王东海,赵艳风,翟盘茂. 2018. 持续性强降水的区域模式动力中期预报研究回顾[J]. 气象学报, (0):-, doi:10.11676/qxxb2018.042
持续性强降水的区域模式动力中期预报研究回顾
A Study of the Regional Model Dynamic Medium-term Forecasting on Persistent Severe Rainfall
投稿时间:2017-09-20  修订日期:2018-04-12
DOI:10.11676/qxxb2018.042
中文关键词:  持续性强降水  区域模式动力中期预报  侧边界滤波  谱逼近  更新初值
英文关键词:Persistent severe precipitation  Dynamic medium-term forecasting by the regional model  Lateral boundary filtering  Spectral nudging  Update initial conditions
基金项目:国家自然科学基金;国家重点基础研究规划项目
作者单位E-mail
王东海 中山大学大气科学学院 wangdh7@mail.sysu.edu.cn 
赵艳风 中山大学大气科学学院 zhaoyanfeng_7266@163.com 
翟盘茂 中国气象科学研究院灾害天气国家重点实验室 pmzhai@camscma.cn 
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中文摘要:
      持续性强降水及其次生灾害给人民的生产和生活造成严重影响,延伸其模式动力预报能力对防灾减灾具有重要意义。随着对持续性强降水过程形成机理及模式动力中期预报认识的不断提高,以减小模式初始条件误差、边界条件误差以及内场预报误差为目标提出了一系列动力中期预报技术方法,主要包括:针对边界条件提出低通滤波技术方案,改进了5天以上的环流及降水预报;针对模式预报内场进行谱逼近技术试验,对提前3-7天的小雨以上量级的降水预报改进明显;针对初始条件进行多尺度混合更新初值技术预报试验,融合全球预报的大尺度场及区域模式预报的中小尺度场进行15天预报,明显提高了50及100 mm以上的持续性累积降水预报时效。
英文摘要:
      Persistent severe rainfall (PSR) and its related phenomena lead to considerable threat to human safety and economic stability, and so prolonging the forecast range would be of great importance to enhance our disaster prevention and mitigation capabilities. With deepened understanding of the formation mechanisms for PSR events and the dynamic medium-term forecast methodology in the regional model, a set of improvement methods for the dynamic medium-term forecasting of PSP events using the regional Weather Research and Forecasting (WRF) model were summarized, with a view of the error reduction for initial conditions, lateral boundary conditions, and regional model interior forecasting. For the lateral boundary conditions, using the low-pass filtering method enables better forecasting of circulation fields and precipitation at lead times above 5 days. For the regional model interior forecasting, the use of spectral nudging leads to clear improvements in precipitation forecasts for the categories above light rain at lead times of 3-7 days. For the initial conditions, the update initial condition is an effective method to retain the large-scale forecasts of the global model predictions and the small-scale features of the WRF forecasts for 15-day forecasts in WRF, it significantly improved the simulative forecasts of the accumulated precipitation above 50 mm and 100 mm.
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