Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study com...Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.展开更多
天气雷达对中小尺度灾害性天气具有较强的监测预警能力,对研究中小尺度对流系统的云雨结构、理解降水内部的热力学和动力学过程有很大的帮助。单站点地基雷达受到诸如电磁波衰减、地物干扰等影响,在探测上存在一些限制。为了扩大天气雷...天气雷达对中小尺度灾害性天气具有较强的监测预警能力,对研究中小尺度对流系统的云雨结构、理解降水内部的热力学和动力学过程有很大的帮助。单站点地基雷达受到诸如电磁波衰减、地物干扰等影响,在探测上存在一些限制。为了扩大天气雷达探测区域,需要采用多部天气雷达组网联合探测。然而雷达组网的各雷达之间没有进行统一标定,影响雷达网资料一致性、组网拼图,以及使雷达资料在数值模式同化的应用中受到限制。本文以TRMM(Tropical Rainfall Measuring Mission)卫星搭载的经过精确标定的测雨雷达PR(Precipitation Radar)数据产品作为标准参照源,订正地基雷达GR(Ground-based Radar)的反射率因子偏差。为了减小PR与GR之间观测值对比的不一致性,利用最佳配对数据对比法(ABCD, Available Best Comparable Dataset法),对2008年1月至2014年9月间,江苏省六部地基雷达(南京、常州、连云港、南通、徐州、盐城)的反射率因子值进行订正。最后对方法的应用范围、存在的问题及未来展望进行了讨论。展开更多
Precipitation radar data derived from the Tropical Rainfall Measuring Mission (TRMM) satellite are used to study precipitation characteristics in 1998 over East Asia (10?38癗, 100C-145癊), especially over mid-latitude...Precipitation radar data derived from the Tropical Rainfall Measuring Mission (TRMM) satellite are used to study precipitation characteristics in 1998 over East Asia (10?38癗, 100C-145癊), especially over mid-latitude land (continental land) and ocean (East China Sea and South China Sea). Results are compared with precipitations in the tropics. Yearly statistics show dominant stratiform rain events over East Asia (about 83.7% by area fraction) contributing to 50% of the total precipitation. Deep convective rains contribute 48% to the total precipitation with a 13.7% area fraction. The statistics also show the unimportance of warm convective rain in East Asia, contributing 1.5% to the total precipitation with a 2.7% area fraction. On a seasonal scale, the results indicate that the rainfall ratio of stratiform rain to deep convective rain is proportional to their rainfall pixel ratio. Seasonal precipitation patterns compare well between Global Precipitation Climatology Project rainfall and TRMM PR measurements except in summer. Studies indicate a clear opposite shift of rainfall amount and events between deep convective and stratiform rains in the meridional in East Asia, which corresponds to the alternative activities of summer monsoon and winter monsoon in the region. The vertical structures of precipitation also exhibit strong seasonal variability in precipitation Contoured Rainrate by Altitude Diagrams (CRADs) and mean profiles in the mid-latitudes of East Asia. However, these structures in the South China Sea are of a tropical type except in winter. The analysis of CRADs reveals a wide range of surface rainfall rates for most deep convective rains, especially in the continental land, and light rain rate for most stratiform rains in East Asia, regardless of over land or ocean.展开更多
In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project （GPCP） version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar （TRMM PR） ...In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project （GPCP） version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar （TRMM PR） are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d^-1 is larger than that of about 0.1 mm d^-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function （PDF） analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d^-1. When the TRMM PR rain rate is greater than 8 mm d^-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d^-1 compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d^-1 between the two datasets when the rain rate is less than 10 mm d^-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.展开更多
The multidimensional morphological characteristics(including scale, horizontal shape and 3 D morphology) of precipitation areas over the Tibetan Plateau in summer were studied using 15 years(1998–2012) of observation...The multidimensional morphological characteristics(including scale, horizontal shape and 3 D morphology) of precipitation areas over the Tibetan Plateau in summer were studied using 15 years(1998–2012) of observational data from the precipitation radar onboard the Tropical Rainfall Measuring Mission satellite. As the scale of the precipitation area increased from 20 to 150 km, the near-surface rain rate(RRav) of the precipitation area increased by up to 78%(from ~1.12 to ~2 mm h~(-1)). Linear precipitation areas had the lowest median RRav(~1 mm h~(-1) over the eastern Tibetan Plateau),whereas square-shaped precipitation areas had the highest median RRav(~1.58 mm h~(-1) over the eastern Tibetan Plateau).The 3D morphology