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On the Relationship between Satellite-Observed Cloud Cover and Precipitation

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  • 1 Center for Environmental Assessment Services, Environmental Data and Information Service, NOAA, Washington, DC 20235
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Abstract

The effect of averaging over various spatial scales (0.5–2.5° latitude) and times (1–24 h) on the relationship between the mean fraction of the averaging area covered by clouds colder than various IR equivalent blackbody temperature thresholds and the precipitation over that area is examined. While a linear relationship between fractional coverage and rainfall amount shows considerable scatter at the smallest scale, there is much better correspondence at the larger scales, with linear correlation coefficients often exceeding 0.8. Large-scale rainfall estimates based on linear regression coefficients detect the timing and magnitudes of major rainfall events during GATE. For scales on the order of 2–3° of latitude, estimates based on a linear model are comparable to those found by Stout et al. (1979) and Griffith et al. (1980) for the GATE area. This simple model appears to be limited to scales considerably larger than the convective scale. Averaging over these scales minimizes the effects of the spatial and temporal details of the convective fields. The linear model can be interpreted as the application of an effective mean rainfall rate to the entire precipitating cloudy area. While such an approach does not provide detailed resolution of the field of precipitation, estimation procedures based on linear models may be useful for large-scale budget studies and certain hydrologic and agricultural applications.

Abstract

The effect of averaging over various spatial scales (0.5–2.5° latitude) and times (1–24 h) on the relationship between the mean fraction of the averaging area covered by clouds colder than various IR equivalent blackbody temperature thresholds and the precipitation over that area is examined. While a linear relationship between fractional coverage and rainfall amount shows considerable scatter at the smallest scale, there is much better correspondence at the larger scales, with linear correlation coefficients often exceeding 0.8. Large-scale rainfall estimates based on linear regression coefficients detect the timing and magnitudes of major rainfall events during GATE. For scales on the order of 2–3° of latitude, estimates based on a linear model are comparable to those found by Stout et al. (1979) and Griffith et al. (1980) for the GATE area. This simple model appears to be limited to scales considerably larger than the convective scale. Averaging over these scales minimizes the effects of the spatial and temporal details of the convective fields. The linear model can be interpreted as the application of an effective mean rainfall rate to the entire precipitating cloudy area. While such an approach does not provide detailed resolution of the field of precipitation, estimation procedures based on linear models may be useful for large-scale budget studies and certain hydrologic and agricultural applications.

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