空报数据和漏报数据是高时空分辨率卫星降水产品误差的重要表现形式,研究漏报和空报数据的特征对于改进降水反演算法、提高卫星降水数据的质量具有重要意义。通过对2009年6~8月中国区域内的CMORPH卫星数据(Climate Prediction Center Mo...空报数据和漏报数据是高时空分辨率卫星降水产品误差的重要表现形式,研究漏报和空报数据的特征对于改进降水反演算法、提高卫星降水数据的质量具有重要意义。通过对2009年6~8月中国区域内的CMORPH卫星数据(Climate Prediction Center Morphing)与观测站点逐小时降水数据分析,发现CMOPRH数据中的漏报数据和空报数据存在以下特征:①CMORPH数据中空报数据远远高于漏报数据,导致CMORPH数据模拟的降水面积要高于实际降水面,表明空报数据对CMORPH精度的影响要大于漏报数据;②当降水量小于5mm时,CMORPH的空报率随着降水量的升高呈现出非线性的下降趋势,经过二次项拟合之后的相关系数达到0.99以上;③CMORPH中空报降水数据的面积与总降水面积之间存在很强的正相关性,二者在6~8月的相关系数分别达到0.9133、0.9474和0.9482,因此可以通过CMORPH数据的总降水面积对空报降水面积进行估算;④从CMORPH空报率的空间分布上看,我国东南沿海以及东北地区的空报率较低,而西北、青藏高原地区的空报率最高。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
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
Based on the satellite data from the Climate Prediction Center morphing(CMORPH) at very high spatial and temporal resolution, the effects of urbanization on precipitation were assessed over the Pearl River Delta(PRD) ...Based on the satellite data from the Climate Prediction Center morphing(CMORPH) at very high spatial and temporal resolution, the effects of urbanization on precipitation were assessed over the Pearl River Delta(PRD) metropolitan regions of China. CMORPH data well estimates the precipitation features over the PRD. Compared to the surrounding rural areas, the PRD urban areas experience fewer and shorter precipitation events with a lower precipitation frequency(ratio of rainy hours, about 3 days per year less); however, short-duration heavy rain events play a more significant role over the PRD urban areas. Afternoon precipitation is much more pronounced over the PRD urban areas than the surrounding rural areas, which is probably because of the increase in short-duration heavy rain over urban areas.展开更多
The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Bas...The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products(3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42 RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions,respectively, and CMORPH performs better than 3B42 RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement(GPM) data in the future.展开更多
The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMO...The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMORPH） are two important multi-satellite precipitation products in TRMM-era and perform important functions in GPM-era. Both TMPA and CMORPH systems simultaneously upgraded their retrieval algorithms and released their latest version of precipitation data in 2013. In this study, the latest TMPA and CMORPH products （i.e., Version-7 real-time TMPA （T-rt） and gauge-adjusted TMPA （T-adj）, and Version- 1.0 real-time CMORPH （C-rt） and Version-l.0 gauge-adjusted CMORPH （C-adj）） are evaluated and intercompared by using independent rain gauge observations for a 12-year （2000--2011） period over two typical basins in China with different geographical and climate conditions. Results indicate that all TMPA and CMORPH products tend to overestimate precipitation for the high-latitude semiarid Laoha River Basin and underestimate it for the low-latitude humid Mishui Basin. Overall, the satellite precipitation products exhibit superior performance over Mishui Basin than that over Laoha River Basin. The C-adj presents the best performance over the high-latitude Laoha River Basin, whereas T-adj showed the best performance over the low-latitude Mishui Basin. The two gauge-adjusted products demonstrate potential in water resource management. However, the accuracy of two real-time satellite precipitation products demonstrates large variability in the two validation basins. The C-rt reaches a similar accuracy level with the gauge-adjusted satellite precipitation products in the high-latitude Laoha River Basin, and T-rt performs well in the low-latitude Mishui Basin. The study also reveals that all satellite precipitation products obviously overestimate light rain amounts and events over Laoha River Basin, whereas they underestimate the amount and events over Mishui Basin. The findings of the precision characteristics associated with the latest TMPA and CMORPH precipitation products at different basins will offer satellite pre- cipitation users an enhanced understanding of the applicability of the latest TMPA and CMORPH for water resource management, hydrologic process simulation, and hydrometeorological disaster prediction in other similar regions in China. The findings will also be useful for IMERG algorithm development and update in GPM-era.展开更多
