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Agreement between monthly precipitation estimates from TRMM satellite, NCEP reanalysis, and merged gauge‐satellite analysis

机译:TRMM卫星的月降水估算,NCEP再分析和轨距合并分析之间的一致性

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Global monthly precipitation is a critical element in understanding variability of the Earth’s climate including changes in the hydrological cycle associated with global warming. The NCEP reanalysis (R1), GPCP, CMAP, and TMPA precipitation data sets are often used in climate studies. This study compares the data sets (R1, GPCP, CMAP, and TMPA) with the TRMM precipitation data sets derived from the TRMM precipitation radar (TPR), microwave imager (TMI), and combined algorithm (TCA) for 11 years (1998–2008) over the satellite’s domain (40°S–40°N). The domain precipitation estimates from seven data sets range from 2.44 to 3.38 mm d~(-1)x over the ocean and from 1.98 to 2.83 mm d~(-1) over land. The regional differences between the TPR and the other data sets are analyzed by a paired t test. Particularly, statistically significant differences between TPR and GPCP and between TPR and CMAP are found in most oceanic regions and in some land areas. In general, there exists substantial disagreement in precipitation intensities from the precipitation data sets. Therefore, significant consideration is given to the uncertainties in the data sets prior to applying the results to climate studies such as estimations of the global hydrological budget analyses. Meanwhile, the anomalies from all the data sets agree relatively well in their variability patterns. It is also found that the dominant mode of interannual variability which is associated with the ENSO pattern is clearly demonstrated by all precipitation data sets. These results suggest that all considered precipitation data sets may produce similar results when they are used for climate variability analyses on annual to interannual time scales.
机译:全球每月降水量是理解地球气候多变性的关键因素,包括与全球变暖有关的水文循环变化。 NCEP重新分析(R1),GPCP,CMAP和TMPA降水数据集通常用于气候研究。本研究将数据集(R1,GPCP,CMAP和TMPA)与从TRMM降水雷达(TPR),微波成像仪(TMI)和组合算法(TCA)获得的TRMM降水数据集进行了11年的比较(1998年– 2008年)在卫星范围内(40°S–40°N)。来自七个数据集的区域降水估计范围在海洋上范围从2.44至3.38 mm d〜(-1)x,在陆地上范围从1.98至2.83 mm d〜(-1)x。通过配对的t检验分析TPR和其他数据集之间的区域差异。特别是,在大多数海洋区域和某些陆地地区,TPR和GPCP之间以及TPR和CMAP之间在统计上存在显着差异。通常,从降水数据集来看,降水强度存在很大分歧。因此,在将结果应用到气候研究(例如对全球水文预算分析的估计)之前,应充分考虑数据集的不确定性。同时,来自所有数据集的异常在其变异性模式中相对一致。还发现,所有降水数据集都清楚地表明了与ENSO模式相关的年际变化的主导模式。这些结果表明,将所有考虑的降水数据集用于年际至年际尺度的气候变异性分析时,都可能产生相似的结果。

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