The University of Karlsruhe (IMK) and EARS assess LST from geo-stationnary sensors data using different approaches to answer the requirements of Observatory Natural Carbon (ONC), which needs heating rate (i.e. gradient of LST from sunrise to noon) on a hourly basis, and of Observatory Food Security and Crop Monitoring (OFM), which uses LST in crop monitoring and yield forecasting studies.

LST derived from METEOSAT-7 data, August 2000.

IMK retrieves LST from METEOSAT thermal infrared channel images using a neural network (see example above). METEOSAT is the only satellite that provides infrared measurements over Africa and Europe that resolves the diurnal wave of LST. The disadvantage of METEOSAT is that only one infrared channel is available. Thus established LST determination methods like split-window technique can not be used and the atmospheric state can not be derived from METEOSAT data. The atmospheric situation (i.e. the temperature and moisture profiles) are taken from ECMWF analysis or re-analysis. The physics of the atmospheric correction of a single infrared channel is the following : calculate the expected satellite measurement for a reasonable range of land surface temperature, surface elevation and emissivity for the actual profiles and viewing angle - this constitutes the forward calculation of atmospheric radiances. The LST is then determined by interpolation of the actual satellite measurement (this is the inversion of the forward calculation) for profiles around the current pixel and horizontal interpolation of the atmospheric correction at the surrounding pixels. A neural network is used to speed-up this procedure. Its input are : the actual satellite measurement, the temperature and moisture profiles, the surface elevation and emissivity, as well as the viewing angle. The LST is not estimated for cloudy pixels. IMK has developed a cloud detection for the three spectral channels of METEOSAT based upon temporal development (bright surface is separated from clouds due to the duration) and sophisticated threshold techniques (IR thresholds for each slot are determined dynamically from several days up to a month, depending on the cloudiness). The resulting cloud mask is also used by CNRM/Météo-France for DSR retrieval and by the Institute of Meteorology of Portugal (IM) for DLR assessment.

The LST product is being currently processed at IM. At the end of the project (end 2006), it will cover the period 1999-2005, with a temporal resolution of 1/2 hour, over Europe and Africa. This product LST is available as it is following the production process. It can be downloaded with an algorithmic documentation (ATBD) and a technical documentation (readme).

EARS provides the Land Surface Temperature generated by the EWBMS (Energy Water Balance Monitoring System) from METEOSAT noon and midnight thermal infrared (10 - 13.1 µm) images, which yield, after calibration, the planetary noon and midnight temperature. These latter are converted to land surface temperatures by means of an atmospheric correction procedure. The atmospheric correction coefficient is determined using a reference within the image. The reference is obtained from the driest pixels, which have the highest planetary temperature over global radiation ratio. It is assumed that these pixels have zero evapotranspiration and thus sensible heat flux equals net radiation. For these pixels, the land surface temperature may then be calculated. The resulting pair of highest planetary and land surface temperature allows to calculate a first order atmospheric correction coefficient, which is then applied to all other pixels of the noon and midnight images. The average surface temperature is obtained by averaging the noon and midnight surface temperature.

To get the products provided by EARS, it is necessary to make a request at the address ears@ears.nl.