Statistical post-processing of ensemble forecasts of compound weather risk (Ref: 4342-6)

复合天气风险集合预报的统计后处理（参考：4342-6）

• 批准号: 2696930
• 金额: --
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2696930
• 关键词: Statistical; post; processing; ensemble; forecasts

The project will develop novel multivariate statistical techniques for recalibrating forecast ensembles that capture spatial, temporal and cross-variable dependence. These will improve probabilistic prediction of compound weather risk. A particular emphasis will lie on high-impact extreme weather events.The research will be conducted in close collaboration with the Met Office as CASE partner. We will use historical data from the Met Office's ensemble prediction system MOGREPS together with the corresponding verifications. Meteorological variables of interest are temperature, surface pressure, wind speed and precipitation.The main objectives of the project are:(i) to develop and explore novel methods for multivariate statistical post-processing of forecast ensembles with a particular view to extreme weather events;(ii) to improve probabilistic prediction of UK compound weather risk due to temperature, wind speed and precipitation;(iii) to help implement better techniques in the Met Office's operational post-processing suite in order to improve prediction of UK compound weather risk.

该项目将开发新型多元统计技术，用于重新校准预测集合，以捕获空间、时间和交叉变量的依赖性。这将改善复合天气风险的概率预测。特别强调的是高影响的极端天气事件。研究将与气象局密切合作，作为CASE合作伙伴进行。我们将使用气象局集合预报系统MOGREPS的历史数据以及相应的验证。该项目的主要目标是：（一）开发和探索对预报集合进行多元统计后处理的新方法，特别着眼于极端天气事件;（二）改进对英国温度、风速和降水造成的复合天气风险的概率预报;（三）加强对气候变化的预测。（iii）帮助在气象局的操作后处理套件中实施更好的技术，以改善对英国复合天气风险的预测。