Impact of Data Assimilation on Forecasting Convection over the United Kingdom Using a High-Resolution Version of the Met Office Unified Model
Impact of Data Assimilation on Forecasting Convection over the United Kingdom Using a High-Resolution Version of the Met Office Unified Model
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使用气象局统一模型的高分辨率版本进行数据同化对英国上空对流预报的影响
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
S. Ballard
中科院分区：
文献类型：
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作者：
M. Dixon;Zhihong Li;H. Lean;N. Roberts;S. Ballard
摘要 高分辨率资料同化系统已在英国气象局统一模型 (UM) 的 4 公里网格长度版本内实施和测试。变分分析方案用于使用传统观测类型来校正更大的尺度。该系统使用两个微移程序来同化高分辨率信息：通过潜热微移（LHN）同化雷达得出的表面降水率，而云微移（CN）用于同化来自卫星、雷达和表面观测的湿度场。数据同化方案在对流风暴启动项目 (CSIP) 的五个对流主导案例研究中进行了测试。通过基于尺度的验证方案，使用雷达得出的每小时累积的表面降水量对模型技能进行统计评估。研究表明，数据同化对临近预报时间尺度的同化和随后的预报期间的技能产生巨大影响。由此产生的预测还显示...
Abstract A high-resolution data assimilation system has been implemented and tested within a 4-km grid length version of the Met Office Unified Model (UM). A variational analysis scheme is used to correct larger scales using conventional observation types. The system uses two nudging procedures to assimilate high-resolution information: radar-derived surface precipitation rates are assimilated via latent heat nudging (LHN), while cloud nudging (CN) is used to assimilate moisture fields derived from satellite, radar, and surface observations. The data assimilation scheme was tested on five convection-dominated case studies from the Convective Storm Initiation Project (CSIP). Model skill was assessed statistically using radar-derived surface-precipitation hourly accumulations via a scale-dependent verification scheme. Data assimilation is shown to have a dramatic impact on skill during both the assimilation and subsequent forecast periods on nowcasting time scales. The resulting forecasts are also shown to ...