Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: a validation and intercomparison study
- 1Scuola di Ingegneria, Università della Basilicata, Potenza, Italy
- 2Karlsruhe Institute of Technology (KIT), IMK-ASF, Karlsruhe, Germany
- 3Instituto Portugues do Mar e da Atmosfera IP, Land SAF, Lisbon, Portugal
- 4European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany
Abstract. 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 at 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, Moderate Resolution Imaging Spectroradiometer, and AVHRR, Advanced Very High Resolution Radiometer) and ECMWF (European Centre for Medium-Range Weather Forecasts) analyses. For surface temperature, the Kalman filter yields a root mean square accuracy of ≈ ±1.5 °C for the two land sites considered and ≈ ±1.0 °C for the sea. 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 permits identification of desert sand regions using the SEVIRI channel at 8.7 μm due to the strong quartz reststrahlen bands around 8–9 μm. Considering the two validation stations, we have found that emissivity retrieved in SEVIRI channel 10.8 μm over the gravel plains of the Namibian 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.