Determination of Rainfall Rates from GOES Satellite Images by a Pattern Recognition Technique

Abstract

Abstract Radiances from clouds observed in visible and infrared images obtained from the SMS-2, GOES-2, and GOES-4 satellites have been used to estimate rainfall by means of a pattern recognition algorithm that was applied to single images. The algorithm classified rain into three classes: 0—no rain (0 ≤ R <0.5 mm h−1); 1—light rain (0.5 ≤ R <0.5 mm h−1); and 2—heavy rain (5.0 mm h−1≤ R). The rainfall rates used in the training set and those used to test the algorithm were derived from a set of twenty-nine Plan Position Indicator (PPI) displays obtained from NOAA operational radars. Data were derived from summer storms, tropical storms and cyclones. Rainfall from precipitating clouds was classified by a pattern recognition technique that used textural and radiance features in a hierarchic decision tree. The analysis was applied to regions 20 × 20 km in area that were measured in the visible spectral region with 1 × 1 km and 2 × 2 km resolution and in the infrared with 4 × 8 km resolution. The radiance fea...