Ryazanova Anna, Voropay Nadezhda, Dyukarev Egor
Institute of Monitoring of Climatic and Ecological System SB RAS, Akademicheskii 10/3, Tomsk 634055, Russia.
V B Sochava Institute of Geography SB RAS, Ulan-Batorskaya st., 1, Irkutsk 664033, Russia.
Data Brief. 2021 Oct 5;38:107440. doi: 10.1016/j.dib.2021.107440. eCollection 2021 Oct.
Bias-Corrected Precipitation data over outh iberia () contains monthly precipitation data for the area within the coordinates 50-65 N, 60-120 E for the period from January 1979 to December 2019. CPSS data were combined from monthly total precipitation data from ERA5 reanalysis European Centre for Medium-Range Weather Forecasts and precipitation data records from ground weather stations. The ERA5 data were scaled according to the derived scale coefficient. The linear scaling coefficient for each month and weather station were calculated and extrapolated to the study area using the ordinary kriging method. Data spatial resolution is 0.25° in the latitude and 0.25° in the longitude. CPSS reproduces the spatial variability of precipitation more precisely than can be done from the weather station observation network. The CPSS dataset will be useful for the study of extreme precipitation events and allow for more accurate hydrologic risk assessment at a regional level based on climate model results.
南西伯利亚地区的偏差校正降水数据(CPSS)包含了1979年1月至2019年12月期间北纬50 - 65度、东经60 - 120度区域内的月降水数据。CPSS数据是由欧洲中期天气预报中心ERA5再分析的月总降水数据和地面气象站的降水数据记录合并而成。ERA5数据根据推导的比例系数进行了缩放。计算了每个月和气象站的线性缩放系数,并使用普通克里金法将其外推到研究区域。数据的空间分辨率在纬度上为0.25°,在经度上为0.25°。CPSS比气象站观测网络更精确地再现了降水的空间变异性。CPSS数据集将有助于研究极端降水事件,并基于气候模型结果在区域层面进行更准确的水文风险评估。