Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting: Adjustment factors for the Netherlands

This dataset contains gridded adjustment factors for correction of the Quantitative Precipitation Estimations (QPE) of the two operational C-band weather radars operated by the Royal Netherlands Meteorological Institute (KNMI). The factors are based on the CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting) method, described in Imhoff et al. (2021). The factors are available for every yearday (temporal resolution of one day) and are based on ten years (2009 - 2018) of radar and reference rainfall data, as distributed by KNMI. For the derivation of the factors, both the operational radar QPE (https://doi.org/10.4121/uuid:05a7abc4-8f74-43f4-b8b1-7ed7f5629a01) and a reference rainfall dataset of KNMI (https://dataplatform.knmi.nl/catalog/datasets/index.html?x-dataset=rad_nl25_rac_mfbs_em_5min&&x-dataset-version=2.0) are used. The reference is not available in real time, but becomes available with a one to two month delay and was therefore available for this climatological factor derivation. The derivation method was as follows per grid cell in the radar domain (Imhoff et al., 2021): 1. For every day in the period 2009--2018, an accumulation took place of all 5-min rainfall sums (of both the unadjusted radar QPE and the reference) within a moving window of 15 days prior to and 15 days after the day of interest. 2. For every yearday, the accumulations (per day) from the previous step were averaged over the ten years. 3. Gridded climatological adjustment factors (Fclim) were calculated per yearday as: Fclim(i,j) = RA(i,j) / RU(i,j). In this equation, RA(i,j) is the reference rainfall sum for the ten years and RU(i,j) the operationally available unadjusted radar QPE sum, based on the previous two steps, at grid cell (i, j). For more details about the method, see Imhoff et al. (2021). For more information about the reference dataset, which consists of the radar QPE spatially adjusted with observations from 31 automatic and 325 manual rain gauges, see Overeem et al. (2009a,b).本数据集包含用于校正荷兰皇家气象研究所（Royal Netherlands Meteorological Institute, KNMI）运行的两部现役C波段天气雷达的定量降水估计（Quantitative Precipitation Estimation, QPE）结果的格点校正因子。该校正因子基于由Imhoff等人（2021年）提出的CARROTS方法（Climatology-based Adjustments for Radar Rainfall in an Operational Setting，基于气候学的业务场景雷达降雨校正方法）构建，其数据来源为KNMI发布的2009年至2018年共十年的雷达与参考降雨数据集，时间分辨率为1日，覆盖每个年积日。 在校正因子的推导过程中，使用了KNMI提供的两部现役雷达的QPE结果（https://doi.org/10.4121/uuid:05a7abc4-8f74-43f4-b8b1-7ed7f5629a01）以及一套参考降雨数据集（https://dataplatform.knmi.nl/catalog/datasets/index.html?x-dataset=rad_nl25_rac_mfbs_em_5min&&x-dataset-version=2.0）。该参考数据集并非实时可用，而是存在1至2个月的延迟，因此可用于本次气候学校正因子的推导。 校正因子的推导针对雷达覆盖区域内的每个格点进行，步骤如下（Imhoff等，2021）： 1. 在2009-2018年的每日时段内，对目标日期前后各15天的滑动窗口内所有5分钟降雨总量（包括未校正雷达QPE与参考降雨数据）进行累加求和； 2. 针对每个年积日，将上一步得到的逐日累加结果在十年周期内取平均； 3. 基于每个年积日计算格点气候学校正因子（Fclim），计算公式为：Fclim(i,j) = RA(i,j) / RU(i,j)。其中，RA(i,j)为网格单元(i,j)在十年周期内的参考降雨累加总量，RU(i,j)为基于前述两步得到的该网格单元的现役未校正雷达QPE累加总量。 关于该方法的更多细节，请参阅Imhoff等（2021）的研究。该参考数据集是通过将雷达QPE结果与31个自动雨量计及325个人工雨量计的观测数据进行空间校正得到的，相关详细信息请参阅Overeem等（2009a,b）的文献。