was defined as the ratio of the average vertical scale to the average horizontal scale, where a large value corresponds to thin and tall, and a small value corresponds to plump and short. Thin-and-tall precipitation areas and plump-and-short precipitation areas had a greater median RRav, whereas the precipitation areas with a moderate 3D morphology had the lowest median RRav. The vertical structure of the precipitation-area reflectivity was sensitive to both size and 3D morphology, but was not sensitive to the horizontal shape. The relationship between RRav and the morphological characteristics was most significant over the southern slopes of the Tanggula Mountains and the Tibetan Plateau east of 100°E. The morphological characteristics of precipitation areas are therefore closely related to the intensity of precipitation and could potentially be used to forecast precipitation and verify numerical models.展开更多
Numerical simulations of two heavy rainfall cases in the Changjiang-Huaihe River basin are performed with TRMM/PR (precipitation radar) data incorporated into the PSU/NCAR meso scale model MM5. The mixing ratio of rai...Numerical simulations of two heavy rainfall cases in the Changjiang-Huaihe River basin are performed with TRMM/PR (precipitation radar) data incorporated into the PSU/NCAR meso scale model MM5. The mixing ratio of rainwater q <SUB>r</SUB> is obtained from the R −q <SUB>r</SUB> relation (R is the rainfall rate), and the mixing ratio of water vapor q <SUB>v</SUB> in the model is replaced by q <SUP>1</SUP>′<SUB>v</SUB> = q <SUB>v</SUB>+q <SUB>r</SUB>. Then, TRMM/PR data are used to modify humidity analysis obtained from conventional radiosonde data, and sensitivity experiments (STE) are performed and compared to control experiments (CTL). Results show that both the heavy rainfall distribution and its maximum amounts from STE are improved compared with those from CTL.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42030501,41877148,41501016,41530752)Scherer Endowment Fund of Department of Geography,Western Michigan University and the Fundamental Research Funds for the Central Universities(No.lzujbky-2019-98)。
文摘Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.
文摘天气雷达对中小尺度灾害性天气具有较强的监测预警能力,对研究中小尺度对流系统的云雨结构、理解降水内部的热力学和动力学过程有很大的帮助。单站点地基雷达受到诸如电磁波衰减、地物干扰等影响,在探测上存在一些限制。为了扩大天气雷达探测区域,需要采用多部天气雷达组网联合探测。然而雷达组网的各雷达之间没有进行统一标定,影响雷达网资料一致性、组网拼图,以及使雷达资料在数值模式同化的应用中受到限制。本文以TRMM(Tropical Rainfall Measuring Mission)卫星搭载的经过精确标定的测雨雷达PR(Precipitation Radar)数据产品作为标准参照源,订正地基雷达GR(Ground-based Radar)的反射率因子偏差。为了减小PR与GR之间观测值对比的不一致性,利用最佳配对数据对比法(ABCD, Available Best Comparable Dataset法),对2008年1月至2014年9月间,江苏省六部地基雷达(南京、常州、连云港、南通、徐州、盐城)的反射率因子值进行订正。最后对方法的应用范围、存在的问题及未来展望进行了讨论。
文摘Precipitation radar data derived from the Tropical Rainfall Measuring Mission (TRMM) satellite are used to study precipitation characteristics in 1998 over East Asia (10?38癗, 100C-145癊), especially over mid-latitude land (continental land) and ocean (East China Sea and South China Sea). Results are compared with precipitations in the tropics. Yearly statistics show dominant stratiform rain events over East Asia (about 83.7% by area fraction) contributing to 50% of the total precipitation. Deep convective rains contribute 48% to the total precipitation with a 13.7% area fraction. The statistics also show the unimportance of warm convective rain in East Asia, contributing 1.5% to the total precipitation with a 2.7% area fraction. On a seasonal scale, the results indicate that the rainfall ratio of stratiform rain to deep convective rain is proportional to their rainfall pixel ratio. Seasonal precipitation patterns compare well between Global Precipitation Climatology Project rainfall and TRMM PR measurements except in summer. Studies indicate a clear opposite shift of rainfall amount and events between deep convective and stratiform rains in the meridional in East Asia, which corresponds to the alternative activities of summer monsoon and winter monsoon in the region. The vertical structures of precipitation also exhibit strong seasonal variability in precipitation Contoured Rainrate by Altitude Diagrams (CRADs) and mean profiles in the mid-latitudes of East Asia. However, these structures in the South China Sea are of a tropical type except in winter. The analysis of CRADs reveals a wide range of surface rainfall rates for most deep convective rains, especially in the continental land, and light rain rate for most stratiform rains in East Asia, regardless of over land or ocean.
