Daily MSG Evapotranspiration (DMET, LSA-312)

NRT Product available since Dec 2010


Evapotranspiration (ET) accounts for the flux of water evaporated at the Earth-atmosphere interface (soil + vegetation + water bodies) and transpired by vegetation through stomata in its leaves as a consequence of photosynthetic processes. Evapotranspiration, plays a crucial role in the recycling of precipitation, in soil water availability and consequently on food production. Evapotranspiration is dependent mainly on the solar energy available to vaporize the water and in water content in the soil layers. Because of the dependence on solar energy, ET varies with latitude, season of year, time of day, and cloud cover.


Product Documentation

This operational product is documented in the following documents:

Please see Product Peer-Review publications in References.

The use of LSA SAF products in publications is kindly requested to be duly acknowledged:
ET and DMET were provided by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF; Trigo et al., 2011)

Trigo, I. F., C. C. DaCamara, P. Viterbo, J.-L. Roujean, F. Olesen, C. Barroso, F. Camacho-de Coca, D. Carrer, S. C. Freitas, J. García-Haro, B. Geiger, F. Gellens-Meulenberghs, N. Ghilain, J. Meliá, L. Pessanha, N. Siljamo, and A. Arboleda, 2011: The Satellite Application Facility on Land Surface Analysis. Int. J. Remote Sens., 32, 2725-2744, doi: 10.1080/01431161003743199

The evapotranspiration generated in the framework of the LSA SAF consortium consists of two outputs: the instantaneous ET product (MET) with a time interval of 30 minutes (in mm per hour) and the daily evapotranspiration product (DMET) obtained by integrating instantaneous values over the whole day (in mm per day). Both products are generated over the full MSG disc domain, covering Europe, Africa and most of South America at SEVIRI spatial resolution (3 km at sub satellite point). Together with the ET estimates, additional information about the quality of the estimation is provided. In the case of the MET product, the quality flag is calculated based on the quality of input variables, the algorithm performances and pre/post processing manipulations on the estimates. For DMET product, two additional images are provided: the first one contains information on the percentage of missing values for every pixel in the considered day and the second one provides information on the number of missing instantaneous images in the same day.


Algorithm Description

The methodology adopted for the ET product combines the advantages of geostationary satellite remote sensing (high repetition rate, wide area coverage, high spatial resolution) with the ability of a Soil Vegetation Atmosphere Transfer (SVAT) model to describe physical and physiological process occurring in vegetation canopy. In this approach, radiation components at the surface derived from Meteosat geostationary satellites together with recent land-cover information (from ECOCLIMAP land cover database) –for v1–, and in addition biophysical products and soil moisture status information (from land data assimilation system and land surface temperature) –for v2– and ancillary meteorological data (from ECMWF forecasts) are used to drive a physical model of energy exchange between the soil-vegetation-atmosphere systems. The scope of the method is limited to evaporation from terrestrial surfaces and inland water rather than from ocean surfaces. The ET product has been validated on different climatic and environmental conditions, providing evidence that the algorithm is able to produce ET estimates with accuracy equivalent to the accuracy of measurements, ie 20-25% for instantaneous retrieval (see validation report -VR-). The approach adopts the tile approach in which each model entity (pixel), is composed of a mix of homogeneous plant functional types (tiles), representing main land-coverage types (bare soil, grassland, crops, forests). The surface energy balance is solved for each tile separately, and the resulting pixel ET value is obtained as the weighted contribution of all tiles in the pixel.


Data Characteristics

The ET product output and accompanying quality flag, are stored on single files on HDF5 (Hierarchical Data Format, version 5) format. HDF5 is a machine independent standard for storing/sharing scientific data. In this format, each file contains also the necessary information for manipulating the data. For more information on this data format see https://www.hdfgroup.org/


Product Uncertainties

The main sources of uncertainties on the ET product come from: a) the physical formalism of the algorithm itself, b) from the errors associated with each input of the algorithm, in particular from other LSA-SAF components and c) from surface heterogeneity and land cover classification used in the algorithm. From a global point of view, most uncertainties cumulated on the ET results from sensors performance, accuracy of cloudy pixels identification, accuracy of atmospheric corrections which propagates into algorithms using this information, and providing input for the ET algorithm.



