青藏高原的降水数据主要由遥感产品和多源观测数据融合产生,由于青藏高原的观测站点分布稀疏不均,遥感数据误差较大,因此常用的CMORPH(Climate Prediction Center Morphing Technique)等降水数据集精度有限。通过K最近邻(K-Nearest Neig...青藏高原的降水数据主要由遥感产品和多源观测数据融合产生,由于青藏高原的观测站点分布稀疏不均,遥感数据误差较大,因此常用的CMORPH(Climate Prediction Center Morphing Technique)等降水数据集精度有限。通过K最近邻(K-Nearest Neighbor,简称KNN)模型,可以建立环境(海拔、坡度、坡向、植被)、气象因子(气温、湿度、风速)和日降水量的关系,从而订正青藏高原的CMORPH日降水数据集,提高数据精度。对CMORPH日降水数据的误差分析表明,采用KNN模型订正后的CMORPH降水数据优于原始数据和采用PDF(Probability Density Function Matching Method)法订正的CMORPH数据,且空间分布较好地符合青藏高原的降水分布特征。展开更多
利用青藏高原77个地面台站的2003年~2009年夏季(6月~9月)的降水资料,对月尺度和年尺度上CMORPH(Climate Prediction Center morphing)多卫星降水数据的精度进行研究,并引入Sokol模型对年尺度上的CMORPH数据进行修正,旨在为基于卫星降水...利用青藏高原77个地面台站的2003年~2009年夏季(6月~9月)的降水资料,对月尺度和年尺度上CMORPH(Climate Prediction Center morphing)多卫星降水数据的精度进行研究,并引入Sokol模型对年尺度上的CMORPH数据进行修正,旨在为基于卫星降水数据的青藏高原地区气候、水文等方面的研究提供科学依据。研究结果表明:1CMORPH数据对青藏高原降水的时间变化趋势和空间变化趋势的模拟精度较低,且存在明显的时空不稳定性。2不同时间尺度的CMORPH数据在青藏高原东南部的模拟精度要高于其他地区,而喜马拉雅山脉北麓以及青藏高原东北部的模拟精度最低。3CMORPH年数据存在明显的高值高估、低值低估的现象,其模拟值与误差之间的相关系数均在0.53以上。4经过Sokol模型修正后,CMORPH年数据均方根误差明显降低,而相关系数均有不同程度的提高,表明该模型能够提高CMORPH数据对青藏高原地区降水的模拟精度。展开更多
Daily precipitation amounts and frequencies from the CMORPH （Climate Prediction Center Morphing Technique） and TRMM （Tropical Rainfall Measuring Mission） 3B42 precipitation products are validated against warm seas...Daily precipitation amounts and frequencies from the CMORPH （Climate Prediction Center Morphing Technique） and TRMM （Tropical Rainfall Measuring Mission） 3B42 precipitation products are validated against warm season in-situ precipitation observations from 2003 to 2008 over the Tibetan Plateau and the regions to its east. The results indicate that these two satellite datasets can better detect daily precipitation frequency than daily precipitation amount. The ability of CMORPH and TRMM 3B42 to accurately detect daily precipitation amount is dependent on the underlying terrain. Both datasets are more reliable over the relatively flat terrain of the northeastern Tibetan Plateau, the Sichuan basin, and the mid-lower reaches of the Yangtze River than over the complex terrain of the Tibetan Plateau. Both satellite products are able to detect the occurrence of daily rainfall events; however, their performance is worse in regions of complex topography, such as the Tibetan Plateau. Regional distributions of precipitation amount by precipitation intensity based on TRMM 3B42 are close to those based on rain gauge data. By contrast, similar distributions based on CMORPH differ substantially. CMORPH overestimates the amount of rain associated with the most intense precipitation events over the mid-lower reaches of the Yangtze River while underestimating the amount of rain associated with lighter precipitation events. CMORPH underestimates the amount of intense precipitation and overestimates the amount of lighter precipitation over the other analyzed regions. TRMM 3B42 underestimates the frequency of light precipitation over the Sichuan basin and the mid-lower reaches of the Yangtze River. CMORPH overestimates the frequencies of weak and intense precipitation over the mid-lower reaches of the Yangtze River, and underestimates the frequencies of moderate and heavy precipitation. CMORPH also overestimates the frequency of light precipitation and underestimates the frequency of intense precipitation over the other three regions. The TRMM 3B42 product provides better characterizations of the regional gamma distributions of daily precipitation amount than the CMORPH product, for which the cumulative distribution functions are biased toward lighter precipitation events.展开更多
