Joint Temperature, Humidity, and Sea Surface Temperature Retrieval from IASI Sensor Data

We discuss a joint retrieval algorithm of temperature, humidity, ozone, and sea surface tem- perature (SST; more precisely, this is the surface skin temperature of the ocean) for the IASI (Infrared Atmospheric Sounding Interferometer) instrument. The algorithm is based on optimal estimation methodology and was carefully tested under realistic conditions (using high resolution ECMWF analysis fields). The algorithm contains in a first step an effective and fast channel selection method based on information content theory, which leads to a reduction of the total number of IASI channels ( 8400) to about 3 % only ( 250), which are subsequently used in the retrieval processing. We show that this reduction is possible without significant decrease in performance compared to using many more (order 2000) channels. The clearly improved performance of the joint algorithm compared to more spe- cific retrieval setups is exemplified as well. Finally, the application of the algorithm to AIRS (Advanced Infrared Sounder) data, a next step planned, is addressed.