I. Baker

Colorado State University, Fort Collins, Colorado, United States

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Publications (106)158.68 Total impact

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    ABSTRACT: Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated gridded (1° spatial resolution) runoff from six terrestrial biosphere models (TBMs), seven reanalysis products, and one gridded surface station product in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of these 14 estimates with stream gauge data, both as depleted flow and corrected for net withdrawals (2005 only), at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71 to 356 mm yr−1) relative to observed continental-scale runoff (209 or 280 mm yr−1 when corrected for net withdrawals). Across all 14 products 8 exhibit Nash–Sutcliffe efficiency values in excess of 0.8 and three are within 10% of the observed value. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regions—although two products are systematically biased across all regions—and largely scales with water use. Although gridded composite TBM and reanalysis runoff show some regional similarities, individual product values are highly variable. At the coarse scales used here we find that progress in better constraining simulated runoff requires standardized forcing data and the explicit incorporation of human effects (e.g., water withdrawals by source, fire, and land use change).
    Ecological Modelling 05/2015; 303. DOI:10.1016/j.ecolmodel.2015.02.006 · 2.07 Impact Factor
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    ABSTRACT: Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magni-tude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for the Alaskan Arctic from four recent model intercomparison projects – NACP (North American Carbon Program) site and regional syntheses, TRENDY (Trends in net land atmosphere carbon exchanges), and WETCHIMP (Wetland and Wetland CH 4 Inter-comparison of Models Project) – we provide a baseline of terrestrial carbon cycle uncertainty, defined as the multi-model standard deviation (σ) for each quantity that follows. Mean annual absolute uncertainty was largest for soil carbon (14.0 ± 9.2 kg C m −2), then gross primary pro-duction (GPP) (0.22 ± 0.50 kg C m −2 yr −1), ecosystem res-piration (Re) (0.23 ± 0.38 kg C m −2 yr −1), net primary pro-duction (NPP) (0.14 ± 0.33 kg C m −2 yr −1), autotrophic res-piration (Ra) (0.09 ± 0.20 kg C m −2 yr −1), heterotrophic res-piration (Rh) (0.14 ± 0.20 kg C m −2 yr −1), net ecosystem ex-change (NEE) (−0.01 ± 0.19 kg C m −2 yr −1), and CH 4 flux (2.52 ± 4.02 g CH 4 m −2 yr −1). There were no consistent spa-tial patterns in the larger Alaskan Arctic and boreal regional carbon stocks and fluxes, with some models showing NEE for Alaska as a strong carbon sink, others as a strong car-bon source, while still others as carbon neutral. Finally, AmeriFlux data are used at two sites in the Alaskan Arc-tic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assess-ment of carbon cycle uncertainties may be used as a base-line for the improvement of experimental and modeling ac-tivities, as well as a reference for future trajectories in car-bon cycling with climate change in the Alaskan Arctic and larger boreal region.
    Biogeosciences 08/2014; 11(18):4271-4288. DOI:10.5194/bg-11-4271-2014 · 3.75 Impact Factor
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    ABSTRACT: Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for Alaska, we provide a baseline of terrestrial carbon cycle structural and parametric uncertainty, defined as the multi-model standard deviation (σ) against the mean (x\bar) for each quantity. Mean annual uncertainty (σ/x\bar) was largest for net ecosystem exchange (NEE) (-0.01± 0.19 kg C m-2 yr-1), then net primary production (NPP) (0.14 ± 0.33 kg C m-2 yr-1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m-2 yr-1), gross primary production (GPP) (0.22 ± 0.50 kg C m-2 yr-1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m-2 yr-1), CH4 flux (2.52 ± 4.02 g CH4 m-2 yr-1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m-2 yr-1), and soil carbon (14.0± 9.2 kg C m-2). The spatial patterns in regional carbon stocks and fluxes varied widely with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Additionally, a feedback (i.e., sensitivity) analysis was conducted of 20th century NEE to CO2 fertilization (β) and climate (γ), which showed that uncertainty in γ was 2x larger than that of β, with neither indicating that the Alaskan Arctic is shifting towards a certain net carbon sink or source. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic.
