Intercomparison of Gridded Precipitation Datasets over a Sub-Region of the Central Himalaya and the Southwestern Tibetan Plateau
Intercomparison of Gridded Precipitation Datasets over a Sub-Region of the Central Himalaya and the Southwestern Tibetan Plateau
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DOI：
10.3390/w12113271
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发表时间：
2020-11
期刊：
影响因子：
3.4
通讯作者：
Alexandra Hamm;A. Arndt;Christine Kolbe;Xun Wang;B. Thies;Oleksiy Boyko;P. Reggiani;D. Scherer-D.-Scher
中科院分区：
文献类型：
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作者：
Alexandra Hamm;A. Arndt;Christine Kolbe;Xun Wang;B. Thies;Oleksiy Boyko;P. Reggiani;D. Scherer-D.-Scher
降水量是水文气象研究和应用的中心量。特别是在地形复杂的地区，如亚洲高山地区（High Mountain Asia，HMA），地面降水观测很少。网格化降水产品是克服地面实况观测局限性的一种方法。它们可以提供在空间和时间上连续的数据集。然而，有许多产品可用，它们使用各种方法来生成数据，并导致不同的降水值。在我们的研究中，我们比较了2017年5月至9月喜马拉雅中部和青藏高原西南部一个次区域的9种不同来源的不同网格降水产品（ERA 5，ERA 5-Land，ERA-interim，HAR v2 10 km，HAR v2 2 km，JRA-55，MERRA-2，GPCC和PRETIP）。在研究期间的总空间平均降水量范围从411毫米（GPCC）到781毫米（ERA中期），平均值为623毫米，标准差为132毫米。我们发现，网格化的产品和少数观测，除了少数例外，是一致的，彼此之间关于降水的变化和研究区域内的粗略金额。很明显，较高的网格分辨率可以更好地解决极端降水，导致整体较低的平均降水空间，但较高的极端降水事件。我们还发现，通常较高的地形复杂性导致产品之间的降水量差异较大。由于产品之间在空间和时间上的巨大差异，我们建议根据应用类型和具体研究问题仔细选择用作任何研究应用输入的产品。虽然粗略的产品，如ERA-Interim或ERA 5，覆盖较长的时间，但具有粗网格分辨率，以前已被证明能够捕捉长期趋势，并有助于识别气候变化特征，但这项研究表明，更多的区域应用，如冰川质量平衡建模，需要更高的空间分辨率，例如，在HAR v2 10 km中再现。
Precipitation is a central quantity of hydrometeorological research and applications. Especially in complex terrain, such as in High Mountain Asia (HMA), surface precipitation observations are scarce. Gridded precipitation products are one way to overcome the limitations of ground truth observations. They can provide datasets continuous in both space and time. However, there are many products available, which use various methods for data generation and lead to different precipitation values. In our study we compare nine different gridded precipitation products from different origins (ERA5, ERA5-Land, ERA-interim, HAR v2 10 km, HAR v2 2 km, JRA-55, MERRA-2, GPCC and PRETIP) over a subregion of the Central Himalaya and the Southwest Tibetan Plateau, from May to September 2017. Total spatially averaged precipitation over the study period ranged from 411 mm (GPCC) to 781 mm (ERA-Interim) with a mean value of 623 mm and a standard deviation of 132 mm. We found that the gridded products and the few observations, with few exceptions, are consistent among each other regarding precipitation variability and rough amount within the study area. It became obvious that higher grid resolution can resolve extreme precipitation much better, leading to overall lower mean precipitation spatially, but higher extreme precipitation events. We also found that generally high terrain complexity leads to larger differences in the amount of precipitation between products. Due to the considerable differences between products in space and time, we suggest carefully selecting the product used as input for any research application based on the type of application and specific research question. While coarse products such as ERA-Interim or ERA5 that cover long periods but have coarse grid resolution have previously shown to be able to capture long-term trends and help with identifying climate change features, this study suggests that more regional applications, such as glacier mass-balance modeling, require higher spatial resolution, as is reproduced, for example, in HAR v2 10 km.