Applying bias correction for merging rain gauge and radar data
Applying bias correction for merging rain gauge and radar data
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DOI：
10.1016/j.jhydrol.2015.01.020
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发表时间：
2015-03
影响因子：
6.4
通讯作者：
E. Rabiei;U. Haberlandt
中科院分区：
文献类型：
--
作者：
E. Rabiei;U. Haberlandt
天气雷达提供非常高的时间和空间分辨率的面雨量信息。雷达数据已在几个水文应用中得到应用，尽管这些数据的误差来源各不相同。一些研究试图提出解决这些问题的方法。此外，天气雷达通常会低估或高估降雨量。在这项研究中，提出了一种新的雷达数据校正方法--分位数映射偏差校正方法。然后，用条件合并、克里格法和外漂移内插技术将雷达资料与观测雨量进行融合。分析了两种融合方法对雷达数据质量的敏感度。实施偏差校正后，不仅提高了雷达数据的质量，而且提高了利用雷达数据作为附加信息的内插技术的性能。总体而言，条件合并对雷达数据质量表现出更高的敏感性，但在使用经偏差校正的雷达数据时，其表现优于所有其他内插技术。此外，总体上观察到了插补性能的季节性变化。文中还给出了一个利用雷达资料分解观测站从日分辨率到小时分辨率的实例。
Weather radar provides areal rainfall information with very high temporal and spatial resolution. Radar data has been implemented in several hydrological applications despite the fact that the data suffers from varying sources of error. Several studies have attempted to propose methods for solving these problems. Additionally, weather radar usually underestimates or overestimates the rainfall amount. In this study, a new method is proposed for correcting radar data by implementing the quantile mapping bias correction method. Then, the radar data is merged with observed rainfall byconditional mergingandkriging with external driftinterpolation techniques. The merging product is analysed regarding the sensitivity of the two investigated methods to the radar data quality. After implementing bias correction, not only did the quality of the radar data improve, but also the performance of the interpolation techniques using radar data as additional information. In general, conditional merging showed greater sensitivity to radar data quality, but performed better than all the other interpolation techniques when using bias corrected radar data. Furthermore, a seasonal variation of interpolation performances has in general been observed. A practical example of using radar data for disaggregating stations from daily to hourly temporal resolution is also proposed in this study.