Improving the regional model forecasting of persistent severe rainfall over the Yangtze River Valley using the spectral nudging and update cycle methods: a case study

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• 作者：Yanfeng Zhao ; Donghai Wang and Jianjun Xu
• 刊名：Atmospheric Science Letters
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：18
• 期：2
• 页码：96-102
• 全文大小：7217K
• ISSN：1530-261X

文摘

China's worst flooding since 1998 occurred over the Yangtze River Valley from 30 June to 6 July 2016. This study investigated the event using a new method – the spectral nudging and update cycle (SN + UIC) – in the regional Weather Research and Forecasting model, fuller use of small-scale features by using multi-scale blending. The SN + UIC was found to be successful in improving the prediction of this persistent severe rainfall event; and the larger the magnitude and longer the lead time, the more obvious the improvement. It was also found that the use of this new method decreased the root-mean-square error for related meteorological variables.