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[1] The satellite application facility on land surface analysis (Land SAF) generates, archives, and disseminates land surface temperature (LST) in an operational basis. LST is estimated from the spinning enhanced visible and infrared imager (SEVIRI) onboard Meteosat, making use of a generalized split-windows algorithm. Here SEVIRI LST is compared with retrievals from the moderate resolution imaging spectroradiometer (MODIS), collocated in space and time, for three 10°Â 10°areas (Iberian Peninsula, Central Africa, and the Kalahari), and for six 7-day periods between July 2005 and May 2006. Overall, SEVIRI LSTs are warmer than MODIS values, with maximum discrepancies generally observed for daytime. The mismatches between the two satellite retrievals are then analyzed in terms of (1) satellite viewing angle differences, (2) surface orography, and (3) surface type. Daytime discrepancies are strongly impacted by differential heating rates of elements within a pixel (e.g., vegetation types, bareground), leading to a relatively wide range of MODIS-SEVIRI LST differences, with strong dependency on the MODIS view zenith angle. In contrast, average nighttime discrepancies are generally below 2°C. The intercomparison between MODIS and SEVIRI LST is complemented with in situ observations taken at Evora ground station (southwestern part of the Iberian Peninsula). The differences between ground and satellite-derived values show high variability for daytime for both sensors, with a systematic overestimation of in situ values by SEVIRI LST. In the case of nighttime observations, both sensors tend to underestimate local measurements, with estimated bias over all events under study of À1.7°C and À2.6°C for SEVIRI and MODIS LST, respectively.

Information on land surface properties finds applications in a range of areas related to weather forecasting, environmental research, hazard management and climate monitoring. Remotely sensed observations yield the only means of supplying land surface information with adequate time sampling and a wide spatial coverage. The aim of the Satellite Application Facility for Land Surface Analysis (Land-SAF) is to take full advantage of remotely sensed data to support land, land-atmosphere and biosphere applications, with emphasis on the development and implementation of algorithms that allow operational use of data from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors. This article provides an overview of the Land-SAF, with brief descriptions of algorithms and validation results. The set of parameters currently estimated and disseminated by the Land-SAF consists of three main groups: (i) the surface radiation budget, including albedo, land surface temperature, and downward short-and longwave fluxes; (ii) the surface water budget (snow cover and evapotranspiration); and (iii) vegetation and wild-fire parameters.

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