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Severe droughts in the Northern Hemisphere cause widespread decline of agricultural yield, reduction of forest carbon uptake, and increased CO2 growth rates in the atmosphere. Plants respond to droughts by partially closing their stomata to limit their evaporative water loss, at the expense of carbon uptake by photosynthesis. This trade-off maximizes their water-use efficiency, as measured for many individual plants under laboratory conditions and field experiments. Here we analyze the 13C/12C stable isotope ratio in atmospheric CO2 (reported as δ13C) to provide new observational evidence of the impact of droughts on the water-use efficiency across areas of millions of km2 and spanning one decade of recent climate variability. We find strong and spatially coherent increases in water-use efficiency along with widespread reductions of net carbon uptake over the Northern Hemisphere during severe droughts that affected Europe, Russia, and the United States in 2001-2011. The impact of those droughts on water-use efficiency and carbon uptake by vegetation is substantially larger than simulated by the land-surface schemes of six state-of-the-art climate models. This suggests that drought induced carbon-climate feedbacks may be too small in these models and improvements to their vegetation dynamics using stable isotope observations can help to improve their drought response.

Abstract. 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.

Traditional methods of carbon monitoring in mountainous regions are challenged by complex terrain. Recently, solar‐induced fluorescence (SIF) has been found to be an indicator of gross primary production (GPP), and the increased availability of remotely sensed SIF provides an opportunity to estimate GPP across the Western United States. Although the empirical linkage between SIF and GPP is strong, the current mechanistic understanding of this linkage is incomplete and depends upon changes in leaf biochemical processes in which absorbed sunlight leads to photochemistry, heat (via nonphotochemical quenching [NPQ]), fluorescence, or tissue damage. An improved mechanistic understanding is necessary to leverage SIF observations to improve representation of ecosystem processes within land surface models. Here we included an improved fluorescence model within the Community Land Model, Version 4.5 (CLM 4.5), to simulate seasonal changes in SIF at a subalpine forest in Colorado. We found that when the model accounted for sustained NPQ, this provided a larger seasonal change in fluorescence yield leading to simulated SIF that more closely resembled the observed seasonal pattern (Global Ozone Monitoring Experiment‐2 [GOME‐2] satellite platform and a tower‐mounted spectrometer system). We found that an acclimation model based on mean air temperature was a useful predictor for sustained NPQ. Although light intensity was not an important factor for this analysis, it should be considered before applying the sustained NPQ and SIF to other cold climate evergreen biomes. More leaf‐level fluorescence measurements are necessary to better understand the seasonal relationship between sustained and reversible components of NPQ and to what extent that influences SIF.

Abstract. 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 13 C 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 (m bb ) 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 m bb 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.

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Abstract. The interpretation of flux measurements in nocturnal conditions is typically fraught with challenges. This paper reports on how the presence of wave-like disturbances in a time series, can lead to an overestimation of turbulence statistics, errors when calculating the stability parameter, erroneous estimation of the friction velocity u * used to screen flux data, and errors in turbulent flux calculations. Using time series of the pressure signal from a microbarograph, wavelike disturbances at an AmeriFlux site are identified. The wave-like disturbances are removed during the calculation of turbulence statistics and turbulent fluxes. Our findings suggest that filtering eddy-covariance data in the presence of wave-like events prevents both an overestimation of turbulence statistics and errors in turbulent flux calculations. Results show that large-amplitude wave-like events, events surpassing three standard deviations, occurred on 18 % of the nights considered in the present study. Remarkably, on flux towers located in a very stably stratified boundary-layer regime, the presence of a gravity wave can enhance turbulence statistics more than 50 %. In addition, the presence of the disturbance modulates the calculated turbulent fluxes of CO 2 resulting in erroneous turbulent flux calculations of the order of 10 % depending on averaging time and pressure perturbation threshold criteria. Furthermore, the friction velocity u * was affected by the presence of the wave, and in at least one case, a 10 % increase caused u * to exceed the arbitrary 0.25 m s −1 threshold used in many studies. This results in an unintended bias in the data selected for analysis in the flux calculations. The impact of different averaging periods was also examined and found to be variable specific. These early case study results provide an insight into errors introduced when calculating "purely" turbulent fluxes. These results could contribute to improving modeling efforts by providing more accurate inputs of both turbulent kinetic energy, and isolating the turbulent component of u * for flux selection in the stable nocturnal boundary layer.