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This research focuses on developing a linear regression formula that forecasters in the Midwest can use to accurately anticipate the formation of radiation fog. This was accomplished in three stages. First a study of the surface and upper air parameters and processes required to develop radiation fog were identified and explored. Next, a linear regression technique was applied to the 23 parameters identified. The top four indicators were then reprocessed and a new linear regression equation was developed. Finally, the new regression equation was compared to an existing fog forecasting technique. The existing forecast technique selected was the 2 nd Weather Wings 'Fog Stability Index.' Hit rates, False Alarm Rates and Threat Scores for both methods were calculated and compared. In general the linear regression, while only accounting for 45 to 50 percent of the total error (SST), outperformed the Fog Stability Index in ability to accurately forecast the development of radiation fog, and greatly reduced the number of incorrect forecasts. The new linear regression equation reduced the false alarm rate on fog forecasting by 23 to 43 percent and increased the threat score ability 30 to 60 percentage points.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
