In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sit...In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.展开更多
Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range...Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.展开更多
This research aims to study a distance variation of Precipitable Water Vapor(PWV) between Continuously Operating Reference Stations(CORS) in Thailand using a Precise Point Positioning(PPP) technique.Nowadays, Global N...This research aims to study a distance variation of Precipitable Water Vapor(PWV) between Continuously Operating Reference Stations(CORS) in Thailand using a Precise Point Positioning(PPP) technique.Nowadays, Global Navigation Satellite System(GNSS) CORS is not only used to obtain precise positioning applications but also plays an important role in meteorological applications. With a recent establishment of GNSS CORS around Thai region, the PWV can be accurately derived from these GNSS CORS data using the scientific Position and Navigation Data Analyst(PANDA) GNSS processing software. One-year period of GNSS CORS data collected between January 1 and December 31, 2016 are used in this study. The GNSS CORS data used in this study are gathered from various agencies, i.e. Chulalongkorn University,Department of Lands and Department of Public Works and Town & Country Planning. However, a coverage distance from each GNSS CORS for PWV estimations is not precisely determined for Thai region.This information can help reduce expenses in an installation and maintenance of meteorology sensors at each GNSS CORS. Therefore, this paper focuses on determining the distance variation of PWV between GNSS CORS and the coverage distance from each CORS for PWV estimations. The result shows that the coverage distance from each CORS at 74 km or less can provide accurate PWV in Thai region.展开更多
Annual and seasonal diurnal precipitable water vapor(PWV)variations over Central and South America are analyzed for the period 2007-2013.PWV values were obtained from Global Navigation Satellite Systems(GNSS)observati...Annual and seasonal diurnal precipitable water vapor(PWV)variations over Central and South America are analyzed for the period 2007-2013.PWV values were obtained from Global Navigation Satellite Systems(GNSS)observations of sixty-nine GNSS tracking stations.Histograms by climate categories show that PWV values for temperate,polar and cold dry climate have a positive skewed distribution and for tropical climates(except for monsoon subtype)show a negative skewed distribution.The diurnal PWV and surface temperatures(T)anomaly datasets are analyzed by using principal components analysis(PCA).The first two modes represent more than 90%of the PWV variability.The first PCA mode of PWV variability shows a maximum amplitude value in the late afternoon few hours later than the respective values for surface temperature(T),therefore the temperature and the surface conditions(to yield evaporation)could be the main agents producing this variability;PWV variability in inland stations are mainly represented by this mode.The second mode of PWV variability shows a maximum amplitude at midnight,a possible explanation of this behavior is the effect of the sea/valley breeze.The coastal and valley stations are affected by this mode in most cases.Finally,the"undefined"stations,surrounded by several water bodies,are mainly affected by the second mode with negative eigenvectors.In the seasonal analysis,both the undefined and valley stations constitute the main cases that show a sea or valley breeze only during some seasons,while the rest of the year they present a behavior according to their temperature and the surface conditions.As a result,the PCA proves to be a useful numerical tool to represent the main sub-daily PWV variabilities.展开更多
