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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling-calibration procedure
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First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling-calibration procedure

机译：第7版TRMM 3B43沉淀产品与新的按比例缩小校准程序相结合的第一个结果

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摘要

Accurate precipitation data at high spatial and temporal resolution is deemed necessary for many hydrological and water management applications, and especially in data scarce river basins and regions where strong competition for water resources prevails. In this study we used a new downscaling-calibration procedure of the freely accessible Version 7 of TRMM (Tropical Rainfall Measuring Mission) 3B43 product, in conjunction with limited rain gauge data sets, to generate improved monthly pixel-based precipitation data at higher spatial resolution (1km). The spatial downscaling from 0.25° to 1km grids was achieved by using site-specific non-linear relationships between annual precipitation and annually averaged NDVI (Normalized Difference Vegetation Index). The calibration was based on Geograhical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA). The new integrated procedure was tested for Lake Tana Basin (LTB) in Ethiopia with a humid climate (rainfall 1395 mm/yr during 1998-2004) and for the Caspian Sea Region (CSR) in Iran with a semi-arid climate (rainfall 442 mm/yr during 1999-2003). The best 1km annual precipitation data were achieved through downscaling followed by GDA calibration for most cases. The monthly fractions derived from the un-calibrated TRMM 3B43 product can be used to disaggregate 1km annual precipitation to 1km monthly precipitation. The disaggregated 1km monthly precipitation has not only significant improvement in the spatial resolution, but also good agreements with rain gauge data were achieved for both LTB (R~2=0.87, RMSE=56mm, MAE=32mm and Bias=0.01) and the CSR (R~2=0.79, RMSE=23mm, MAE=16mm and Bias=0.14). A similar calibration procedure using rain gauges at monthly time scale did not improve the level of performance.
机译：在许多水文和水管理应用中，特别是在数据稀缺的流域和水资源争夺盛行的地区，必须以高时空分辨率获得准确的降水数据。在这项研究中，我们使用了TRMM（热带降雨测量任务）3B43产品的第7版的新的按比例缩小校准程序，并结合有限的雨量计数据集，以更高的空间分辨率生成了改进的基于像素的月度降水量数据。 （1公里）。通过使用年降水量与年平均NDVI（归一化植被指数）之间特定位置的非线性关系，可以实现从0.25°到1km网格的空间缩小。校准基于地理差异分析（GDA）和地理比例分析（GRA）。新的集成程序已在气候潮湿的埃塞俄比亚塔纳湖盆地（LTB）（1998-2004年降雨1395毫米/年）和伊朗的里海区域（CSR）半干旱气候（降雨442）进行了测试毫米/年（1999-2003年）。在大多数情况下，通过缩小比例，然后通过GDA校准，可获得最佳的1 km年降水量数据。由未校准的TRMM 3B43产品得出的月度分数可用于将1公里的年降水量分解为1公里的月降水量。 LTB（R〜2 = 0.87，RMSE = 56mm，MAE = 32mm和Bias = 0.01）和CSR的分解的1km月降水量不仅在空间分辨率上有显着改善，而且与雨量计数据也达成了良好的协议（R〜2 ＝ 0.79，RMSE ＝ 23mm，MAE ＝ 16mm和偏置＝ 0.14）。在月度尺度上使用雨量计进行类似的校准程序并不能提高性能水平。

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