    Biogeosciences Discussions 01/2014; 11(2). DOI:10.5194/bgd-11-2887-2014
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    ABSTRACT: Significant changes in the water cycle are expected under current global environmental change. Robust assessment of these changes at global scales is confounded by shortcomings in the observed record. Modeled assessments yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated runoff from six terrestrial biosphere models (TBMs), five reanalysis products, and one gridded surface station product with observations from a network of stream gauges in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of simulated runoff with stream gauge data at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71-356 mm yr-1) relative to observed continental-scale runoff (209 mm yr-1). Across all 12 products only two are within 10% of the observed value and only four exhibit Nash-Sutcliffe efficiency values in excess of 0.8. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regions; although two products are systematically biased across all regions. In contrast, bias in a temporal sense, within region by water year, is highly consistent. Although gridded composite TBM and reanalysis runoff show some regional similarities for 2001-2005 with CONUS means, individual product values are highly variable. To further constrain simulated runoff and to link model-observation mismatch to model structural characteristics would require watershed-level simulation studies coupled with river routing schemes, standardized forcing data, and explicit consideration of water cycle management.
    Biogeosciences Discussions 12/2013; 11(1). DOI:10.5194/bgd-11-1801-2014
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    ABSTRACT: Surface ecophysiology at five sites in tropical South America across vegetation and moisture gradients is investigated. From the moist northwest (Manaus) to the relatively dry southeast (Pé de Gigante, state of São Paulo) simulated seasonal cycles of latent and sensible heat, and carbon flux produced with the Simple Biosphere Model (SiB3) are confronted with observational data. In the northwest, abundant moisture is available, suggesting that the ecosystem is light-limited. In these wettest regions, Bowen ratio is consistently low, with little or no annual cycle. Carbon flux shows little or no annual cycle as well; efflux and uptake are determined by high-frequency variability in light and moisture availability. Moving downgradient in annual precipitation amount, dry season length is more clearly defined. In these regions, a dry season sink of carbon is observed and simulated. This sink is the result of the combination of increased photosynthetic production due to higher light levels, and decreased respiratory efflux due to soil drying. The differential response time of photosynthetic and respiratory processes produce observed annual cycles of net carbon flux. In drier regions, moisture and carbon fluxes are in-phase; there is carbon uptake during seasonal rains and efflux during the dry season. At the driest site, there is also a large annual cycle in latent and sensible heat flux.
    Agricultural and Forest Meteorology 12/2013; DOI:10.1016/j.agrformet.2012.11.015 · 3.89 Impact Factor
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    ABSTRACT: [1] Carbonyl sulfide (COS) is an atmospheric trace gas that participates in some key reactions of the carbon cycle and thus holds great promise for studies of carbon cycle processes. Global monitoring networks and atmospheric sampling programs provide concurrent data on COS and CO2 concentrations in the free troposphere and atmospheric boundary layer over vegetated areas. Here we present a modeling framework for interpreting these data and illustrate what COS measurements might tell us about carbon cycle processes. We implemented mechanistic and empirical descriptions of leaf and soil COS uptake into a global carbon cycle model (SiB 3) to obtain new estimates of the COS land flux. We then introduced these revised boundary conditions to an atmospheric transport model (Parameterized Chemical Transport Model) to simulate the variations in the concentration of COS and CO2 in the global atmosphere. To balance the threefold increase in the global vegetation sink relative to the previous baseline estimate, we propose a new ocean COS source. Using a simple inversion approach, we optimized the latitudinal distribution of this ocean source and found that it is concentrated in the tropics. The new model is capable of reproducing the seasonal variation in atmospheric concentration at most background atmospheric sites. The model also reproduces the observed large vertical gradients in COS between the boundary layer and free troposphere. Using a simulation experiment, we demonstrate that comparing drawdown of CO2 with COS could provide additional constraints on differential responses of photosynthesis and respiration to environmental forcing. The separation of these two distinct processes is essential to understand the carbon cycle components for improved prediction of future responses of the terrestrial biosphere to changing environmental conditions.
    Journal of Geophysical Research: Biogeosciences 06/2013; 118(2). DOI:10.1002/jgrg.20068 · 3.44 Impact Factor
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    ABSTRACT: There is a continued need for models to improve consistency and agreement with observations [Friedlingstein et al., 2006], both overall and under more frequent extreme climatic events related to global environmental change such as drought [Trenberth et al., 2007]. Past validation studies of terrestrial biosphere models have focused only on few models and sites, typically in close proximity and primarily in forested biomes [e.g., Amthor et al., 2001; Delpierre et al., 2009; Grant et al., 2005; Hanson et al., 2004; Granier et al., 2007; Ichii et al., 2009; Ito, 2008; Siqueira et al., 2006; Zhou et al., 2008]. Furthermore, assessing model‐data agreement relative to drought requires, in addition to high‐quality observedCO2 exchange data, a reliable drought metric as well as a natural experiment across sites and drought conditions.
