Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: a validation and inter-comparison study

A Kalman filter based approach for the physical retrieval of surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager) infrared observations has been developed and validated against in situ and satellite observations. Validation for land has been provided based on in situ observations from the two permanent stations Evora and Gobabeb operated by Karlsruhe Institute of Technology (KIT) within the framework of EUMETSAT's Satellite Application Facility on Land Surface Analysis (LSA-SAF). Sea surface retrievals have been intercompared on a broad spatial scale with equivalent satellite products (MODIS or Moderate Resolution Imaging Spectroradiometer and AVHRR or Advanced Very High Resolution Radiometer) and ECMWF (European Centre for Medium Range Weather Forecasts) analyses. Results show that for surface temperature the algorithm yields an accuracy of ≈ ± 1.5 °C in case of land and ≈ ± 1.0 °C in case of sea surface. Comparisons with polar satellite instruments over the sea surface show nearly zero temperature bias. Over the land surface the retrieved emissivity follows the seasonal vegetation cycle and allows to identify desert sand regions because of strong reststrahlen bands of Quartz in the SEVIRI channel at 8.7 μm. Considering the two validation stations, we have that emissivity retrieved in SEVIRI channel 10.8 μm over the gravel plains of the Namib desert is in excellent agreement with in situ observations. Over Evora, the seasonal variation of emissivity with vegetation is successfully retrieved and yields emissivity values for green and dry vegetation that are in good agreement with spectral library data. The algorithm has been applied to the SEVIRI full disk and emissivity maps on that global scale have been physically retrieved for the first time