A Pattern Recognition Technique for Retrieving Humidity Profiles from Meteosat or GOES Imagery

Abstract

A retrieval technique based on cloud classification is designed to derive humidity profiles from Meteosat visible (VIS), infrared window (IR), and water vapor (WV) channels, or equivalent sensors available on other satellites. Dewpoint depression (DPD) is the variable retrieved at six standard levels: 1000, 850, 700, 500, 400, and 300 mb. Collocation of soundings and Meteosal-2 imagery was obtained over Europe for March, June, and July 1988. Results are derived from over 2000 dependent and 1000 independent samples. It is found that a classification in seven (IR only) or nine (VIS-IR) classes contains the essential information on cloud type for the application sought. Measures were extracted from approximately 8-km pixel resolution images on 80-km ? 80-km and 160-km ? 160-km arm, little dependency on horizontal scale was found for the mean humidity profiles associated with each cloud class. The WV channel proved very useful in improving DPDs at higher levels while the VIS channel improved inferences of low-level humidity in classes associated with precipitation. Overall DPD errors range from 3 to 5 K rms depending on level; this corresponds to 13%?20% rms in terms of relative humidity and to approximately 4.4 mm rms in terms of total precipitable water. The three GOES-7 channels closest to Meteosal-2 VIS, IR, and WV channels were used to extend the study to the tropics and to the winter season from data collected in 1991 and 1992. The main advantages of the technique are its applicability to cloudy atmospheres, its robustness and the fact that it can efficiently provide retrievals from 60°S to 60;deg;N every half-hour.