文摘空报数据和漏报数据是高时空分辨率卫星降水产品误差的重要表现形式,研究漏报和空报数据的特征对于改进降水反演算法、提高卫星降水数据的质量具有重要意义。通过对2009年6~8月中国区域内的CMORPH卫星数据(Climate Prediction Center Morphing)与观测站点逐小时降水数据分析,发现CMOPRH数据中的漏报数据和空报数据存在以下特征:①CMORPH数据中空报数据远远高于漏报数据,导致CMORPH数据模拟的降水面积要高于实际降水面,表明空报数据对CMORPH精度的影响要大于漏报数据;②当降水量小于5mm时,CMORPH的空报率随着降水量的升高呈现出非线性的下降趋势,经过二次项拟合之后的相关系数达到0.99以上;③CMORPH中空报降水数据的面积与总降水面积之间存在很强的正相关性,二者在6~8月的相关系数分别达到0.9133、0.9474和0.9482,因此可以通过CMORPH数据的总降水面积对空报降水面积进行估算;④从CMORPH空报率的空间分布上看,我国东南沿海以及东北地区的空报率较低,而西北、青藏高原地区的空报率最高。
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。
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。
基金supported by the National Natural Science Foundation of China(41375050)
文摘Based on the satellite data from the Climate Prediction Center morphing(CMORPH) at very high spatial and temporal resolution, the effects of urbanization on precipitation were assessed over the Pearl River Delta(PRD) metropolitan regions of China. CMORPH data well estimates the precipitation features over the PRD. Compared to the surrounding rural areas, the PRD urban areas experience fewer and shorter precipitation events with a lower precipitation frequency(ratio of rainy hours, about 3 days per year less); however, short-duration heavy rain events play a more significant role over the PRD urban areas. Afternoon precipitation is much more pronounced over the PRD urban areas than the surrounding rural areas, which is probably because of the increase in short-duration heavy rain over urban areas.
基金supported by the Programme of Introducing Talents of Discipline to Universities(the 111 Project,Grant No.B08048)the National Natural Science Foundation of China(Grant No.41501017)the Natural Science Foundation of Jiangsu Province(Grant No.BK20150815)
文摘The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products(3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42 RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions,respectively, and CMORPH performs better than 3B42 RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement(GPM) data in the future.
基金Under the auspices of Programme of Introducing Talents of Discipline to Universities by Ministry of Education and the State Administration of Foreign Experts Affairs, China (the 111 Project, No. B08048)National Natural Science Foundation of China (No. 41501017)Natural Science Foundation of Jiangsu Province (No. BK20150815)
文摘The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMORPH） are two important multi-satellite precipitation products in TRMM-era and perform important functions in GPM-era. Both TMPA and CMORPH systems simultaneously upgraded their retrieval algorithms and released their latest version of precipitation data in 2013. In this study, the latest TMPA and CMORPH products （i.e., Version-7 real-time TMPA （T-rt） and gauge-adjusted TMPA （T-adj）, and Version- 1.0 real-time CMORPH （C-rt） and Version-l.0 gauge-adjusted CMORPH （C-adj）） are evaluated and intercompared by using independent rain gauge observations for a 12-year （2000--2011） period over two typical basins in China with different geographical and climate conditions. Results indicate that all TMPA and CMORPH products tend to overestimate precipitation for the high-latitude semiarid Laoha River Basin and underestimate it for the low-latitude humid Mishui Basin. Overall, the satellite precipitation products exhibit superior performance over Mishui Basin than that over Laoha River Basin. The C-adj presents the best performance over the high-latitude Laoha River Basin, whereas T-adj showed the best performance over the low-latitude Mishui Basin. The two gauge-adjusted products demonstrate potential in water resource management. However, the accuracy of two real-time satellite precipitation products demonstrates large variability in the two validation basins. The C-rt reaches a similar accuracy level with the gauge-adjusted satellite precipitation products in the high-latitude Laoha River Basin, and T-rt performs well in the low-latitude Mishui Basin. The study also reveals that all satellite precipitation products obviously overestimate light rain amounts and events over Laoha River Basin, whereas they underestimate the amount and events over Mishui Basin. The findings of the precision characteristics associated with the latest TMPA and CMORPH precipitation products at different basins will offer satellite pre- cipitation users an enhanced understanding of the applicability of the latest TMPA and CMORPH for water resource management, hydrologic process simulation, and hydrometeorological disaster prediction in other similar regions in China. The findings will also be useful for IMERG algorithm development and update in GPM-era.
