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This report describes the development and testing of an objective technique to forecast cloudiness and precipitation through extrapolation of satellite imagery. By utilizing on objectively determined cloud-motion vector, the technique makes local forecasts of satellite parameters (brightness and IR temperature), with high temporal resolution, using simple linear extrapolation. Algorithms are then used to convert the satellite parameters to total cloud cover, probability of 1-hour precipitation, and presence of low, middle, and high clouds. The test program computed motion vectors and made forecasts out to 7 hours, in half-hour steps, at 30 locations. The program was tested on 12 spring and fall cases, using half-hourly GOES imagery. For periods beyond 2 hours, forecasts of cloud cover and precipitation were markedly better than persistence, which deficiencies in specification hindered short-period performance. Forecasts of cloud layers were worse than persistence due to inadequate specification algorithms. The net results were quite encouraging, and further refinements and developments are planned.
An effort is underway at Air Force Geophysics Laboratory to develop automated procedures to make short-range (0-6 hr) terminal weather forecasts using GOES imagery data. A simple approach is to extrapolate the cloud patterns using motion vectors derived from a comparison of successive images. This report describes a test of candidate motion vector techniques using twelve cases of six successive images in a variety of weather conditions. Included in the techniques were two that track brightness centers, three that use cross-covariance, and two using winds aloft. All were compared against persistence (no motion, no change). For all time periods and all thresholds, a binary covariance technique had the highest scores but the techniques using winds aloft were very close. Also, no technique was much better than persistence. There is evidence that most (perhaps 75 percent) of the total changes occurring are not due to simple motion of the cloud patterns but due to more complex processes.
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