Multivariate probability matching of satellite infrared and microwave radiometric measurements for rainfall retrieval at the geostationary scale
| Autor: | M. Palmacci, Francisco J. Tapiador, Frank S. Marzano, Domenico Cimini, J. Turk, Graziano Giuliani |
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| Rok vydání: | 2004 |
| Předmět: |
Multivariate statistics
Meteorology Probability matching Physics::Geophysics Physics::Space Physics Geostationary orbit Environmental science Radiometry Satellite Astrophysics::Earth and Planetary Astrophysics Scale (map) Image resolution Physics::Atmospheric and Oceanic Physics Microwave Remote sensing |
| Zdroj: | IGARSS Scopus-Elsevier |
| DOI: | 10.1109/igarss.2003.1294041 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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