Assimilation of Leaf Area Index and Soil Water Index from Satellite Observations in a Land Surface Model in Hungary

In this study, a Land Data Assimilation System (LDAS) is applied over the Carpathian Basin at Hungarian Meteorological Service to monitor above-ground biomass, surface fluxes (carbon and water), associated root-zone soil moisture regional scale (spatial resolution of 8 km × km) in quasi-real-time. system SURFEX model used, which applies vegetation growth version Interactions between Soil, Biosphere Atmosphere (ISBA-A-gs) photosynthesis scheme describe evolution vegetation. forced using outputs ALADIN numerical weather prediction run operationally Service. First, an open-loop (i.e., no assimilation) mode for period 2008–2015. Secondly, Extended Kalman Filter (EKF) method used assimilate Leaf Area Index (LAI) Spot/Vegetation (until May 2014) PROBA-V (from June Soil Water (SWI) ASCAT/Metop satellite measurements. The benefit LDAS proved whole country selected site West Hungary (Hegyhátsál). It demonstrated that EKF can provide useful information both wet dry seasons as well. shown data assimilation efficient inter-annual variability biomass values. development water carbon vary from season capable tool these parameters.