Inter–Annual Variability of Model Parameters Improves Simulation of Annual Gross Primary Production
Journal Article
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abstract
Abstract; ; Parametric uncertainty can hinder land surface models (LSM) from accurately simulating carbon fluxes, such as gross primary production (GPP). These models generally cannot capture inter–annual variability (IAV) of fluxes well due to missing processes, and temporally varying parameters can partially alleviate this limitation. We evaluated this assumption using two models: a light‐use efficiency (LUE) model with several environmental response functions, and an optimality‐based model that includes parameter acclimation and drought stress. De et al. (2025,; https://doi.org/10.1029/2024MS004697; ) concluded that calibrating all parameters per site–year improves annual performance. As a follow‐up, we now inverted parameters of each environmental response function annually at a time, while simultaneously estimating year‐invariant optima for all other parameters, applying this across 198 eddy‐covariance sites. The IAV of GPP in arid sites was substantially improved when hydrological parameters varied annually, both for herbaceous and forest ecosystems. However, for tropical, temperate and boreal sites, IAV improved from annual variation of parameters controlling the GPP responses to temperature, light or atmospheric dryness. Given the paucity of arid and semi‐arid sites, allowing year‐specific parameters for vapor pressure deficit and atmospheric carbon dioxide effects yielded an overall median annual normalized Nash‐Sutcliffe efficiency of 0.733. Re‐evaluating some experiments from De et al. (2025,; https://doi.org/10.1029/2024MS004697; ), we found that spatial variation of model parameters was higher than temporal variation, even though yearly varying parameters can improve annual performance. Our results challenge the existing perspective on temporally static parameterizations, reflecting the need to statistically learn temporal parameter variation from observations to improve IAV representation in LSMs.;
