Joint Assimilation of Surface Soil Moisture and Lai 2 Observations into a Land Surface Model 3 4

9 10 11 ABSTRACT 12 Land Surface Models (LSM) offer a description of land surface processes and set the 13 lower boundary conditions for meteorological models. In particular the accurate description of 14 those surface variables which display a slow response in time, like root zone soil moisture or 15 vegetation biomass, is of great importance. Errors in their estimation yield significant 16 inaccuracies in the estimation of heat and water fluxes in Numerical Weather Prediction 17 (NWP) models. In the present study, the ISBA-A-g s LSM is used decoupled from the 18 atmosphere. In this configuration, the model is able to simulate the vegetation growth, and 19 consequently LAI. A simplified 1D-VAR assimilation method is applied to observed surface 20 soil moisture and LAI observations of the SMOSREX site near Toulouse, in southwestern 21 France, from 2001 to 2004. This period includes severe droughts in 2003 and 2004. The data 22 are jointly assimilated into ISBA-A-g s in order to analyse the root zone soil moisture and the 23 vegetation biomass. It is shown that the 1D-VAR improves the model results. The efficiency 24 score of the model (Nash criterion) is increased from 0.79 to 0.86 for root-zone soil moisture 25 and from 0.17 to 0.23 for vegetation biomass.