Satellite Cloud Data as Input to Cloud Seeding Operations

Authors

  • James A. Henry Department of Geography University of Florida

Abstract

Droughts have produced economic hardships in many sections throughout the United States in recent years, especially in areas where agricultural production is significant. The repercussions have led to increased interest in cloud seeding to augment rainfall for agricultural use during severe water shortages.

Knowledge of two climatic factors is important in assessing the probability of significantly enhancing precipitation over a specific location during occurrences of below-normal rainfall. One is the time-space distribution of naturally occurring precipitation during droughts. Huff and Semonin (1975) and Huff (1979) found that, even during extended growing-season droughts in lllinois, opportunities existed to increase agricultural water supplies by cloud seeding.

The second factor whose analysis can aid the development of a cloud seeding program is a cloud climatology of the area. Several such studies have used ground-based observations (e.g., Changnon and Huff, 1957). Cloud distribution can also be studied with weather radar and satellite data. The former was used by Bark (1975) to survey precipitating clouds over western Kansas. Satellite data have been used to produce cumulus cloud climatologies for selected regions in the Midwest (Stodt and Grant, 1976; Marotz and Henry, 1978). Simultaneous observations of clouds using digital radar and SMS/GOESsa tellite data were conducted on a limited basis at Miles City, Montana during HIPLEX (Poellot and Reynolds, 1979).

One aspect of cloud alimatology studies not intensively studied hitherto is the difference in cloud characteristics, over an area the size of a state, between years of abundant and meager rainfall. The purpose of the present study is twofold: I) determine May-September cloud cover amounts and cumulus cloud sizes from satellite data for representative normal, wet and dry years in Florida; and 2) analyze the relation of the derived cloud data to precipitation values and an index of drought. This type of information can be a valuable input in the planning stages of a weather modification program aimed at ameliorating agricultural water shortages.

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Scientific Papers