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首页> 外文期刊>Journal of hydrometeorology >Statistical evaluation of combined daily gauge observations and rainfall satellite estimates over continental South America
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Statistical evaluation of combined daily gauge observations and rainfall satellite estimates over continental South America

机译：南美大陆地区每日标准观测值与降雨量卫星估计值的组合的统计评估

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摘要

This paper describes a comprehensive assessment of a new high-resolution, gauge-satellite-based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes to get the lowest bias when compared with the observed values (rain gauges). Intercomparisons and cross-validation tests have been carried out between independent rain gauges and different merging techniques. This validation process was done for the control algorithm [Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis real-time algorithm] and five different merging schemes: additive bias correction; ratio bias correction; TRMM Multisatellite Precipitation Analysis, research version; and the combined scheme proposed in this paper. These methodologies were tested for different months belonging to different seasons and for different network densities. All compared, merging schemes produce better results than the control algorithm; however, when finer temporal (daily) and spatial scale (regional networks) gauge datasets are included in the analysis, the improvement is remarkable. The combined scheme consistently presents the best performance among the five techniques tested in this paper. This is also true when a degraded daily gauge network is used instead of a full dataset. This technique appears to be a suitable tool to produce real-time, high-resolution, gauge- and satellite-based analyses of daily precipitation over land in regional domains.
机译：本文介绍了一项新的高分辨率评估，该评估基于高分辨率，基于星际卫星的南美洲2004年每日降水分析。该方法基于加性和乘性偏差校正方案的组合，在比较时获得最低偏差与观察值（雨量计）。在独立的雨量计和不同的合并技术之间已经进行了比对和交叉验证测试。该验证过程是针对控制算法[热带降雨测量任务（TRMM）多卫星降水分析实时算法]和五种不同的合并方案完成的：加性偏差校正;比率偏差校正; TRMM多卫星降水分析，研究版本;以及本文提出的组合方案。这些方法论针对不同季节的不同月份和不同网络密度进行了测试。综上所述，合并方案比控制算法产生更好的结果。但是，当分析中包含更精细的时间（每日）和空间比例（区域网络）量表数据集时，改进效果显着。在本文测试的五种技术中，组合方案始终呈现最佳性能。当使用降级的日规网络而不是完整的数据集时，也是如此。这项技术似乎是产生实时，高分辨率，基于量表和卫星的区域区域每日降水量分析的合适工具。

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