Processed data and code used to characterize rain storm intensity, duration, and size across an elevation gradient for assessment of post-fire hazards

These data include pre-existing gridded precipitation datasets that have been processed to obtain the maximum seasonal hourly and daily precipitation accumulations over the specified geographic extent, on a consistent grid. The study area includes the mountainous area of Colorado, west of 104 degrees and the study period is constrained to 1980 through 2022. Additionally, two precipitation frequency studies have been regridded, with data extracted for the same geographic region. The gridded precipitation datasets are also sampled at gage locations to facilitate comparison with station data. Elevation data have been regridded to assess how precipitation trends vary with elevation. This data publication also includes the Python script files used to process these data. All program files used to download and manipulate publicly available data are included, as well as the resulting output data files. The associated Joint Fire Science Program report is included as well.
These data was used to evaluate the spatial patterns in extreme precipitation related to terrain features, identify areas where relative intensity changes with increasing accumulation duration, observe seasonal differences in spatial patterns, and compare spatial patterns of extreme precipitation from gridded datasets with precipitation frequency studies based on interpolated station data. The reduction of orographic effects at shorter time scales is significant for post-wildfire hazards, as these hazards are more strongly associated with brief, intense rainfall events. Additionally, results highlight the need for caution when relying on interpolated data or precipitation frequency studies that use interpolated data in mountainous regions.
For additional details, see White and Nelson (2024) as well as Nelson and White (2024).

本数据集包含预先存在的网格化降水数据集，此类数据集经处理后可获取指定地理范围内、统一网格下的最大逐季逐时与逐日降水累积量。研究区域涵盖西经104度以西的科罗拉多山区，研究时段限定为1980年至2022年。此外，两项降水频率研究成果已被重网格化（regridded），并针对同一地理区域提取了对应数据。本数据集还会在雨量计站点位置进行采样，以便与实测站数据开展对比分析。高程数据已被重网格化，用于评估降水趋势随高程的变化规律。本数据发布包还包含用于处理上述数据的Python脚本文件：所有用于下载、处理公开可用数据的程序文件，以及最终生成的输出数据文件均已收录。配套的《联合火灾科学项目（Joint Fire Science Program）》研究报告也一并提供。
本数据集被用于评估与地形特征相关的极端降水空间格局，识别相对强度随累积时长增加而发生变化的区域，观测空间格局的季节差异，并对比网格化降水数据集的极端降水空间格局与基于插值站数据的降水频率研究结果。在野火后灾害场景中，短时间尺度下地形效应（orographic effects）的减弱效应不容忽视——这类灾害与短时强降雨事件的关联性更强。此外，研究结果警示，在山区依赖插值数据或基于插值数据开展的降水频率研究时需格外谨慎。
如需了解更多细节，请参阅White与Nelson（2024）以及Nelson与White（2024）的相关文献。