The potential falling area forecast for rainstorm induced by vortex in Zhejiang Province based on logistic regression algorithm
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Abstract
The atmospheric low-level vortex is an important weather system that causes rainstorm and flood in southern China. The vortex induced rainstorm is sudden and local, and its occurence time, intensity and falling area have always been difficult for meteorological forecasting. In order to improve the accuracy of rainstorm prediction in Zhejiang Province and improve the localization application of the prediction model, based on daily precipitation data of Zhejiang Province from 1979 to 2020 and reanalysis dataset from the National Centers for Environmental Prediction Climate Forecast System, climatic characteristics of the heavy rain in Zhejiang Province induced by low-level vortex is studied, the vortex induced rainstorm in Zhejiang mostly occurs in the rainy season and has obvious interannual variation characteristics. Then, the 850 hPa vertical velocity, water vapor flux divergence, velocity divergence, low-level jet, shear line and 700 hPa vertical velocity are used as ingredient factors, and the potential falling area forecast for heavy rain induced by vortex is constructed by using logistic regression algorithm. Finally, the forecast products of the European Medium-Range Weather Prediction Center are used to forecast the rainstorm falling area based on this model, and the actual data of the same period are used for systematic test and weather process test. Results show that the overall performance of the model is good, and the rainstorm prediction ability of 24 h and 12 h ahead is improved, which can increase from 12% accuracy and 20% to around 14% and 40% respectively, and the omission rate drops from more than 75% to around 60%, but there is a certain degree of empty report. The forecast model of Zhejiang Province based on logistic regression method has a good indicator for the prediction of such rainstorm areas, and is of great significance for meteorological disaster prevention and mitigation.
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