Author Notes
In this work, we show the results of one of the very few physical-based approaches for the estimation of surface parameters from infrared instruments on board geostationary platforms. The approach has been developed for the infrared channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (MSG) geostationary platform and here has been applied to the region encompassing the Mediterranean, observed by more than 170000 SEVIRI pixels every 15 minutes, for the physical retrieval of the Sea Surface Temperature (SST). The methodology is based on a Kalman filter and enables simultaneous retrieval of surface emissivity and temperature from SEVIRI infrared radiance measurements using channels at 8.7, 10.8, and 12 µm. When run on a PC with a CPU clocked at 2.7GHz and 8GB of RAM, the processor needs about 0.002 s for each pixel to retrieve SST. So for the Mediterranean region, it takes about 7 minutes with a single CPU, i.e. this processor is ready for real-time computing for this region. We tested the processor by comparing its results with SST retrieved from the Advanced Very High Resolution Radiometer (AVHRR) satellite measurements. AVHRR and SEVIRI L2 SST show an excellent agreement with correlation coefficients larger than 0.99, with no bias and a root mean squared difference of less than 0.2 °C. Finally, this methodology shows that the Mediterranean Sea has warmed by four cents of Celsius per year in the last decade.
