中文摘要：

运用1998-2012年青藏高原的TRMM 3B43降水数据以及气象台站实测降水数据,对比分析了青藏高原地区TRMM 3B43降水数据偏差分布规律。结果表明：（1）TRMM 3B43降水数据在青藏高原地区存在明显误差,特别是降水量大的地区和月份,偏差量较大。（2）青藏高原地区TRMM 3B43降水数据偏差分布与海拔、经纬度、降水量存在密切的关系。用偏差分布规律,加法修正法结合随机森林算法对青藏高原地区TRMM 3B43降水数据进行了校准。经过校准之后,数据精度得到显著提高,有效增加了数据的可用性,多年月平均数据决定系数R2最大可达到0.9（3、10月）,最小也接近于0.5（12月）,效率系数E均为正值,最大可达到90（3、10月）;多年季平均和多年平均降水数据中除了第一季度结果稍差外（决定系数R2为0.58）,其余数据校准效果均较好。

英文摘要：

Precipitation is a vital element of the water cycle in the Earth System,which is closely related to the ecological,hydrological,and meteorological processes. Because of the special topographical and climatic conditions,the Tibetan Plateau has great influence in regional and atmospheric circulation patterns. And the hydrology cycle in the Plateau is an important aspect of study for thermal forcing effect on regional climate. Furthermore,various surface features on the Plateau（e.g. vegetation）have a close relationship with precipitation. So it is meaningful to study the precipitation of the Tibetan Plateau. Owing to the lack of ground observations,it is difficult to study the spatial and temporal patterns of precipitation over the plateau. The satellite remote sensing technology can be utilized to fill in the gaps where station data are not available. There are already a series of regional and global remote sensing precipitation products. The Tropical Rainfall Measuring Mission（TRMM）is one of the highest resolution（0.25°×0.25°）products among all the current satellite precipitation datasets. Unfortunately,because of the influence of the terrain and atmospheric condition,the accuracy of it is not very ideal in northwest mountainous areas of China. So it is critical to find a method to calibrate it for further use. Comparing to rain-gauges observed precipitation dataset collected from China Meteorological Data Sharing Service System,the TRMM 3B43 precipitation data over the Tibetan Plateau have some deviation. This paper analyzed the deviation and found it closely related to altitude,latitude,and longitude and precipitation distribution. Supposing that the rain-gauges observed precipitation data are accurate,point-based deviation between original TRMM precipitation and rain-gauge observed precipitation can be calculated. Then surface-based deviation can be obtained using some interpolation algorithm such as Kriging. What is noted above is called addictive correction method. In this paper,originally TRMM