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  • Author or Editor: Peter R. Keehn x
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George J. Huffman
,
Robert F. Adler
,
Bruno Rudolf
,
Udo Schneider
, and
Peter R. Keehn

Abstract

The “satellite-gauge-model” (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5° × 2.5° lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40°N–40–S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brought in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields.

The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions

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Andrew J. Negri
,
Robert F. Adler
,
Robert A. Maddox
,
Kenneth W. Howard
, and
Peter R. Keehn

Abstract

A three-year climatology of satellite-estimated rainfall for the warm season for the southwest United States and Mexico has been derived from data from the Special Sensor Microwave Imager (SSM/1). The microwave data have been stratified by month (June, July, August), yew (1988, 1989, 1990), and time of day (morning and evening orbits). A rain algorithm was employed that relates 86-GHz brightness temperatures to rain rate using a coupled cloud-radiative transfer model.

Results identify an early evening maximum in rainfall along the western slope of the Sierra Madre Occidental during all three months. A prominent morning rainfall maximum was found off the western Mexican coast near Mazatlan in July and August. Substantial differences between morning and evening estimates were noted. To the extent that three years constitute a climatology, results of interannual variability are presented. Results are compared and contrasted to high-resolution (8 km, hourly) infrared cloud climatologies, which consist of the frequency of occurrence of cloud colder than −38°C and −58°C. This comparison has broad implications for the estimation of rainfall by simple (cloud threshold) techniques.

By sampling the infrared data to approximate the time and space resolution of the microwave, we produce ratios (or adjustment factors) by which we can adjust the infrared rain estimation schemes. This produces a combined micro wave/infrared rain algorithm for monthly rainfall. Using a limited set of raingage data as ground truth, an improvement (lower bias and root-mean-square error) was demonstrated by this combined technique when compared to either method alone. The diurnal variability of convection during July 1990 was examined using hourly rain estimates from the GOES precipitation index and the convective stratiform technique, revealing a maximum in estimated rainfall from 1800 to 2100 local time. It is in this time period when the SSM/1 evening orbit occurs. A high-resolution topographic database was available to aid in interpreting the influence of topography on the rainfall patterns.

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