Comparison of Met Office regional model soil moisture with COSMOS-UK field-scale in situ observations

IF 2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Elizabeth Cooper, Cristina Charlton-Perez, Rich Ellis
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引用次数: 0

Abstract

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.

Abstract Image

Abstract Image

英国气象局区域土壤水分模型与 COSMOS-UK 实地观测数据的比较
英国气象局最先进的、确定性的、允许对流的陆地-大气耦合区域天气预报系统,被称为UKV或UK Variable resolution model(Tang等,Meteorological Applications,2013;20:417-426),自2015年起开始运行。UKV陆面数据同化方案会定期进行科学更新,这些更新会改善对屏幕温度和湿度的预测,因为这些数据会对大气状态和天气预报产生直接影响。人们较少关注 UKV 土壤水分分析是否接近独立的现场土壤水分观测,部分原因是 1.5 平方公里网格模型输出与传统点传感器测量之间很难进行有意义的比较。在需要对径流和河流进行水文预报时,土壤水分被认为是非常重要的。这是因为土壤水分控制着降雨渗入土壤的程度,而地表径流量则影响着河流流量峰值的时间(Ward & Robinson, Principles of Hydrology.麦格劳-希尔出版公司;2000 年;Singh 等人,《水资源研究》,2021 年,57,e2020WR028827)。Gómez 等人(《遥感》,2020 年;12:3691)报告了在 UKV 系统中使用土壤湿度数据同化而非气象局全球模型的每日降尺度产品对河流流量预报的益处。英国气象局在卡丁顿测量土壤温度和土壤湿度(Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279-295);英国气象局没有其他测量土壤湿度的站点。在本研究中,我们利用英国生态学和水文学中心(UKCEH)的 COSMOS-UK 网络的野外尺度(~200 米半径)土壤水分测量数据,对 2018 年夏季英国异常干旱期间的 UKV 土壤水分进行了独立验证和分析。我们发现,与 COSMOS-UK 土壤水分观测数据的匹配情况总体良好,而且在最近的一次业务升级中对陆地数据同化方法所做的更改总体上对非常干旱条件下的 UKV 土壤水分分析产生了有利影响。
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来源期刊
Atmospheric Science Letters
Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.90
自引率
3.30%
发文量
73
审稿时长
>12 weeks
期刊介绍: Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.
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