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Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13°C 12°C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball-Berry stomatal conductance slope (mbb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised mbb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. This study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.

Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. We distinguished between isotopic behavior in response to a decrease of δ13C within atmospheric CO2 (Suess effect) vs. photosynthetic discrimination (Δcanopy), by creating a site-customized atmospheric CO2 and δ13C of CO2 time series. We implemented a seasonally varying Vcmax model calibration that best matched site observations of net CO2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ13C of needle and stem tissue, but underestimated the δ13C of bulk soil carbon by 1-2%. The model overestimated the multiyear (2006-2012) average Δcanopy relative to prior data-based estimates by 2-4%. The amplitude of the average seasonal cycle of Δcanopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled An - gs (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled An - gs version used in the default model. The model attributed most of the seasonal variation in discrimination to An, whereas interannual variation in simulated Δcanopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10% increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.

When estimating fossil fuel carbon dioxide (FFCO2) emissions from observed CO2 concentrations, the accuracy can be hampered by biogenic carbon exchanges during the growing season even for urban areas where strong fossil fuel emissions are found. While biogenic carbon fluxes have been studied extensively across natural vegetation types, biogenic carbon fluxes within an urban area have been challenging to quantify due to limited observations and differences between urban versus rural regions. Here we developed a simple model representation, i.e., Solar-Induced Fluorescence (SIF) for Modeling Urban biogenic Fluxes ("SMUrF"), that estimates the gross primary production (GPP) and ecosystem respiration (Reco) over cities around the globe. Specifically, we leveraged space-based SIF, machine learning, eddy-covariance flux data, and additional remote sensing-based products, and developed algorithms to gap fill fluxes for urban areas. Grid-level hourly mean net ecosystem exchange (NEE) are extracted from SMUrF and evaluated against 1) non-gapfilled measurements at 67 eddy-covariance (EC) sites from FLUXNET during 2010-2014 (r > 0.7 for most data-rich biomes), 2) independent observations at two urban vegetation and two crop EC sites over Indianapolis from Aug 2017 to Dec 2018 (r = 0.75), and 3) an urban biospheric model based on fine-grained land cover classification within Los Angeles (r = 0.83). Moreover, we compared SMUrF-based NEE with inventory-based FFCO2 emissions over 40 cities and addressed the urban-rural contrast regarding both the magnitude and timing of CO2 fluxes. By examining a few summertime satellite tracks over four cities, we found that the urban-rural gradient in column CO2 (XCO2) anomalies due to NEE can sometimes reach ~ 0.5 ppm and be close to XCO2 enhancements due to FFCO2 emissions. With rapid advances in space-based measurements and increased sampling of SIF and CO2 measurements over urban areas, SMUrF can be useful for informing the biogenic CO2 fluxes over highly vegetated regions during the growing season. [ABSTRACT FROM AUTHOR]

Summer droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem drought response in land models is critical for predicting carbon dynamics. The goal of this study was to assess the performance of the Community Land Model, Version 4.5 (CLM) for an old-growth coniferous forest in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a climate that has heavy winter precipitation followed by summer drought. Particular attention was given to the model skill in the simulation of stomatal conductance and its response to drought stress. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected on reduced 13C:12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic drought stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit and soil water content, reasonably capturing the impact of drought stress on ecosystem functioning. The calibrated parameters may be of use for future modeling studies involving stands of similar age and composition under a similar climate regime. More broadly, the calibration of the Ball-Berry stomatal conductance model in CLM aligned with observations reported in the literature for coniferous trees, suggesting that a future release of CLM would benefit from using a distinct, lower slope value (mbb=6) for conifers, rather than a unique value for all C3 plants (mbb=9). Thanks to the recent implementation of photosynthetic 13C discrimination within CLM, the results of this study indicate that carbon isotope measurements can be used to constrain stomatal conductance and water use efficiency in CLM as an alternative to flux observations. They also have the potential to guide structural improvements in the model in respect to the representation of carbon storage pools. [ABSTRACT FROM AUTHOR]