文摘青藏高原的降水数据主要由遥感产品和多源观测数据融合产生,由于青藏高原的观测站点分布稀疏不均,遥感数据误差较大,因此常用的CMORPH(Climate Prediction Center Morphing Technique)等降水数据集精度有限。通过K最近邻(K-Nearest Neighbor,简称KNN)模型,可以建立环境(海拔、坡度、坡向、植被)、气象因子(气温、湿度、风速)和日降水量的关系,从而订正青藏高原的CMORPH日降水数据集,提高数据精度。对CMORPH日降水数据的误差分析表明,采用KNN模型订正后的CMORPH降水数据优于原始数据和采用PDF(Probability Density Function Matching Method)法订正的CMORPH数据,且空间分布较好地符合青藏高原的降水分布特征。
文摘利用青藏高原77个地面台站的2003年~2009年夏季(6月~9月)的降水资料,对月尺度和年尺度上CMORPH(Climate Prediction Center morphing)多卫星降水数据的精度进行研究,并引入Sokol模型对年尺度上的CMORPH数据进行修正,旨在为基于卫星降水数据的青藏高原地区气候、水文等方面的研究提供科学依据。研究结果表明:1CMORPH数据对青藏高原降水的时间变化趋势和空间变化趋势的模拟精度较低,且存在明显的时空不稳定性。2不同时间尺度的CMORPH数据在青藏高原东南部的模拟精度要高于其他地区,而喜马拉雅山脉北麓以及青藏高原东北部的模拟精度最低。3CMORPH年数据存在明显的高值高估、低值低估的现象,其模拟值与误差之间的相关系数均在0.53以上。4经过Sokol模型修正后,CMORPH年数据均方根误差明显降低,而相关系数均有不同程度的提高,表明该模型能够提高CMORPH数据对青藏高原地区降水的模拟精度。
基金Supported by the National Natural Science Foundation of China (41175080)National Basic Research and Development (973) Program of China (2012CB417205)Meteorological Key Technology Integration and Application Program (CMAGJ2011Z08)
文摘Daily precipitation amounts and frequencies from the CMORPH （Climate Prediction Center Morphing Technique） and TRMM （Tropical Rainfall Measuring Mission） 3B42 precipitation products are validated against warm season in-situ precipitation observations from 2003 to 2008 over the Tibetan Plateau and the regions to its east. The results indicate that these two satellite datasets can better detect daily precipitation frequency than daily precipitation amount. The ability of CMORPH and TRMM 3B42 to accurately detect daily precipitation amount is dependent on the underlying terrain. Both datasets are more reliable over the relatively flat terrain of the northeastern Tibetan Plateau, the Sichuan basin, and the mid-lower reaches of the Yangtze River than over the complex terrain of the Tibetan Plateau. Both satellite products are able to detect the occurrence of daily rainfall events; however, their performance is worse in regions of complex topography, such as the Tibetan Plateau. Regional distributions of precipitation amount by precipitation intensity based on TRMM 3B42 are close to those based on rain gauge data. By contrast, similar distributions based on CMORPH differ substantially. CMORPH overestimates the amount of rain associated with the most intense precipitation events over the mid-lower reaches of the Yangtze River while underestimating the amount of rain associated with lighter precipitation events. CMORPH underestimates the amount of intense precipitation and overestimates the amount of lighter precipitation over the other analyzed regions. TRMM 3B42 underestimates the frequency of light precipitation over the Sichuan basin and the mid-lower reaches of the Yangtze River. CMORPH overestimates the frequencies of weak and intense precipitation over the mid-lower reaches of the Yangtze River, and underestimates the frequencies of moderate and heavy precipitation. CMORPH also overestimates the frequency of light precipitation and underestimates the frequency of intense precipitation over the other three regions. The TRMM 3B42 product provides better characterizations of the regional gamma distributions of daily precipitation amount than the CMORPH product, for which the cumulative distribution functions are biased toward lighter precipitation events.
