An assessment of gridded precipitation products over High Mountain Asia

被引:6
|
作者
Dollan, Ishrat J. [1 ]
Maina, Fadji Z. [2 ,3 ]
Kumar, Sujay V. [3 ]
Nikolopoulos, Efthymios I. [4 ]
Maggioni, Viviana [1 ]
机构
[1] George Mason Univ, Dept Civil Environm & Infrastruct Engn, Fairfax, VA 22030 USA
[2] NASA Goddard Space Flight Ctr, Hydrol Sci Lab, Greenbelt, MD USA
[3] Univ Space Res Assoc, Goddard Earth Sci Technol & Res Studies & Invest, Columbia, MD USA
[4] Rutgers State Univ, Dept Civil & Environm Engn, New Brunswick, NJ USA
基金
美国国家航空航天局;
关键词
Validation; High Mountain Asia; Precipitation products; Seasons; Ensemble products; GLOBAL PRECIPITATION; GAUGE OBSERVATIONS; TIBETAN PLATEAU; SATELLITE; RAINFALL; RESOLUTION; CLIMATE; PERFORMANCE; MICROWAVE; ENSEMBLE;
D O I
10.1016/j.ejrh.2024.101675
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Study region: High Mountain Asia Study focus: The study assesses five high-resolution gridded precipitation products against observations taken at twenty-seven weather stations across High Mountain Asia (HMA), one of the world's most complex and data scarce regions. Estimating spatiotemporal patterns of average and extreme precipitation in HMA is challenged by several factors, including the lack of ground observations, the diverse climate zones, and the sharp orographic gradients. Evaluating the quality and reliability of multi-source precipitation products before analyzing their trends and patterns is fundamental in such a region. A suite of high-resolution satellite-based product (the Climate Hazards Group Infrared Precipitation with Stations, CHIRPS, and the Integrated MultisatellitE Retrievals for Global Precipitation Measurement, IMERG), model reanalysis precipitation estimates (European Centre for Medium-Range Weather Forecasts, fifth generation atmospheric reanalysis product, ERA5), and their blended product (ensemble mean EM and a localized probability matched mean, LPM) are evaluated on a daily scale from 2001 to 2008. The performance of each product is analyzed in relation to elevation, seasonal accumulation, and extreme indices (e.g., frequency of wet days and consecutive wet days). New Hydrological Insights for the Region: Results show that reanalysis products present the largest overestimation, satellite retrievals the lowest, and ensemble products' performance is encapsulated in between. LPM carries a high bias especially during winter when satellite estimates struggle to capture solid precipitation. The two ensemble products show higher correlations with the ground observations and smaller uncertainties in the error metrics than the original products.
引用
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页数:16
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