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Inter–Annual Variability of Model Parameters Improves Simulation of Annual Gross Primary Production

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 p...

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Asıl Yazarlar: Ranit De, Alexander Brenning, Markus Reichstein, Ladislav Šigut, Borja Ruiz Reverter, Mika Korkiakoski, Eugénie Paul‐Limoges, Peter D. Blanken, T. Andrew Black, Bert Gielen, Torbern Tagesson, Georg Wohlfahrt, Leonardo Montagnani, Sebastian Wolf, Jiquan Chen, Michael Liddell, Ankur R. Desai, Sujan Koirala, Nuno Carvalhais
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: American Geophysical Union (AGU) 2026-06-01
Seri Bilgileri:Journal of Advances in Modeling Earth Systems
Konular:
parameter variability
interannual variability
gross primary productivity
optimality Moel
light use efficiency
temporally varying parameters
Online Erişim:https://doi.org/10.1029/2025MS005116
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