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Geo-spatial grid-based transformations of precipitation estimates using spatial interpolation methods

机译：基于空间插值方法的基于地理空间网格的降水量估算转换

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Geo-spatial interpolation methods are often necessary in instances where the precipitation estimates available from multisensor source data on a specific spatial grid need to be transformed to another grid with a different spatial grid or orientation. The study involves development and evaluation of spatial interpolation or weighting methods for transforming hourly multisensor precipitation estimates (MPE) available in the form of 4 ×4 km~2 HRAP (hydrologic rainfall analysis project) grid to a Cartesian 2×2 km~2 radar (NEXt generation RADar:NEXRAD) grid. Six spatial interpolation weighting methods are developed and evaluated to assess their suitability for transformation of precipitation estimates in space and time. The methods use distances and areal extents of intersection segments of the grids as weights in the interpolation schemes. These methods were applied to transform precipitation estimates from HRAP to NEXRAD grids in the South Florida Water Management District (SFWMD) region in South Florida, United States. A total of 192 rain gauges are used as ground truth to assess the quality of precipitation estimates obtained from these interpolation methods. The rain gauge data in the SFWMD region were also used for radar data bias correction procedures. To help in the assessment, several error measures are calculated and appropriate weighting functions are developed to select the most accurate method for the transformation. Three local interpolation methods out of six methods were found to be competitive and inverse distance based on four nearest neighbors (grids) was found to be the best for the transformation of data.
机译：在需要从特定空间网格上的多传感器源数据获得的降水估计需要转换为具有不同空间网格或方向的另一个网格的情况下，通常需要地理空间插值方法。该研究涉及空间插值或加权方法的开发和评估，以将每小时4×4 km〜2 HRAP（水文降雨分析项目）网格形式的每小时多传感器降水估计（MPE）转换为笛卡尔2×2 km〜2雷达（NEXt代RADar：NEXRAD）网格。开发并评估了六种空间插值加权方法，以评估它们在空间和时间上转换降水量估计的适用性。该方法使用网格的相交段的距离和面积作为插值方案中的权重。这些方法用于将美国南部佛罗里达州南佛罗里达州水管理区（SFWMD）地区的降水量估计从HRAP转换为NEXRAD网格。总共使用192个雨量计作为地面实况，以评估通过这些插值方法获得的降水估计的质量。 SFWMD区域中的雨量计数据也用于雷达数据偏差校正程序。为了帮助评估，计算了一些误差度量，并开发了适当的加权函数以选择最准确的转换方法。发现六种方法中的三种局部插值方法具有竞争性，并且基于四个最近邻（网格）的反距离被认为是数据转换的最佳方法。

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