[en] In the framework of the EUMETSAT Land Surface Analysis (LSA) - Satellite Application Facility (SAF),
models have been developed to retrieve from the MSG SEVIRI imager, surface variables like albedo,
short- and long-wave radiation fluxes and vegetation parameters (Leaf Area Index, LAI, and Fraction of
Vegetation Cover, FVC). An energy balance model is also being elaborated to produce actual
evapotranspiration (ET) estimates as one of the end products of the LSA-SAF. The model is a simplified
Soil-Vegetation-Atmosphere (SVAT) scheme adopting the tile approach, i.e. a sub-pixel computation of
surface fluxes. The atmospheric forcings are 30 minutes full spatial resolution MSG derived surface
radiative fluxes complemented by the ECMWF screen-level meteorological variables (air temperature
and humidity, wind speed, …). Important factors that strongly influence ET estimates are the time-
dependent vegetation characteristics. In SVAT schemes, the influence of vegetation on energy partition
is parameterized using key phenological factors, such as FVC and LAI. While some models use fixed
vegetation characteristics during the whole year, others take advantage of a finer temporal sampling of
vegetation evolution up to a couple of days. This contribution will first present the chosen way to use
remote sensed daily vegetation parameters derived from SEVIRI in the LSA-SAF ET model. Secondly,
we will show how the partitioning of surface heat fluxes is improved when using a finer characterization
of vegetation both spatially and temporally. At last, we will present the impact of remotely sensed
vegetation parameters uncertainty on the LSA-SAF ET model outputs.