Evapotranspiration is an important component of the water cycle and it is associated with the latent heat flux (LE), a key link between the energy and water cycles.

Accurate measurements of evaporation rates at large spatial scales are central to understanding land and atmosphere interactions in the context of global warming. It is of great importance in disciplines like weather forecasting, water management, agriculture, hydrology, ecology and global climate monitoring.


Arboleda, A., Ghilain N., Gellens-Meulenberghs, F.: Continuous monitoring of evapotranspiration (ET): Overview of LSA-SAF evapotranspiration products” Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104210E; 11 – 14 September 2017 Warsaw, Poland; doi: 10.1117/12.2278249; https://doi.org/10.1117/12.2278249, 2017

Arboleda, A., Ghilain N., Trigo, I., Coelho, S., Martins, J. P., Gellens-Meulenberghs, F.: LSA-SAF evapotranspiration and surface heat flux products 2.0, poster. EUMETSAT Satellite conference 2017. 02-05 October 2017, Rome, Italy, 2017.

Ghilain, N.: Continental scale monitoring of subdaily and daily evapotranspiration enhanced by the assimilation of surface soil moisture derived from thermal infrared geostationary data, Chapter 16, p. 309-332, in Satellite Soil Moisture Retrieval Techniques and Applications, P.K. Srivastava, G. Petropoulos & Y.H. Kerr, edts, Elsevier Publisher, 2016.

Ghilain, N., Arboleda, A., and Gellens-Meulenberghs, F: Evapotranspiration modelling at large scale using near-real time MSG SEVIRI derived data, Hydrol. Earth Syst. Sci., 15, 771-786, doi: https://doi.org/10.5194/hess-15-771-2011, 2011.

Ghilain, N., Arboleda, A., Barrios, J., M. and Gellens-Meulenberghs, F.: LSA-SAF ET&SF – version 2: monitoring evapotranspiration & surface heat fluxes over entire continents at kilometer scale in near-real time thanks to satellite data. Abstract, EGU 2018, 8-13 April, Vienna, Austria, 2018.

Ghilain, N., Arboleda, A., Batelaan, O., Ardö, J., Trigo, I., Barrios, J. M. and Gellens-Meulenberghs, F., 2019: A new retrieval algorithm for soil moisture index from thermal infrared sensor on-board geostationary satellites over Europe and Africa and its validation. Remote Sensing, 11(17), 1968; https://doi.org/10.3390/rs11171968

Ghilain, N., Arboleda, A., Barrios, J. M. and Gellens-Meulenberghs, F., 2020: Water interception by canopies for remote sensing based evapotranspiration models. International Journal of Remote Sensing, 14(8), 2934-2945, DOI: https://doi.org/10.1080/01431161.2019.1698072

Martins, J. P. A., Trigo, I., Ghilain, N., Jimenez, C., Goettsche, F.-M., Ermida, S., Olesen, F., Gellens-Meulenberghs, F., Arboleda, A., 2019: An All-Weather Land Surface Temperature Product based on MSG/SEVIRI observations. Remote Sensing, 11, 3044, 28 pp.

Petropoulos G., Ireland, G., Lamine S., Griffiths H., Ghilain N., Anagnostopoulos V., North M., Srivastava P.K., Georgopoulou H.: Operational evapotranspiration estimates from SEVIRI in support of sustainable water management, Int J. Applied EO Geoinf, 30, 190-202, 2016.

Trigo, I. F., DaCamara, C. C., Viterbo, P., Roujean, J.-L., Olesen, F., Barroso, C., de Coca, F. C., Carrer, D., Freitas, S. C., Garcia-Haro, J., Geiger, B., Gellens-Meulenberghs, F., Ghilain, N., Melia, J., Pessanha, L., Siljamo, N., & Arboleda, A: The Satellite Application Facility on Land Surface Analysis, Int. J. Remote Sens., 32 , 2725-2744, 2011.