Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments
Bias Correction of High-Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments
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DOI：
10.1029/2019jd030804
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发表时间：
2019-12-26
影响因子：
4.4
通讯作者：
Allen-Sader, Clare
中科院分区：
文献类型：
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作者：
Bannister, Daniel;Orr, Andrew;Allen-Sader, Clare
人们普遍认识到，需要为水文和水资源系统评估提供兴都库什、喀喇昆仑和喜马拉雅山脉集水区降水量的准确估计，并认识到需要确定极端降水量，以评估水文气象灾害。在这里，我们调查偏差校正的天气研究和预报模型输出的能力，在5公里的网格间距，再现降水的时空变化的Beas和Sutlej河流域在喜马拉雅山，测量44站分布在1980年至2012年。对于Sutlej盆地，我们发现，原始（未校正）模型输出普遍低估了年，月，（特别是低强度）日降水量。对于Beas盆地，模型性能更好，尽管仍然存在偏差。据推测，在Sutlej盆地的干偏差的原因是失败的模式，以代表清晨最大的降水在季风期间，这是与过多的降水落在逆风。然而，应用非线性偏差校正方法的模式输出产生了更好的结果，这是上级降水估计再分析和两个网格数据集。这些研究结果突出了使用当前网格化数据集作为喜马拉雅流域水文建模输入的困难，表明偏差校正的高分辨率区域气候模型输出实际上是必要的。此外，降水极端的Beas和Sutlej流域的网格数据集的代表性相当不足，这表明偏差校正的区域气候模型输出也是必要的水文气象风险评估在喜马拉雅流域。
The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognized, as is identifying precipitation extremes for assessing hydro-meteorological hazards. Here, we investigate the ability of bias-corrected Weather Research and Forecasting model output at 5-km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low-intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early-morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a nonlinear bias-correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modeling in Himalayan catchments, suggesting that bias-corrected high-resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably underrepresented in the gridded datasets, suggesting that bias-corrected regional climate model output is also necessary for hydro-meteorological risk assessments in Himalayan catchments.