Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite
Ghilain, N × Arboleda, A Sepulcre-Cantò, G Batelaan, Okke Ardö, J Gellens-Meulenberghs, F #
European Geophysical Society
Hydrology and Earth System Sciences vol:16 issue:8 pages:2567-2583
Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations
from land surface models.
The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data.
The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG) and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF) are particularly interesting for such applications,as they aimed at providing continuous and consistent
daily time series in near-real time over Africa, Europe
and South America. In this paper, we compare them to
monthly vegetation parameters from a database commonly
used in numerical weather predictions (ECOCLIMAP-I),
showing the benefits of the new daily products in detecting
the spatial and temporal (seasonal and inter-annual) variability
of the vegetation, especially relevant over Africa.We propose
a method to handle Leaf Area Index (LAI) and Fractional
Vegetation Cover (FVC) products for evapotranspiration
monitoring with a land surface model at 3–5 km spatial
resolution. The method is conceived to be applicable for
near-real time processes at continental scale and relies on the
use of a land cover map.We assess the impact of using LSASAF
biophysical variables compared to ECOCLIMAP-I on
evapotranspiration estimated by the land surface model HTESSEL.
Comparison with in-situ observations in Europe
and Africa shows an improved estimation of the evapotranspiration,
especially in semi-arid climates. Finally, the impact
on the land surface modelled evapotranspiration is compared
over a north–south transect with a large gradient of vegetation
and climate inWestern Africa using LSA-SAF radiation
forcing derived from remote sensing. Differences are highlighted.
An evaluation against remote sensing derived land
surface temperature shows an improvement of the evapotranspiration