Researchers at the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) have been at the forefront in the development of precipitation retrieval algorithms from passive microwave sensors for over 20 years. This includes algorithms used for the DMSP Special Sensor Microwave Imager (SSM/I), the TRMM Microwave Imager (TMI), the NOAA Advanced Microwave Sounding Unit (AMSU) and the EOS Aqua Advanced Scanning Microwave Radiometer (AMSR-E). NOAA requires such retrievals to support two of its main scientific mission elements: "Weather and Water" and "Climate Monitoring and Prediction".
This presents an overview of the algorithm development, recent advances (i.e., the expansion of the retrievals to over snow covered surfaces) and future plans (i.e., the development of a general retrieval framework adaptable for use with any microwave sensor) as NOAA enters into the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Global Precipitation Measurement (GPM) era. Application examples to highlight the use of these products at NOAA are also presented.
Revised versions of previous passive microwave land rainfall algorithms are developed for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), the Special Sensor Microwave/Imager (SSM/I), and the new Advanced Microwave Sounding Radiometer-Earth Observing System (EOS) (AMSR-E). The relationships between rainfall rate and 85 GHz brightness temperature are re-calibrated with respect to previous algorithms using collocated TMI and TRMM Precipitation Radar (PR) data. Another new feature is a procedure to estimate the probability of convective rainfall, as convective/stratiform classification can reduce the abmiguity of possible rainfall rates for a given brightness temperature. These modifications essentially eliminate the global high bias found in studies of previous versions of the SSM/I and TMI algorithms. However, many regional and seasonal biases still exist, and these are identified. The applicability of the new features to the other microwave sensors is studied using SSM/I data. The AMSR-E algorithm is the same as the TMI, as the footprint resolutions and frequencies of these instruments are very similar. The TMI algorithm will be used in the land portion of the offical Version 6 TMI instantaneous rainfall rate product, to be released in 2003, while the AMSR algorithm will be used for future AMSR-E products.