Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satel...Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis （TMPA; 3B43 V.6） product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index （SPI）, at the grid point （0.25°×0.25°） and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. （1） At the grid point spatial scale, in comparison with the monitoring results between rain gauges （SPIlg） and TMPA grid （SPIls）, both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index （CSI） are distributed in the middle stream of the Lancang River Basin. （2） The same as SPIls, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. （3） At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. （4） At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate （underestimate） the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.展开更多
A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation A...A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.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
Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite...Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite rainfall estimates have been very important sources for precipitation information, particularly in rain gauge-sparse regions. In this study, Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） products 3B42, RTV5V6, and RTV7 were evaluated for their applicability to the upper Yellow and Yangtze River basins on the Tibetan Plateau. Moreover, the capability of the TMPA products to simulate streamflow was also investigated using the Variable Infiltration Capacity （VIC） semi-distributed hydrological model. Results show that 3B42 performs better than RTVSV6 and RTV7, based on verification of the China Meteorological Administration （CMA） observational precipitation data. RTVSV6 can roughly capture the spatial precipitation pattern but overestimation exists throughout the entire study region. The anticipated improvements of RTV7 relative to RTVSV6 have not been realized in this study. Our results suggest that RTV7 significantly overestimates the precipitation over the two river basins, though it can capture the seasonal cycle features of precipitation. 3B42 shows the best performance in streamflow simulation of the abovementioned satellite products. Although involved in gauge adjustment at a monthly scale, 3B42 is capable of daily streamflow simulation. RTV5V6 and RTV7 have no capability to simulate streamflow in the upper Yellow and Yangtze River basins.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
This study presented a detailed comparison of daily precipitation estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network(PERSIANN) and Tropical Rainfall Measuring Missi...This study presented a detailed comparison of daily precipitation estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network(PERSIANN) and Tropical Rainfall Measuring Mission(TRMM) Multi-satellite Precipitation Analysis(TMPA) over Hunan province of China from 1998 to 2014. The ground gauge observations are taken as the reference. It is found that overall TMPA clearly outperforms PERSIANN, indicating by better statistical metrics(including correlation coefficient, root mean square error and relative bias). For the geospatial pattern, although both products are able to capture the major precipitation features(e.g., precipitation geospatial homogeneity) in Hunan, yet PERSIANN largely underestimates the precipitation intensity throughout all seasons. In contrast, there is no clear bias tendency from TMPA estimates. Precipitation intensity analysis showed that both the occurrence and amount histograms from TMPA are closer to the gauge observations from spring to autumn.However, in the winter season PERSIANN is closer to gauge observation, which is likely due to the ground contamination from the passive microwave sensors used by TMPA.展开更多
The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing ...The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing the latest Version-7 TRMM Multi-satellite Precipitation Analysis （TMPA 3B42V7） data for drought condition monitoring in the Weihe River Basin （0.135×10^6 km2）. The accuracy of the monthly TMPA 3B42V7 satellite precipitation data was firstly evaluated against the ground rain gauge observations. The statistical characteristics between a short period data series （1998-2013） and a long period data series （1961-2013） were then compared. The TMPA 3B42V7-based SPI （Standardized Precipitation Index） sequences were finally validated and analyzed at various temporal scales for assessing the drought conditions. The results indicate that the monthly TMPA 3B42V7 precipitation is in a high agreement with the rain gauge observations and can accurately capture the temporal and spatial characteristics of rainfall within the Weihe River Basin. The short period data can present the characteristics of long period record, and it is thus acceptable to use the short period data series to estimate the cumulative probability function in the SPI calculation. The TMPA 3B42V7-based SPI matches well with that based on the rain gauge observations at multiple time scales （i.e., 1-, 3-, 6-, 9-, and 12-month） and can give an acceptable temporal distribution of drought conditions. It suggests that the TMPA 3B42V7 precipitation data can be used for monitoring the occurrence of drought in the Weihe River Basin.展开更多
基金Basic work of the Ministry of Science and Technology of China,No.2008FY110300-01
文摘Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis （TMPA; 3B43 V.6） product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index （SPI）, at the grid point （0.25°×0.25°） and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. （1） At the grid point spatial scale, in comparison with the monitoring results between rain gauges （SPIlg） and TMPA grid （SPIls）, both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index （CSI） are distributed in the middle stream of the Lancang River Basin. （2） The same as SPIls, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. （3） At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. （4） At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate （underestimate） the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.
