Forecasting of Flash-Flood-Producing Precipitation by Coupling Multiple Sources of Information
Abstract: The precipitation forecasts from radar and satellite cloud pictures (with a lead time of 0 - 2 h), from upper air and ground surface atmospheric sounding (with a lead time of 0 - 24 h) and from numerical forecasting mode (with a lead time of 0 - 72 h) have different forecast effect in different forecast pe-riods. Considering the short lead time and low accuracy forecast for early warning of mountain tor-rents, study on the numerical forecasting model, the model’s optimized combination of parameters, data assimilation, correcting the errors on forecasted rainfall in flash-flood affected region and an op-timized calculating method based on big data for radar monitoring precipitation. Linxiang City of Hu-nan Province was selected as experimental area and the results show that the WRF numerical forecast is more suitable for the forecast of disasters including mountain torrents. Among them, WSM6 cloud microphysical process, Grell-Devenyi ensemble convective parameterization scheme and YSU boun-dary layer parameter configuration scheme can greatly simulate the process of mountain torrents and storm causing a flood, precipitation deviation correction method based on frequency (or area) match can considerably improve the systematic deviation in the rainfall and scope of rain area in the preci-pitation forecast, the big data analysis method used in radar rainfall forecast can remarkably improve the accuracy. A forecasting disastrous flash floods method has been proposed by coupling upper air and ground surface atmospheric sounding, the 0 - 72 h short-term quantitative precipitation forecasts (QPF) from numerical forecasting mode and the 0 - 2 h nowcast QPF based on radar, which helps to increase the lead time of flash flooding forecasts from 2 h to 72 h and enhance significantly the fore-casting accuracy.
文章引用: 熊 明 , 杨文发 , 李 俊 , 周北平 , 訾 丽 (2017) 多元信息耦合的致灾山洪降雨预报方法。 水资源研究， 6， 91-102. doi: 10.12677/JWRR.2017.62013
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