Progress, challenges, and future steps in data assimilation for convection-permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021
Progress, challenges, and future steps in data assimilation for convection-permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021
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对流数值天气预报数据同化的进展、挑战和未来步骤：2021 年 11 月 10 日至 12 日举行的虚拟会议报告
DOI：
10.1002/asl.1130
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发表时间：
2022
影响因子：
3
通讯作者：
Hu G
中科院分区：
文献类型：
--
作者：
Hu G
2021年11月，皇家气象学会数据同化（DA）特别兴趣小组和阅读大学举办了一次虚拟会议，主题是DA用于对流允许数值天气预报。会议的目的是讨论最近的发展情况，并审查各种挑战，包括方法发展情况和在最佳利用观测结果方面取得的进展。会议于11月10日和12日进行了两个半天，包括六次会谈和一次小组讨论。科学报告强调了欧洲和美国最近在允许对流的DA方面的一些工作，包括观测同化方面的新发展，如可见光通道中受云影响的卫星辐射、地基剖面网络、飞机数据和雷达反射率数据，以及背景和观测误差协方差建模方法的进步和业务系统的进展。小组讨论集中在未来的关键挑战，包括多尺度（天气尺度，中尺度和对流尺度）的处理，集合设计，背景和观测误差协方差的规格，以及更好地利用观测。这些将是需要解决的关键问题，以改善短期预报和危险天气的即时预报。
In November 2021, the Royal Meteorological Society Data Assimilation (DA) Special Interest Group and the University of Reading hosted a virtual meeting on the topic of DA for convection‐permitting numerical weather prediction. The goal of the meeting was to discuss recent developments and review the challenges including methodological developments and progress in making the best use of observations. The meeting took place over two half days on the 10 and 12 November, and consisted of six talks and a panel discussion. The scientific presentations highlighted some recent work from Europe and the USA on convection‐permitting DA including novel developments in the assimilation of observations such as cloud‐affected satellite radiances in visible channels, ground‐based profiling networks, aircraft data, and radar reflectivity data, as well as methodological advancements in background and observation error covariance modelling and progress in operational systems. The panel discussion focused on key future challenges including the handling of multiscales (synoptic‐, meso‐, and convective‐scales), ensemble design, the specification of background and observation error covariances, and better use of observations. These will be critical issues to address in order to improve short‐range forecasts and nowcasts of hazardous weather.