    Journal of Geophysical Research Atmospheres 02/2013; 115. DOI:10.1029/2009JG001229 · 3.44 Impact Factor
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    ABSTRACT: Export Date: 25 July 2013, Source: Scopus, Article in Press
    Agricultural and Forest Meteorology; 01/2013
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    ABSTRACT: This data set provides standardized output variables for gross primary productivity (GPP), net ecosystem exchange (NEE), leaf area index (LAI), ecosystem respiration (Re), latent heat flux (LE), and sensible heat flux (H) from 24 terrestrial biosphere models for 47 eddy covariance flux tower sites in North America. Each model used standardized input data for each flux tower site (i.e., gap-filled, locally observed weather; land use history; and other site specific data) and followed standard model setup and spinup procedures. The files also contain gap-filled observations and total uncertainty estimates. The data set was compiled for the North American Carbon Program (NACP) Site-Level Synthesis for use in model inter-comparison and assessment of how well the models simulate carbon processes across vegetation types and environmental conditions in North America. There is one compressed (.zip) file with this data set. When expanded, the .zip file contains model output data for one variable at one site. The model output and observations are available at the native half-hourly time step, or in daily, monthly, and annual aggregations, in comma-separated text (.csv) format.
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    ABSTRACT: Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model-data agreement, but usually do not identify the time and frequency patterns of model-data disagreement, leaving unclear the steps required to improve model response to environmental drivers that vary on characteristic frequencies. Wavelet coherence can quantify the times and timescales at which two time series, for example time series of models and measurements, are significantly different. We applied wavelet coherence to interpret the predictions of 20 ecosystem models from the North American Carbon Program (NACP) Site-Level Interim Synthesis when confronted with eddy-covariance-measured net ecosystem exchange (NEE) from 10 ecosystems with multiple years of available data. Models were grouped into classes with similar approaches for incorporating phenology, the calculation of NEE, the inclusion of foliar nitrogen (N), and the use of model-data fusion. Models with prescribed, rather than prognostic, phenology often fit NEE observations better on annual to interannual timescales in grassland, wetland and agricultural ecosystems. Models that calculated NEE as net primary productivity (NPP) minus heterotrophic respiration (HR) rather than gross ecosystem productivity (GPP) minus ecosystem respiration (ER) fit better on annual timescales in grassland and wetland ecosystems, but models that calculated NEE as GPP minus ER were superior on monthly to seasonal timescales in two coniferous forests. Models that incorporated foliar nitrogen (N) data were successful at capturing NEE variability on interannual (multiple year) timescales at Howland Forest, Maine. The model that employed a model-data fusion approach often, but not always, resulted in improved fit to data, suggesting that improving model parameterization is important but not the only step for improving model performance. Combined with previous findings, our results suggest that the mechanisms driving daily and annual NEE variability tend to be correctly simulated, but the magnitude of these fluxes is often erroneous, suggesting that model parameterization must be improved. Few NACP models correctly predicted fluxes on seasonal and interannual timescales where spectral energy in NEE observations tends to be low, but where phenological events, multi-year oscillations in climatological drivers, and ecosystem succession are known to be important for determining ecosystem function. Mechanistic improvements to models must be made to replicate observed NEE variability on seasonal and interannual timescales.
    Biogeosciences 01/2013; 10(11-11):6893-6909. DOI:10.5194/bg-10-6893-2013 · 3.75 Impact Factor
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    ABSTRACT: Correct representations of root functioning, such as root water uptake and hydraulic redistribution, are critically important for modeling the responses of vegetation to droughts and seasonal changes in soil moisture content. However, these processes are poorly represented in global land surface models. In this study, we incorporated two root functions: a root water uptake function which assumes root water uptake efficiency varies with rooting depth, and a hydraulic redistribution function into a global land surface model, CABLE. The water uptake function developed by Lai and Katul (2000) was also compared with the default one (see Wang et al., 2010) that assumes that efficiency of water uptake per unit root length is constant. Using eddy flux measurements of CO2 and water vapor fluxes at three sites experiencing different patterns of seasonal changes in soil water content, we showed that the two root functions significantly improved the agreement between the simulated fluxes of net ecosystem exchange and latent heat flux and soil moisture dynamics with those observed during the dry season while having little impact on the model simulation during the wet seasons at all three sites. Sensitivity analysis showed that varying several model parameters influencing soil water dynamics in CABLE did not significantly affect the model's performance. We conclude that these root functions represent a valuable improvement for land surface modeling and should be implemented into CABLE and other land surface models for studying carbon and water dynamics where rainfall varies seasonally or interannually.
