Abstract
A combined Microwave/Infrared Rain Rate Algorithm (MIRRA) is presented. Historically, infrared algorithms have benefited from excellent temporal sampling, but the relationship between cloud top temperature and surface rain rate is very indirect. Alternatively, passive microwave algorithms are typically more physically direct and accurate, yet the associated sensors do not provide favourable temporal sampling for daily and monthly rainfall amounts. MIRRA is an attempt to utilize the strengths of these two broad approaches to rain rate measurement from space. The algorithm has been tested and developed using data from the TOGA-COARE campaign, with shipboard radar rain rate estimates used as truth. Results indicate enhanced performance in bias, correlation and rms error for MIRRA compared with other infrared and combined algorithms at the instantaneous scale, while retaining the good performance of geostationary algorithms at daily and monthly scales.
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