Demonstrator systems for using remote sensing data (LAI, VOD, SIF) in online global prior fluxes for the CO2MVS prototype - Météo-France Accéder directement au contenu
Rapport Année : 2023

Demonstrator systems for using remote sensing data (LAI, VOD, SIF) in online global prior fluxes for the CO2MVS prototype

Résumé

The purpose of this work is to ingest satellite observations of leaf area index (LAI), microwave vegetation optical depth (VOD), and solar induced fluorescence (SIF) to constrain the terrestrial biogenic carbon uptake. Numerical experiments performed by 4 modelling approaches (ISBA, ECLand, ORCHIDEE, SDBM) are compared. ISBA and ECLand use an LDAS approach to perform a sequential assimilation of satellite observations to analyse model state variables, ORCHIDEE uses satellite data to optimize the value of model parameters, SDBM is directly driven by satellite FAPAR. The VOD assimilation is evaluated using ISBA and ECLand. The consistency of SIF with LAI and gross primary production (GPP) is evaluated using ISBA. Global FLUXCOM-V2 GPP estimates are used to benchmark models.
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Dates et versions

meteo-04541420 , version 1 (10-04-2024)

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  • HAL Id : meteo-04541420 , version 1

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Jean-Christophe Calvet, Bertrand Bonan, Oscar Rojas- Munoz, Anna Agusti-Panareda, Patricia de Rosnay, et al.. Demonstrator systems for using remote sensing data (LAI, VOD, SIF) in online global prior fluxes for the CO2MVS prototype. ECMWF. 2023. ⟨meteo-04541420⟩
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