Dataset of pan-European 1-h OPERA radar precipitation accumulations adjusted with rain gauge accumulations from Netatmo personal weather stations

Ground-based weather radars provide precipitation estimates with wide coverage and high spatiotemporal resolution, but usually need adjustment with rain gauge data to obtain a reasonable accuracy. The (near) real-time availability and density of rain gauge networks operated by official institutes, especially national meteorological and hydrological services, is often relatively low. Crowdsourced rain gauge networks typically have a much higher density than networks from official institutes. Data from PWSs from brand Netatmo were obtained. Here, pan-European 1-h radar precipitation accumulations have been adjusted with 1-h rain gauge accumulations from personal weather stations (PWSs) for each clock-hour. The radar data were obtained from the Operational Program on the Exchange of weather RAdar information (OPERA) over the period 1 September 2019–31 August 31 2020. Two statistical methods and a satellite cloud type mask have been applied to the OPERA data to further remove non-meteorological echoes. Although not all these methods could be applied in (near) real-time, the OPERA dataset is representative of near (real-time) data, because these methods do only concern non-meteorological echo removal and not precipitation estimation itself. The Netatmo PWS data were subjected to quality control employing neighbouring PWSs and unadjusted radar data, before they were merged with the radar accumulations. A spatial adjustment (merging) method has been employed. The dataset covers 78% of geographical Europe. The dataset aims to show the potential of crowdsourced rain gauge data to improve radar data in (near) real-time.

地基气象雷达可提供覆盖范围广、时空分辨率优异的降水估测产品，但通常需结合雨量计（rain gauge）数据进行校正，方可达到合理的精度水平。官方机构（尤其是国家气象与水文服务部门）运营的雨量计网络，其近实时可用性与布设密度往往相对较低。众包雨量计网络的布设密度通常远高于官方机构的同类网络。研究人员获取了Netatmo品牌个人气象站（Personal Weather Station, PWS）的观测数据。本研究针对每个整小时时段，采用个人气象站的1小时雨量计累积数据，对泛欧洲1小时雷达降水累积量进行了校正。本次研究所用的雷达数据来源于2019年9月1日至2020年8月31日期间的天气雷达信息交换业务计划（Operational Program on the Exchange of weather RAdar information, OPERA）。研究团队针对OPERA数据集应用了两种统计方法与一种卫星云型掩码技术，以进一步剔除非气象回波。尽管上述方法并非全部可适配近实时应用场景，但OPERA数据集仍具备近实时数据的代表性，原因在于这些方法仅针对非气象回波剔除，并不涉及降水估测核心流程。Netatmo品牌的个人气象站数据在与雷达降水累积数据合并前，已通过相邻个人气象站观测数据与未校正雷达数据完成了质量控制流程。本数据集采用了空间校正（合并）方法。该数据集覆盖了地理意义上欧洲大陆的78%范围。本数据集旨在展现众包雨量计数据在近实时场景下改善雷达降水数据的应用潜力。