首页|雅鲁藏布江流域TRMM降水数据降尺度研究

雅鲁藏布江流域TRMM降水数据降尺度研究

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为了获取我国西南典型缺资料地区雅鲁藏布江流域较高时空分辨率的降水空间分布数据,开展了复杂地形条件下的卫星降水资料降尺度方法研究.构建了基于TRMM降水数据的雅鲁藏布江流域降水时空降尺度模型,并利用搜集的降水实测数据对模型进行了率定和精度验证,结果表明:1)研究提出的水汽运移距离因子在雅江流域与降水具有很强的相关性,在构建的空间降尺度模型中其显著性优于传统地形指示因子DEM;2)TRMM降尺度结果较原始降水数据空间分布更为合理性且细节刻画能力更强,但统计精度月际差异明显,月R2值主要集中在0.5~0.9之间,RMSE值在3.7~40 mm之间波动,且整体呈现随月降雨量增加而增大的趋势,个别月份由于降水观测极值出现而导致R2值不足0.1.日尺度上,降尺度结果受原始TRMM降水数据精度影响,平均精度R2不足0.3.
TRMM precipitation downscaling in the data scarce Yarlung Zangbo River basin
Moisture migration distance (MMD) and NDVI were used to build a model of TRMM (tropical rainfall measuring mission)precipitation spatial-temporal downscaling for higher temporal-spatial resolution rainfall data production in the data scarce Yalung Zangbo river basin.The model was calibrated and validated using collected station observations in the area.MMD was found to correlate strongly with precipitation in the basin and better significance and representativeness was noted than traditional terrain factor DEM,and could eventually replace DEM in final spatial downscaling model;Accuracy of downscaled TRMM precipitation was found to vary significantly.The monthly R2 between downscaled and observed precipitation also varied from 0.5~0.9.RMSE fluctuated between 3.7 mm and 40 mm.R2 value was no more than 0.1 in some months due to observed extremes.Due to the poor accuracy of original TRMM daily precipitation in this area,the downscaled daily result showed less consistency with the observations,and the R2 was no more than 0.3 at all stations.

downscalingmoisture migration DistanceNDVITRMMYarlung Zangbo River

蔡明勇、吕洋、杨胜天、周秋文

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环境保护部卫星环境应用中心,100094,北京

北京师范大学地理学与遥感科学学院,100875,北京

贵州师范大学地理与环境科学学院,550001,贵州贵阳

降尺度 水汽运移距离 NDVI TRMM 雅鲁藏布江

国家自然科学基金资助项目国家自然科学基金资助项目国家自然科学基金资助项目国家863资助项目

4160147141271414416713622012AA12A310

2017

北京师范大学学报(自然科学版)
北京师范大学

北京师范大学学报(自然科学版)

CSTPCDCSCD北大核心
影响因子:0.505
ISSN:0476-0301
年,卷(期):2017.53(1)
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