兴都库什-喜马拉雅地区的网格化降水产品:七种降水产品的性能和精度

Bhogendra Mishra, S. Panthi, Bhoj Raj Ghimire, Shobha Poudel, Bijaya Maharjan, Y. Mishra
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摘要

气候变化预计将改变降水和温度模式,这将影响亚洲的水文状况。该地区的大多数河流系统起源于兴都库什喜马拉雅山脉,降水模式的改变对其可持续性构成威胁,使其成为规划者和利益相关者的主要担忧。获得准确的降水分布数据对水量核算至关重要,这带来了挑战。为了解决这一问题,根据卫星图像和建模技术开发的网格降水产品已成为观测降雨的可行替代或补充。然而,这些产品在该地区的准确性尚不确定。在这项研究中,我们旨在评估和比较各地区最常用的七种降水产品,以解决这一差距。该研究评估了七种降雨产品,即APHRDITE、TRMM、CHIRPS、PERSIANN-CDR、CMORPH、WFDEI和GPCC,方法是将日降雨量、月降雨量和月降雨量数据与香港地区6个国家和11个流域的168个站点数据进行比较。该分析使用了四个连续的统计指标(Pearson相关系数、偏差、均方根误差和Nash-Sutcliffe效率系数)和两个分类指标(检测概率和误报率)。APHRDITE在几个具有高r值和低RMSE值的盆地中始终表现良好,但在不同的盆地中具有正或负偏差值。CMORPH在Ganga_ Brahmaputra盆地具有最低的正偏差值,而GPCC在Sindha盆地具有最大的r值和最低的RMSE值。CHIRPS在阿富汗表现良好,但具有正偏差值。GPCC在缅甸和巴基斯坦表现良好,但存在负偏或正偏。APHRDITE在尼泊尔的表现一直很好,但存在负偏差值。总体而言,不同网格降水产品的性能因国家和评估类型而异。
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Gridded precipitation products on the Hindu Kush-Himalaya: Performance and accuracy of seven precipitation products
Climate change is expected to change precipitation and temperature patterns, which will impact the hydrological regime in Asia. Most river systems in the region originate from the Hindu Kush-Himalayas, and the altered precipitation patterns pose a threat to their sustainability, making it a major concern for planners and stakeholders. Obtaining accurate data on precipitation distribution is crucial for water accounting, which poses challenge. To address this, gridded precipitation products developed from satellite imagery and modeling techniques have become a viable alternative or addition to observed rainfall. However, the accuracy of these products in the region is uncertain. In this study, we aim to evaluate and compare the seven most commonly used precipitation products for the regions to address this gap. The study evaluated seven rainfall products, namely APHRODITE, TRMM, CHIRPS, PERSIANN-CDR, CMORPH, WFDEI, and GPCC by comparing daily, dekadal, and monthly rainfall data to 168 stations data in six countries and 11 river basins in the HKH region. The analysis used four continuous statistical indicators (Pearson correlation coefficient, Bias, Root Mean Square Error, and Nash–Sutcliffe Efficiency coefficient) and two categorical indicators (Probability of Detection and False Alarm Ratio). APHRODITE consistently performed well in several basins with high r values and low RMSE values, but had positive or negative bias values in different basins. CMORPH had the lowest positive bias value in the Ganga_Brahmaputra basin, while GPCC showed the largest r value and lowest RMSE value in the Sindha basin. CHIRPS performed well in Afghanistan, but had positive bias values. GPCC performed well in Myanmar and Pakistan, but had negative or positive bias values. APHRODITE performed consistently well in Nepal, but had negative bias values. Overall, the performance of different gridded precipitation products varies depending on the country and type of evaluation.
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