Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence

Seyed Hamed Alemohammad , Bin Fang (1) , Alexandra Konings , Filipe Aires (2) , Julia Green , Jana Kolassa , Diego Miralles , Catherine Prigent (2) , Pierre Gentine

1 IRIF (UMR_8243) - Institut de Recherche en Informatique Fondamentale
2 LERMA - Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique

Domaines: Physique [physics]; Astrophysique [astro-ph]

Seyed Hamed Alemohammad, Bin Fang, Alexandra Konings, Filipe Aires, Julia Green, et al.. Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence. Biogeosciences, 2017, 14 (18), pp.4101-4124. ⟨10.5194/bg-14-4101-2017⟩. ⟨hal-02194157⟩