Multivariate probability matching of satellite infrared and microwave radiometric measurements for rainfall retrieval at the geostationary scale

The objective of this paper is to investigate how the synergy between low-earth-orbit (LEO) microwave (MW) and geostationary earth orbit (GEO) infrared (IR) radiometric measurements can be exploited for satellite rainfall detection and estimation. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is, at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The basic idea behind the investigated statistical integration methods follows an established approach consisting in using the satellite MW-based rain-rate estimates, assumed to be sufficiently accurate, to calibrate spaceborne IR measurements on limited sub-regions and time windows. The proposed methodology is focused on a new statistical approach, namely the multivariate probability matching (MPM). The MPM method is rigorously formulated and systematically analyzed in terms of relative detection and estimation accuracy.