An infrared rainfall estimation technique that includes information from a split window is developed. The split window refers to the difference in the brightness between the far infrared (IR) channels situated at around 10 µm and 12 µm, which has been used to estimate atmospheric water vapour and for rain area detection. The technique, called the Microwave calibrated Infrared Split-window Technique (MIST), can be considered an extension of the Adjusted GOES Precipitation Index (AGPI). IR rain rates are first estimated from an IR-rain rate relation derived from matching the monthly histograms of combined microwave rain estimates (3B40RT) produced by the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the infrared data observed from a geostationary satellite. The novelty is the inclusion of the split-window information to eliminate non-rainy pixels as a second step. The technique has been applied to Geostationary Meteorological Satellite (GMS) and Geostationary Operational Environmental Satellite (GOES) data and tested for a dry and a wet period. The results show that the MIST has comparable biases and better rain event detection skill than the TMPA, although the TMPA is constrained by the gauge analysis by design while the MIST has no direct gauge input.
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Document Type: Research Article
Institute of Space and Earth Information Science, Chinese University of Hong Kong, Shatin Hong Kong, China,Department of Geography and GeoInformation Science, George Mason University, Fairfax VA 22030, USA
Publication date: 2009-01-01
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