Assessing JULES across bioclimatic domains through a Pan-African flux tower evaluation: insights into controls on gross primary productivity, ecosystem respiration, and evapotranspiration biases

Land surface models are fundamental for simulating coupled carbon, water and energy exchanges in Earth system models, yet their performance remains poorly constrained across Africa's diverse hydroclimatic gradients. We evaluate the Joint UK Land Environment Simulator (JULES) using eddy covariance observations from 16 flux towers spanning major African ecosystem types. Model skill is assessed for gross primary productivity (GPP), ecosystem respiration (Reco), and evapotranspiration, and we examine how model bias and error vary along gradients of mean annual temperature, aridity index, and precipitation anomalies. JULES reproduced broad seasonal dynamics of carbon and water fluxes across several ecosystems but showed systematic limitations in simulating Reco and interannual variability of GPP. Model performance differed among ecosystem types, with wetlands exhibiting large model-observation mismatches and cropland sites showing GPP overestimation linked to excessive simulated leaf area index. To isolate environmental controls on performance, we applied linear mixed-effects modeling to partition site-level variability from climate-driven effects. Aridity and precipitation anomalies emerged as dominant predictors of model bias and error, with wetter and anomalously humid conditions associated with larger deviations from observations, indicating limitations in representing soil hydrology and vegetation water stress processes. By integrating an expanded African flux tower network, this study provides a comprehensive regional evaluation of JULES. The results identify hydroclimatic regimes where model development should be prioritized and emphasize the importance of strengthening benchmarking across underrepresented African ecosystems to improve model transferability and support reliable climate and land management decision support under environmental change.