www.elsevier.com/locate/sna Influence of Land Surface Parameters and Atmosphere on METEOSAT Brightness Temperatures and Generation of Land Surface Temperature Maps by Temporally and Spatially Interpolating Atmospheric Correction S. Scha ¨dlich,* F. M. Go ¨ ttsche,* and F.-S. Olesen* Tendencies toward desertification or changes of the land INTRODUCTION surface can be detected by monitoring land surface temper- Land degradation as a consequence of desertification is a ature (LST), but accurate retrievals require good knowl- major problem of “Global Change.” Remote sensing tech- edge of the atmosphere and land surface parameters. Here, niques provide an overview on a large spatial scale. Long- the effect of land surface emissivity, LST, and ground height term change detection studies are needed for periods on the error of LST associated with atmospheric correction longer than the fluctuations of the land/ocean-atmosphere is modeled for the thermal infrared (TIR) channel of MET- system [e.g., the El Nin ˜ o Southern Oscillation (ENSO) EOSAT using MODTRAN. The atmospheric conditions of or the North Atlantic Oscillation (NAO)]. Data from the midlatitude summer (MLS) and midlatitude winter (MLW) geostationary METEOSAT series have been available for are considered. The results confirm that for accurate atmo- approximately 20 years. This time interval is still too short spheric corrections temperature and height variations have for investigations of climatic fluctuations, but fluctuations to be extended by an emissivity variation. LST maps for on the time scale of ENSO or NAO events could be sepa- larger areas are generated using atmospheric corrections rated from the long-term trends of aridification and deserti- derived from ECMWF reanalysis and Digital Elevation fication. Measurements of polar orbiting and geostationary Model (DEM) data. The corrections are spatially and tem- satellites will be continued until at least 2012 [e.g., mea- porally interpolated using Shepards’ method and a model surements of European sensors (METEOSAT Second of the diurnal LST wave, respectively. The interpolations Generation MSG, EUMETSAT Polar System EPS) and allow the generation of spatially smooth LST maps for any of U.S. sensors (Geostationary Operational Environmental time of the day. Modeling the diurnal wave can partially Satellite GOES, National Polar-Orbiting Operational Envi- compensate for the adverse effect of cloudiness and radio- ronmental Satellite System NPOESS)]. metric noise. Elsevier Science Inc., 2001 Much experience with desertification processes was gained during field experiments, such as EFEDA (Bolle et al., 1993), which focused on the coupling between sur- face and atmosphere and investigated relationships be- tween remotely sensed quantities and characteristics of the land surface. * Institut fu ¨ r Meteorologie und Klimaforschung, Universita ¨t Karls- Only remote sensing can supply the long-term and ruhe/Forschungszentrum Karlsruhe, Germany large-scale observations needed to detect desertification. Address correspondence to S. Scha ¨ dlich, Universita ¨t Karlsruhe/ Forschungszentrum Karlsruhe, Institut fu ¨ r Meteorologie und Klima- Tendencies toward desertification or changes of the land forschung, Postfach 3640, 76021 Karlsruhe, Germany. E-mail: stephan. surface can be detected early by monitoring various surface schaedlich@imk.fzk.de Received 9 August 1999; revised 7 June 2000. parameters. One key parameter is the change of the diurnal REMOTE SENS. ENVIRON. 75:39–46 (2001) Elsevier Science Inc., 2001 0034-4257/00/$–see front matter 655 Avenue of the Americas, New York, NY 10010 PII S0034-4257(00)00154-1