Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

Bio-physical variables; Continental scale; Daily evapotranspirations; Fractional vegetation cover; In-situ observations; Interannual; Land cover; Land surface; Land surface analysis; Land surface models; Land surface temperature; Leaf Area Index; Meteosat second generations; Near-real time; Numerical weather prediction; Radiation forcing; Satellite application facilities; Semi-arid climate; South America; Spatial resolution; Vegetation dynamics; Vegetation parameters; Water Science and Technology; Earth and Planetary Sciences (miscellaneous)

Abstract :

[en] 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 LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. 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 in Western 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 simulations. © 2012 Author(s).

Disciplines :

Earth sciences & physical geography

Author, co-author :

Ghilain, Nicolas ; Université de Liège - ULiège > Sphères ; Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium

Arboleda, A.; Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium

Sepulcre-Cantò, G.; Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium ; Institute for Environment and Sustainability, Joint Research Center, Ispra, Italy

Batelaan, O.; Dept. of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, 1050 Brussels, Belgium ; Dept. Earth and Environmental Sciences, Katholieke Universiteit Leuven, 3001 Heverlee, Belgium

Ardö, J.; Dept. Physical Geography and Ecosystems Analysis, Lund University, 223 62 Lund, Sweden

Gellens-Meulenberghs, F.; Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium

Language :

English

Title :

Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

Publication date :

26 November 2012

Journal title :

Hydrology and Earth System Sciences

ISSN :

1027-5606

eISSN :

1607-7938

Publisher :

Copernicus GmbH

Volume :

Issue :

Pages :

2567 - 2583

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://hess.copernicus.org/articles/16/2567/2012/hess-16-2567-2012.pdf

Available on ORBi :

since 20 February 2026

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