基金supported by the National Natural Science Foundation of China(Grant No.51979069)the Fundamental Research Funds for the Central Universities(Grant No.B200204029)the National Natural Science Foundation of Jiangsu Province,China(Grant No.BK20211202).
文摘A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.
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.
基金supported by the National Basic Research Program of China(the 973 Program,Grant No.2010CB951101)the Special Fund of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering of Hohai University(Grant No.1069-50985512)the"Strategic Priority Research Program"of the Chinese Academy of Sciences(Grant No.XDA05110102)
文摘Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite rainfall estimates have been very important sources for precipitation information, particularly in rain gauge-sparse regions. In this study, Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） products 3B42, RTV5V6, and RTV7 were evaluated for their applicability to the upper Yellow and Yangtze River basins on the Tibetan Plateau. Moreover, the capability of the TMPA products to simulate streamflow was also investigated using the Variable Infiltration Capacity （VIC） semi-distributed hydrological model. Results show that 3B42 performs better than RTVSV6 and RTV7, based on verification of the China Meteorological Administration （CMA） observational precipitation data. RTVSV6 can roughly capture the spatial precipitation pattern but overestimation exists throughout the entire study region. The anticipated improvements of RTV7 relative to RTVSV6 have not been realized in this study. Our results suggest that RTV7 significantly overestimates the precipitation over the two river basins, though it can capture the seasonal cycle features of precipitation. 3B42 shows the best performance in streamflow simulation of the abovementioned satellite products. Although involved in gauge adjustment at a monthly scale, 3B42 is capable of daily streamflow simulation. RTV5V6 and RTV7 have no capability to simulate streamflow in the upper Yellow and Yangtze River basins.
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National Key Research and Development Program of China(2017YFC1404002)National Natural Science Foundation of China(41405001,U1502233)
文摘This study presented a detailed comparison of daily precipitation estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network(PERSIANN) and Tropical Rainfall Measuring Mission(TRMM) Multi-satellite Precipitation Analysis(TMPA) over Hunan province of China from 1998 to 2014. The ground gauge observations are taken as the reference. It is found that overall TMPA clearly outperforms PERSIANN, indicating by better statistical metrics(including correlation coefficient, root mean square error and relative bias). For the geospatial pattern, although both products are able to capture the major precipitation features(e.g., precipitation geospatial homogeneity) in Hunan, yet PERSIANN largely underestimates the precipitation intensity throughout all seasons. In contrast, there is no clear bias tendency from TMPA estimates. Precipitation intensity analysis showed that both the occurrence and amount histograms from TMPA are closer to the gauge observations from spring to autumn.However, in the winter season PERSIANN is closer to gauge observation, which is likely due to the ground contamination from the passive microwave sensors used by TMPA.
基金jointly supported by the National Key Research and Development Program approved by Ministry of Science and Technology,China(2016YFA0601504)the Program of Introducing Talents of Discipline to Universities by the Ministry of Education and the State Administration of Foreign Experts Affairs,China(B08048)+1 种基金the National Natural Science Foundation of China(41501017,51579066)the Natural Science Foundation of Jiangsu Province(BK20150815)
文摘The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing the latest Version-7 TRMM Multi-satellite Precipitation Analysis （TMPA 3B42V7） data for drought condition monitoring in the Weihe River Basin （0.135×10^6 km2）. The accuracy of the monthly TMPA 3B42V7 satellite precipitation data was firstly evaluated against the ground rain gauge observations. The statistical characteristics between a short period data series （1998-2013） and a long period data series （1961-2013） were then compared. The TMPA 3B42V7-based SPI （Standardized Precipitation Index） sequences were finally validated and analyzed at various temporal scales for assessing the drought conditions. The results indicate that the monthly TMPA 3B42V7 precipitation is in a high agreement with the rain gauge observations and can accurately capture the temporal and spatial characteristics of rainfall within the Weihe River Basin. The short period data can present the characteristics of long period record, and it is thus acceptable to use the short period data series to estimate the cumulative probability function in the SPI calculation. The TMPA 3B42V7-based SPI matches well with that based on the rain gauge observations at multiple time scales （i.e., 1-, 3-, 6-, 9-, and 12-month） and can give an acceptable temporal distribution of drought conditions. It suggests that the TMPA 3B42V7 precipitation data can be used for monitoring the occurrence of drought in the Weihe River Basin.
