Articles | Volume 24, issue 9
https://doi.org/10.5194/hess-24-4291-2020
https://doi.org/10.5194/hess-24-4291-2020
Research article
 | 
02 Sep 2020
Research article |  | 02 Sep 2020

Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces

Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet

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Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
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