基金NKBRDPC Grant No.2004CB418304NSFCGrant Nos.40175015 , 40375018 +1 种基金 NSFC grant of the Joint Research Fund for Overseas Chinese Young Scholars(No.40428006)EORC/JAXA(No.206).
文摘In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project （GPCP） version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar （TRMM PR） are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d^-1 is larger than that of about 0.1 mm d^-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function （PDF） analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d^-1. When the TRMM PR rain rate is greater than 8 mm d^-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d^-1 compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d^-1 between the two datasets when the rain rate is less than 10 mm d^-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.
基金supported by the National Natural Science Foundation of China (Grant Nos. 91837310, 41675041, 41620104009 and 41675043)the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (Grant No. 2019QZKK0104)+3 种基金Fundamental Research Funds for the Guangzhou Science and Technology Plan project (Grant No. 201903010036)the Fundamental Research Funds for the Central Universities from Sun Yat-Sen University (Grant No. 20lgpy19)the China Postdoctoral Science Foundation (Grant No. 2020M672943)the Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies (Grant No. 2020B1212060025)。
文摘The multidimensional morphological characteristics(including scale, horizontal shape and 3 D morphology) of precipitation areas over the Tibetan Plateau in summer were studied using 15 years(1998–2012) of observational data from the precipitation radar onboard the Tropical Rainfall Measuring Mission satellite. As the scale of the precipitation area increased from 20 to 150 km, the near-surface rain rate(RRav) of the precipitation area increased by up to 78%(from ~1.12 to ~2 mm h~(-1)). Linear precipitation areas had the lowest median RRav(~1 mm h~(-1) over the eastern Tibetan Plateau),whereas square-shaped precipitation areas had the highest median RRav(~1.58 mm h~(-1) over the eastern Tibetan Plateau).The 3D morphology was defined as the ratio of the average vertical scale to the average horizontal scale, where a large value corresponds to thin and tall, and a small value corresponds to plump and short. Thin-and-tall precipitation areas and plump-and-short precipitation areas had a greater median RRav, whereas the precipitation areas with a moderate 3D morphology had the lowest median RRav. The vertical structure of the precipitation-area reflectivity was sensitive to both size and 3D morphology, but was not sensitive to the horizontal shape. The relationship between RRav and the morphological characteristics was most significant over the southern slopes of the Tanggula Mountains and the Tibetan Plateau east of 100°E. The morphological characteristics of precipitation areas are therefore closely related to the intensity of precipitation and could potentially be used to forecast precipitation and verify numerical models.
基金This research was supported by the National Natural Science Foundation of China under Grant No.49794030.
文摘Numerical simulations of two heavy rainfall cases in the Changjiang-Huaihe River basin are performed with TRMM/PR (precipitation radar) data incorporated into the PSU/NCAR meso scale model MM5. The mixing ratio of rainwater q <SUB>r</SUB> is obtained from the R −q <SUB>r</SUB> relation (R is the rainfall rate), and the mixing ratio of water vapor q <SUB>v</SUB> in the model is replaced by q <SUP>1</SUP>′<SUB>v</SUB> = q <SUB>v</SUB>+q <SUB>r</SUB>. Then, TRMM/PR data are used to modify humidity analysis obtained from conventional radiosonde data, and sensitivity experiments (STE) are performed and compared to control experiments (CTL). Results show that both the heavy rainfall distribution and its maximum amounts from STE are improved compared with those from CTL.
