Use of a global land data assimilation system (LDAS-Monde) to produce theroot-zone soil moisture essentialclimate variable

In order to estimate evapotranspiration in the region, we mapped the spatial vari- ability of LAI and agricultural practices and used them as input data into two model types: a)

Due  to  the  fast  evolution  of  ocean  models  during  the  past  20  years,  thanks  mainly  to  computer  power  increases,  the  flexibility  of  «

Three configurations corre- sponding to contrasted model errors are considered: (1) best case (BC) simulation with locally observed atmospheric vari- ables and model parameters,

Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates... Global

(points) and the model initial estimations (solid line). Analysis of a) root zone soil moisture and, b) vegetation biomass, using the simplified 32. 1D-VAR method for 2001 to

For soil moisture in near- surface layers (4–20 cm depth), analysis increments are sim- ilar for both approaches, but EnSRF estimates tend to be wetter especially for arid places due

Main soil and vegetation parameters used for the SMOSREX grassland in the ISBA-A-gs model, for the best case (i.e. specific atmospheric forcing, soil and vegetation parameters

In this study we present a carbon cycle data as- similation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer