ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Application of Sichuan Heavy Rainfall Ensemble Prediction Probability Products Based on Bayesian Method
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Abstract:
A method of improving the Sichuan heavy rainfall forecasting accuracy based on the Bayesian decision theory is explored. This method uses the heavy rainfall climate probability of Sichuan 147 stations from June to September in 1951 to 2004 to modify the ensemble prediction probability products of precipitation more than 50 mm produced by southwest regional ensemble forecasting system. The continuous forecasting test results from June to September in 2008 show that the posterior probability, i.e. the probability modified by the Bayesian mathod, can eliminate the false prediction to some extent. Although the effect of improving the heavy rainfall forecasting accuracy is not obvious compared with the prior probability, it still provides an exploring method-how to use the numerical ensemble prediction products to improve the Sichuan heavy rainfall forecasting accuracy and how to provide more valuable heavy rainfall information for the early warning decision method.
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