The UK Met Office state‐of‐the‐art, deterministic, convection‐permitting, coupled land‐atmosphere, regional weather forecasting system, known as the UKV or UK Variable resolution model (Tang et al. Meteorological Applications, 2013; 20:417–426), has been operational since 2015. Science updates are regularly made to the UKV land surface data assimilation scheme when those updates improve predictions of screen temperature and humidity, since these quantities have a direct impact on atmospheric states and weather forecasts. Less attention has been paid to whether UKV soil moisture analyses are close to independent, in‐situ soil moisture observations, partly because it is difficult to make meaningful comparisons between 1.5 km2 gridded model outputs and traditional point sensor measurements. Soil moisture is recognized to be important when hydrological forecasts for runoff and rivers are required. This is because soil moisture controls the extent to which rainfall can infiltrate the soil, and the amount of surface runoff affects the timing of peak river flows (Ward & Robinson, Principles of Hydrology. McGraw‐Hill Publishing Company; 2000; Singh et al. Water Resources Research, 2021, 57, e2020WR028827). Gómez et al. (Remote Sensing, 2020; 12:3691) report benefits to river flow forecasts when using soil moisture data assimilation in the UKV system instead of a daily downscaled product from the Met Office global model. The Met Office measures soil temperature and soil moisture at Cardington (Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279–295); there is no other UK Met Office site at which soil moisture is measured. In this study, we use field‐scale (~200 m radius) soil moisture measurements from the UK Centre for Ecology and Hydrology's (UKCEH's) COSMOS‐UK network to provide independent verification and analysis of UKV soil moisture during summer 2018, an unusually dry period in the United Kingdom. We find that the match to COSMOS‐UK soil moisture observations is generally good, and that changes made to the land data assimilation approach during a recent operational upgrade had a generally beneficial impact on UKV soil moisture analyses under very dry conditions.

中文翻译：

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英国气象局区域模型土壤湿度与 COSMOS-UK 现场规模实地观测的比较

英国气象局最先进的、确定性的、允许对流的、陆地-大气耦合的区域天气预报系统，称为 UKV 或英国可变分辨率模型（Tang 等，2017）。气象应用，2013； 20:417–426），自 2015 年开始运行。当这些更新改进屏幕温度和湿度的预测时，会定期对 UKV 陆地表面数据同化方案进行科学更新，因为这些数量对大气状态和天气预报有直接影响。人们较少关注 UKV 土壤水分分析是否接近独立的原位土壤水分观测，部分原因是很难在 1.5 公里之间进行有意义的比较2网格模型输出和传统点传感器测量。当需要对径流和河流进行水文预报时，土壤湿度被认为非常重要。这是因为土壤湿度控制降雨渗透土壤的程度，而地表径流量影响河流峰值流量的时间（Ward & Robinson，水文学原理。麦格劳-希尔出版公司； 2000；辛格等人。水资源研究, 2021, 57, e2020WR028827)。戈麦斯等人。 （遥感, 2020; 12:3691）报告了在 UKV 系统中使用土壤湿度数据同化而不是英国气象局全球模型的每日缩小产品时对河流流量预测的好处。英国气象局测量卡丁顿（Osborne & Weedon、水文气象学杂志, 2021, 22:279–295);英国气象局没有其他地点可以测量土壤湿度。在本研究中，我们使用英国生态与水文学中心 (UKCEH) COSMOS-UK 网络的现场规模（半径约 200 m）土壤湿度测量结果，对 2018 年夏季的 UKV 土壤湿度进行独立验证和分析，夏季异常干燥。在英国时期。我们发现，与 COSMOS-UK 土壤湿度观测结果的匹配总体上良好，并且在最近的操作升级期间对土地数据同化方法所做的更改对非常干燥条件下的 UKV 土壤湿度分析产生了总体有利的影响。