Aircraft play an important role in providing in‐situ upper air observations for use in numerical weather prediction (NWP) models. Aircraft observations of wind, temperature and humidity have been routinely assimilated into NWP models for decades. More recently, the Met Office has installed a network of six receivers to collect Mode‐Select Enhanced Surveillance (Mode‐S EHS) broadcasts and derive wind and temperature information. The paper focuses on the assimilation of high‐frequency (sub‐hourly) Mode‐S winds into the Met Office's hourly cycling high‐resolution NWP model, which employs four‐dimensional‐variational data assimilation (4D‐Var). An observing system experiment (OSE) experiment was carried out to assess the impact of additionally assimilating Mode‐S wind data on the model forecasts in both summer and winter. It is shown that assimilating Mode‐S winds has a positive benefit on the forecast skill in the first 6 hr wind profiles, with an improvement of the mean bias and root mean square (RMS) errors of up to 0.5 m·s⁻¹ in the first hour and 0.3 m·s⁻¹ in the sixth hour. The assimilation of Mode‐S winds is also seen to be beneficial to the near‐surface‐focused UK NWP composite index, and to the hourly precipitation accumulations in fractions skill score (FSS) for forecasts up to 9 hr ahead.

中文翻译：

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吸收Mode-E EHS风在大都会办公室高分辨率NWP模型中的影响

飞机在提供现场服务方面发挥着重要作用用于数值天气预报（NWP）模型的高空观测。数十年来，飞机观测到的风，温度和湿度已被常规地纳入NWP模型。最近，大都会办公室已经安装了由六个接收器组成的网络，以收集“模式选择增强监视”（Mode-S EHS）广播，并获取风和温度信息。本文着重于将高频（亚小时）S型风同化到美国气象局的每小时循环高分辨率NWP模型中，该模型采用了四维变化数据同化（4D-Var）。进行了观测系统实验（OSE），以评估在夏季和冬季对模式S风数据进行额外同化对模型预报的影响。^-1在第一个小时且^{0.3m·S -1}在第六小时。S型风的同化也被认为有利于以近地表为中心的英国NWP综合指数，也有利于每小时分数累积技术分数（FSS）的每小时降水积聚，可预报未来9小时。