    Journal of Geophysical Research Atmospheres 10/2012; 117(G4). DOI:10.1029/2012JG002038 · 3.44 Impact Factor
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    ABSTRACT: Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000–2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America. Thus, the RCIS focuses on model simulations available from analyses that have been completed by ongoing NACP projects and other recently published studies. The TBM flux estimates are compared and evaluated over different spatial (1◦ × 1◦ and spatially aggregated to different regions) and temporal (monthly and annually) scales. The range in model estimates of net ecosystem productivity (NEP) for North America is much narrower than estimates of productivity or respiration, with estimates of NEP varying between −0.7 and 2.2 PgC yr−1, while gross primary productivity and heterotrophic respiration vary between 12.2 and 32.9 PgC yr−1 and 5.6 and 13.2 PgC yr−1, respectively. The range in estimates from the models appears to be driven by a combination of factors, including the representation of photosynthesis, the source and of environmental driver data and the temporal
    Ecological Modelling 07/2012; 232:144-157. DOI:10.1016/j.ecolmodel.2012.02.004 · 2.07 Impact Factor
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    ABSTRACT: Interannual variability in biosphere-atmosphere exchange of CO2 is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter-annual variability in observations. Herein, using standardized data from the North American Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long-term measurements of biosphere-atmosphere CO2 exchange made with eddy-covariance flux towers at 11 forested sites in North America. Instead of focusing on model-data agreement we take a systematic, variability-oriented approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.
    Global Change Biology 06/2012; DOI:10.1111/j.1365-2486.2012.02678.x · 8.22 Impact Factor
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    ABSTRACT: Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.
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    ABSTRACT: Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0�C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0�C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such as ɛmax (LUE), Vcmax (unstressed Rubisco catalytic capacity) or Jmax (the maximum electron transport rate).
    Journal of Geophysical Research Atmospheres 01/2012; 117:G03010. · 3.44 Impact Factor
  • B. Orescanin · A. Denning · I. T. Baker
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    ABSTRACT: The exchange of the trace gases between the land and atmosphere is highly influenced by vegetation. Therefore, the representation of phenological properties in global carbon models plays a key role in understanding and predicting the global carbon cycle. Phenological parameters such as Leaf Area Index (LAI) and fraction of photosynthetically active radiation absorbed (fPAR) are often calculated or estimated based on remote sensing measurements, which can be biased by clouds, aerosols, or snow. Alternatively, we can prognose vegetation phenology through the use of models that predict vegetation status based on meteorological conditions. Here our goal is to provide better understanding of carbon dynamics as a function of phenological parameters and their dependence on meteorological forcing. We evaluate phenological characteristics and their influence on carbon dynamics at several grassland sites. Modeled carbon flux, as a function of both diagnosed (from satellite) and prognosed phenological state are confronted with data from flux towers. Remotely-sensed phenology has a tendency to expand the growing season, and does not reflect the rapid response of vegetation in rain-green biomes as well as the prognostic phenology model does. These differences in phenology are reflected in modeled fluxes of energy, moisture, and carbon.
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    ABSTRACT: We compare global variations in atmospheric CO2 concentrations using a comprehensive model of surface carbon cycling and atmospheric transport to retrievals of column CO2 mole fraction from near-infrared spectroscopy from the GOSAT mission. Surface carbon exchanges due to photosynthesis, respiration, decomposition, biomass burning, fossil fuel combustion, and air-sea gas exchange are computed every hour. These fluxes are used as input to a global atmospheric tranport model to obtain three-dimensional fields of CO2, which are sampled at the time and location of quality-screened GOSAT data retrieved by the Atmospheric Carbon Observations from Space (ACOS) team. The system is operated on a 0.5° x 0.67° grid (dx ~ 50 km), providing global mesoscale coverage, and has good skill at replicating diurnal, synoptic, and seasonal variations over vegetated land surfaces. It is driven by meteorological output from the NASA Goddard EOS Data Assimilation System. Surface weather from the system drives calculations of terrestrial ecosystem metabolism (radiation, precipitation, humidity, temperature) and air-sea gas exchange (wind), with other input data coming from satellite data products. Simulated spatial patterns and seasonal variations of simulated and observed column CO2 exhibit broad agreement, but some offsets in latitude and seasonal variations are noted. These are attributed to both model and satellite retrieval errors.
