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Carbon, water and energy exchange between the land and atmosphere controls how ecosystems either accelerate or ameliorate the effect of climate change. However, evaluating improvements to processes controlling carbon cycling, water use and energy exchange in global land surface models (LSMs) remains challenging in part because of persistent model errors in estimating leaf area. Here we evaluate the changes in global carbon, water and energy exchange brought about when a LSM prognostic estimates of leaf area are made consistent with estimates from satellites. This approach achieves two aims; first to quantify the effect of ignoring errors in leaf area index (LAI) on land‐atmosphere fluxes and second, to evaluate how closely this LSM replicates fluxes with and without an LAI constraint. We implemented an ensemble Kalman filter with spatiotemporal adaptive inflation to more closely match community land model (CLM5.0) estimates of leaf area to those from the Global Inventory Modeling and Mapping Studies leaf area index (LAI3g) product. We then evaluate the model's estimates of gross primary productivity (GPP) and latent heat flux (LE) against well established global estimates of these fluxes. We find that the model is biased high by 27% relative to the LAI3g product. Moreover, the effect of bias in LAI is substantial for GPP (18%) and LE (6%) and likely to confound efforts to refine processes controlling these fluxes. This data assimilation approach serves as a method to evaluate the efficacy of refinements to flux processes until the processes controlling the dynamics of LAI are better resolved in LSMs.

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite‐derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above‐ground biomass. The adjusted simulation significantly reduced the above‐ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation‐constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon.

Climate‐driven woody vegetation mortality is a defining feature of semiarid biomes that drives fundamental changes in ecosystem structure. However, the observed impacts of woody mortality on ecosystem‐scale energy and water budgets and the responses of surviving vegetation are highly variable among studies in water‐limited environments. A previous girdling manipulation experiment in a piñon‐juniper woodland suggested that although ecosystem‐scale evapotranspiration was not altered by large‐scale piñon mortality, soil water content decreased and the surviving juniper experienced greater water stress than juniper in an undisturbed woodland. Here we experimentally explored to what extent mortality‐induced changes in energy balance components can explain these results. We compared energy fluxes measured above two adjacent piñon‐juniper woodlands where piñon girdling was implemented at one site and the other subsequently experienced large‐scale natural piñon mortality. We found that the mortality‐induced decrease in canopy area was not sufficient to alter surface reflectance, roughness, and partitioning between energy budget components at both sites. A radiative transfer model estimated that because of the sparse premortality canopy, surface reflectance is more sensitive to a large increase in understory leaf area than further loss of crown area. Increased water stress in the remaining juniper following both mortality events can be explained by an increase in radiation on the ground that promoted higher soil temperature and evaporation. We found similar responses of ecosystem and tree‐level functions to both girdling and natural mortality. This suggests that girdling is an appropriate approach to explore the impact of tree mortality on ecosystem structure, function, and energy balance.