer et al., 2008). TRIFFID has demonstrated pre- cal site level, (ii) offline global forced with WFDEI (WATCH vious usability in carbon–chemistry–climate interactions re- Forcing Data methodology applied to ERA-Interim