  • I. Shiach · I. T. Baker · A. Denning
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    ABSTRACT: The response of terrestrial fluxes of energy, water, and carbon to drought is evaluated. Major droughts should be clearly evident in reanalyzed precipitation data, although this is not always the case. With reduced precipitation we can expect a suppression in Gross Primary Photosynthesis (GPP) if physiological stress is sufficient, with atttendant changes in energy partitioning due to stomatal closure. There may also be a response in respiratory release of CO2 with temperature increase. This study aimed to investigate the behavior of the terrestrial biosphere using the Simple Biosphere Model (SiB3) during and following times of drought and to identify any model responses inconsistent with observational relationships. The Standardized Precipitation Index (SPI) was evaluated from 1983 to 2006 in order to evaluate historical drought maps, and to facilitate a qualitative analysis of modeled drought behavior. Standardized and raw anomaly maps were produced for modeled physiological variables (GPP, transpiration, respiration, heat fluxes, carbon flux, and stress factors) in order to determine general response patterns for comparison with observations. The SiB model was determined to be generally accurate in its representation of significant drought, with regard to perturbations in Bowen ratio, GPP, and CO2 respiration. However, model response was heterogeneous, and did not always respond in a manner consistent with published descriptions of drought.
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    ABSTRACT: Carbonyl sulfide (OCS) is an atmospheric trace gas that is taken up by leaves in parallel with photosynthetic uptake of CO2 (GPP). The latter is an important component of carbon cycle models and accurate measurements of photosynthesis are needed to test these models. However, it is difficult to obtain this information from atmospheric measurements of CO2 as air depleted of CO2 by GPP mixes very near the surface with air enriched in CO2 by respiration. Gradients in CO2, thus reflect the net sum of these two processes. In contrast, there is essentially no source of OCS in terrestrial ecosystems. The primary source of OCS is the oceans, thus mixing between this source and the photosynthetic sink occurs in the more remote atmosphere. This has led several researchers to postulate that gradients or time dependent changes in the concentration of OCS in air masses in contact with continental surfaces might be used to infer the rate of GPP of these surfaces. Several recent studies support this inference. However, it is important to note that these observations occur in a global context. The magnitude, spatial distribution and temporal dynamics of OCS sources and sinks are still poorly defined. This presentation will review recent efforts to improve our representation of the global cycle of OCS. We summarize new physiological measurements of exchange of OCS and CO2 by leaves including a wide range of species and environmental conditions, and report a new parameterization for OCS uptake for SiB3. We use these new simulations of surface exchanges in an atmospheric transport model, PCTM to simulate the concentration of OCS at points and times corresponding to flask measurements. While there remain important uncertainties about soil uptake and the ocean source, these simulations agree fairly well with observations.
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    ABSTRACT: Global carbon and water cycles are inextricably linked through photosynthesis and the nexus between these two biogeochemical cycles is stomatal conductance. It is estimated that approximately 35,000 Pg H20 and 360 Pg C pass through stomates annually. Thus, understanding how stomatal conductance responds to concomitant increases in atmospheric CO2, surface temperatures, and atmospheric water vapor is critical for constraining climate predictions. First, we use a global dataset of atmospheric CO2 isotopes (13CO2) to demonstrate that over the growth season source 13CO2 to the atmosphere varies in response to stomatal conductance. We then test two commonly-used stomatal conductance functions, based on relative humidity and vapor pressure deficit (VPD). We determine that the VPD-based function is better at predicting stomatal conductance on a global scale. Lastly, we use an ensemble of model simulations to predict stomatal conductance in response to increasing temperatures. What we discovered, is that relative humidity will remain constant, but vapor pressure deficit will increase significantly. Therefore future increases in vapor pressure deficit may greatly curtail the amount of carbon assimilated and water transpired by the terrestrial biosphere, resulting in a positive climate-carbon feedback.