The Self-Calibrating multivariate precipitation retrieval (SCaMPR) for high-Resolution, low-latency satellite-Based rainfall estimates

Abstract

The Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) is an algorithm for retrieving rainfall rates using visible (VIS)/infrared (IR) and microwave-frequency data from Earth-orbiting satellites. Rainfall rates derived from microwave-frequency data are used as a calibration target for an algorithm framework that both selects the optimal VIS/IR predictors and determines their optimal calibration coefficients in real time. This algorithm is highly flexible and its short data latency makes it well-suited for rapidly-changing heavy rainfall situations that trigger flash flooding. © 2010 Springer Science+Business Media B.V.