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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >Downscaling satellite-derived daily precipitation products with an integrated framework
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Downscaling satellite-derived daily precipitation products with an integrated framework

机译:具有综合框架的透露卫星衍生的每日降水量

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摘要

Spatially downscaling satellite precipitation products have been performed on annual and monthly precipitation. Accurate downscaling on daily precipitation remains a challenge due to the limitation of the downscaling assumption, the large spatial discontinuity of daily precipitation, and the relatively poor quality of satellite-derived daily precipitation product. In this study, an integrated downscaling-fusion framework was proposed and used to downscale satellite-derived daily precipitation. First, a spatio-temporal downscaling scheme is applied to produce preliminary downscaled daily precipitation. The accuracy of the derived preliminary results is then boosted by merging with daily gauge observations using an ensemble fusion method. The performance of the proposed framework was tested and evaluated by downscaling the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) daily precipitation data from 0.1 to 0.01 degrees over eastern and central China for the period of 2015-2016. The results showed that (a) the downscaling scheme accurately mapped the spatio-temporal variation in daily precipitation, and the preliminary downscaled results perfectly maintained the accuracy of the original IMERG data; (b) the fused results were much more accurate than the original IMERG data, decreasing the root-mean-square errors (RMSEs) by 22, 10, and 18% at daily, monthly, and annual timescales, respectively, for the whole period; and (c) the fused daily precipitation data considerably strengthened the detection of rain/no rain area compared with the original IMERG daily precipitation data, with a 17% reduction in the inconsistency index.
机译:已经对年度和月度降水进行了空间较低的卫星降水产品。由于较低的假设限制,日降水量的大量空间不连续性以及卫星衍生的每日沉淀产品的较差质量,准确地降水量仍然是一个挑战。在该研究中,提出了一种集成的俯卧型融合框架并用于低估卫星衍生的每日降水。首先,应用时空缩小方案来产生初步较低的每日降水。然后通过使用集合融合方法与日常仪表观测合并来提高衍生的初步结果的准确性。通过在2015 - 2016年东部和中部的全球降水测量(IMERR)每日降水数据下,对全球降水测量(IMERG)的集成多卫星检索进行了测试和评估了拟议的框架的性能。结果表明,(a)较低的方案准确地绘制了日常降水量的时空变化,初步缩小结果完美地保持了原始IMerc数据的准确性; (b)融合的结果比原来的IMERD数据更准确,在整个时期分别在每日,月度和年度时间尺度下减少22,10和18%的根均方误差(RMSE) ; (c)与原始的IMERG日降水数据相比,融合日降水量数据大大加强了雨/无雨区的检测,不一致的17%减少了17%。

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