Comparisons of gauge and satellite rain estimates for the central United States during August 1979

Abstract

Rainfall estimates, inferred from the thermal infrared channel of the Geostationary Operational Environmental Satellite‐East (GOES‐East) for August 1979, are compared with gauge rainfalls over hourly and daily time frames for area‐averaged amounts and point values. The area of interest is a 3.6×106 km2 region in the central third of the United States. Over the month the satellite rainfalls tend to be smaller by 20–40% than the corresponding gauge amounts, but mean sampling errors inherent in a gauge network of this density (1 gauge/4000 km2) are estimated to be minimally 100% of the areal mean rainfall. Root‐mean‐square errors are approximately 1 mm for daily and 0.1 mm for hourly area‐averaged rainfalls and are 14 mm for daily and 5 mm for hourly point rainfalls. Satellite‐gauge differences of daily (hourly) point values can be large, but 50% of the satellite amounts are within ±4 (±2) mm of the gauge amount, and 90% are within ±20 (±8) mm, reinforcing the fact that the satellite‐derived rainfall is an area‐averaged rather than a point estimate of rain amount. Timing of rain events is comparable for daily area‐averaged satellite and gauge data. However, hourly area‐averaged gauge data exhibit considerably more short‐term fluctuations than the hourly satellite data. For the two satellite algorithms tested, the streamlined technique requires the least computation time (10% of that needed by the life history technique) and shows a little difference in its comparisons with the gauges.

Integration of Remote Sensing and GIS for Hydrologic Studies

“…Most of these methods fall into one of six categories; i.e., cloud indexing approach, threshholding approach, life-history approach (Griffith, 1987;Scofield, 1987;Shih, 1990), pattern-classification approach (Weiss and Smith, 1987), integrating approach (Cheng and Shih, 1992), and microwave radiometry (Spencer et aI., 1988). It should be noted that direct measurement of rainfall from satellite data for operational purposes has not been generally feasible.…”

Precipitation

“…The cloud top has the temperature of the ambient environment, so very cold tops of convective systems represent very deep and intense convection. The primary source of error is that rainfall is not directly sensed by the thermal radiometers (Griffith, 1987). Consequently, thermal infrared measurements are best suited for convective rainfall where the basic assumptions are valid.…”

“…Griffith developed two diagnostic, automatic techniques for use with the visible and infrared spin scan radiometer (VISSR) on the Geostationary Operational Environmental Satellites (GOES) (Griffith et al, 1978;Griffith et al, 1981;Griffith, 1987). The life-history technique incorporates information about the life cycle of the convective cloud in the rainfall estimation.…”

“…In the life-history approach of Griffith, the assumptions are: 1) raining clouds have cloud top temperatures colder than -19° C, 2) rainfall rate is directly proportional to the cloud area on a given image, 3) rainfall intensity at a point is inversely proportional to the temperature of the cloud top, and 4) rainfall distribution in time is a function of the stage of the life cycle of the cloud (Griffith, 1987). These assumptions presume that convective cloud development follows a more-or-less established pattern.…”

“…For personal use only; all rights reserved. rain volume is assigned to the next warmer 40% (Griffith, 1987). Modifications of the life history or streamlined approaches could incorporate actual rainfall areas and intensities from calibrated radar (Barrett, 1981).…”