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A Method for Improving the Accuracy of Weather Forecasts Bas | 21000

Journal of Climatology & Weather Forecasting

ISSN - 2332-2594

Abstrato

A Method for Improving the Accuracy of Weather Forecasts Based on a Comprehensive Statistical Analysis of Historical Data for the Contiguous United States

Audrey W. Zhu and Halton Pi

Using historical weather forecast data downloaded from the National Oceanic and Atmospheric Administration’s [NOAA] National Weather Service Digital Library, we performed statistical analysis on the forecast accuracies of temperature, probability of precipitation, quantitative precipitation and wind speed. The major findings of this study are: (1) There are significant variations in forecast accuracies at different geographical locations in the United States; (2) The overall accuracies of 3-day or longer temperature forecasts are similar in magnitude to the standard deviations of historical daily changes in temperature; (3) There are statistically significant biases in the forecasts of either large positive or negative changes in temperatures; (4) The observed probabilities of precipitation are significantly lower than forecasted probabilities for 2-day or longer horizons; (5) On the average, the 3-day or longer forecasts for quantitative precipitation tend to significantly under estimate actual amount for periods of heavy precipitation; and (6) Forecasters generally under predict wind speeds by a large margin for days when wind speeds exceed 20 mph. An improved weather forecast model can be constructed based on some of the empirical statistical parameters from this study.

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