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Evaluation of TRMM Precipitation Dataset over Himalayan Catchment: The Upper Ganga Basin, India

机译:喜马拉雅流域TRMM降水数据集的评估:印度恒河上游

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Satellite based rainfall estimation techniques have emerged as a potential alternative to ground based rainfall measurements. The Tropical Rainfall Measuring Mission (TRMM) precipitation, in particular, has been used in various climate and hydrology based studies around the world. While having wide possibilities, TRMM rainfall estimates are found to be inconsistent with the ground based rainfall measurements at various locations such as the southwest coast and Himalayan region of India, northeast parts of USA, Lake Victoria in Africa, La Plata basin in South America, etc. In this study, the applicability of TRMM estimates is evaluated over the Upper Ganga Basin (Himalayan catchment) by comparing against gauge-based India Meteorological Department (IMD) gridded precipitation records. Apart from temporal evaluation, the ability of TRMM in capturing spatial distribution is also examined using three statistical parameters namely correlation coefficient ( r ), mean absolute error (MAE) and relative bias (RBIAS). In the results, the dual nature of bias is evident in TRMM precipitation with rainfall magnitude falling in the range from 100 to 370 mm representing positive bias, whereas, rainfall magnitude above 400 mm, approximately, representing negative bias. The Quantile Mapping (QM) approach has been used to correct the TRMM dataset from these biases. The raw TRMM precipitation is found to be fairly correlated with IMD rainfall for post-monsoon and winter season with R 2 values of 0.65 and 0.57, respectively. The R 2 value of 0.41 is obtained for the monsoon season, whereas least correlation is found for the pre-monsoon season with an R 2 value of 0.24. Moreover, spatial distribution of rainfall during post-monsoon and winter season is captured adequately; however, the limited efficiency of TRMM is reflected for pre-monsoon and monsoon season. Bias correction has satisfactorily enhanced the spatial distribution of rainfall obtained from TRMM for almost all the seasons except for monsoon. Overall, the corrected TRMM precipitation dataset can be used for various climate analyses and hydrological water balance based studies in the Himalayan river basins.
机译:基于卫星的降雨估计技术已经成为基于地面的降雨测量的潜在替代方法。尤其是热带降雨测量团(TRMM)的降水已被全世界的各种基于气候和水文学的研究所采用。 TRMM降雨估算值的可能性很大,但在许多地方,例如印度西南海岸和印度喜马拉雅地区,美国东北部地区,非洲的维多利亚湖,南美的拉普拉塔盆地,在这项研究中,TRMM估算的适用性是通过与基于标准的印度气象部门(IMD)网格化降水记录进行比较来评估的,在恒河上游盆地(喜马拉雅流域)上。除了时间评估之外,还使用三个统计参数,即相关系数(r),平均绝对误差(MAE)和相对偏差(RBIAS),来检查TRMM捕获空间分布的能力。结果表明,在TRMM降水中,偏见具有双重性质,降雨量在100至370 mm范围内代表正偏,而高于400 mm的降雨量大约代表负偏。分位数映射(QM)方法已用于根据这些偏差校正TRMM数据集。发现季风后和冬季的原始TRMM降水与IMD降水相当相关,R 2值分别为0.65和0.57。季风季节的R 2值为0.41,而季风季节以前的相关性最小,R 2值为0.24。此外,季风季节和冬季降雨的空间分布得到了充分的捕捉;但是,TRMM效率有限反映在季风前和季风季节。偏差校正已令人满意地增强了除季风以外几乎所有季节从TRMM获得的降雨的空间分布。总体而言,校正后的TRMM降水数据集可用于喜马拉雅河流域的各种气候分析和基于水文水平衡的研究。

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