针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附...针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附近的大气颗粒物浓度数据进行分析.结果显示,在非沙尘暴条件下,GNSS解算的大气可降水量(precipitable water vapor,PWV)精度表现良好,其与ERA5模型的PWV的差值均值和标准差均约在2 mm,证明了解算结果的可靠性.沙尘暴发生前,各站点PWV与大气颗粒物浓度的相关性均低于20%,表现出较弱的相关性.在沙尘暴期间,该相关性显著提高,尤其在BJFS和CHAN站点,PWV与大气颗粒物浓度的相关性超过60%.相位滞后消除后,NXZW站点的相关性更是达到70.25%.进一步分析还发现,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性也显著提高,其中BJFS和CHAN站点的相关性超过70%.综合分析表明,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性进一步增高,这表明大气颗粒物对PWV差值的贡献比对PWV本身的贡献显著增加,从而说明了PWV差值方法在大气颗粒物浓度监测方面的潜在应用价值.因此,本研究提供了一种新的研究思路和方法,为大气颗粒物浓度和气象条件之间复杂交互关系的进一步研究奠定了基础.展开更多
基于海上移动平台GNSS动态精密单点定位技术(precise point positioning,PPP),对海洋上空可降水量(precipitable water vapor,PWV)探测的影响因素进行了研究,主要分析了采样间隔,卫星截止高度角,PPP解算方式(固定解或浮点解)以及有无北...基于海上移动平台GNSS动态精密单点定位技术(precise point positioning,PPP),对海洋上空可降水量(precipitable water vapor,PWV)探测的影响因素进行了研究,主要分析了采样间隔,卫星截止高度角,PPP解算方式(固定解或浮点解)以及有无北斗卫星系统组合对海洋PWV反演的影响。结果显示,采样间隔为30 s时,PWV反演的精度最高;可用卫星数较少的情况下,截止高度角设为5°~10°时,PWV反演精度更优,随着卫星截止高度角的增大,反演精度逐渐降低;定位解是否固定对PWV反演精度影响较小;在GPS GLONASS系统组合的基础上,加入北斗卫星观测值,将提高观测的冗余度,有利于PWV反演精度的提高。展开更多
基金financially supported by the Special Fund for Meteorological Scientific Research in the Public Interest(GYHY201406012)the National Natural Science Foundation of China(41275114)a construction fund for CMONOC
文摘In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.
基金the National Natural Science Foundation of China(Grant No.42204006)the Guangxi Natural Science Foundation of China(2020GXNSFBA297145)+1 种基金the“Ba Gui Scholars”program of the provincial government of Guangxi,and Innovation Project of GuangXi Graduate Education(Grant No.YCSW2022322)Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(GrantNo.20-01-03,21-01-04)
文摘Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.
文摘This research aims to study a distance variation of Precipitable Water Vapor(PWV) between Continuously Operating Reference Stations(CORS) in Thailand using a Precise Point Positioning(PPP) technique.Nowadays, Global Navigation Satellite System(GNSS) CORS is not only used to obtain precise positioning applications but also plays an important role in meteorological applications. With a recent establishment of GNSS CORS around Thai region, the PWV can be accurately derived from these GNSS CORS data using the scientific Position and Navigation Data Analyst(PANDA) GNSS processing software. One-year period of GNSS CORS data collected between January 1 and December 31, 2016 are used in this study. The GNSS CORS data used in this study are gathered from various agencies, i.e. Chulalongkorn University,Department of Lands and Department of Public Works and Town & Country Planning. However, a coverage distance from each GNSS CORS for PWV estimations is not precisely determined for Thai region.This information can help reduce expenses in an installation and maintenance of meteorology sensors at each GNSS CORS. Therefore, this paper focuses on determining the distance variation of PWV between GNSS CORS and the coverage distance from each CORS for PWV estimations. The result shows that the coverage distance from each CORS at 74 km or less can provide accurate PWV in Thai region.
基金supported by the National Scientific and Technical Council of Argentina(CONICET)PIP 112-201201-00292,ANPCyT grant PICT 20121484Universidad Nacional de La Plata(UNLP)project 11G/142
文摘Annual and seasonal diurnal precipitable water vapor(PWV)variations over Central and South America are analyzed for the period 2007-2013.PWV values were obtained from Global Navigation Satellite Systems(GNSS)observations of sixty-nine GNSS tracking stations.Histograms by climate categories show that PWV values for temperate,polar and cold dry climate have a positive skewed distribution and for tropical climates(except for monsoon subtype)show a negative skewed distribution.The diurnal PWV and surface temperatures(T)anomaly datasets are analyzed by using principal components analysis(PCA).The first two modes represent more than 90%of the PWV variability.The first PCA mode of PWV variability shows a maximum amplitude value in the late afternoon few hours later than the respective values for surface temperature(T),therefore the temperature and the surface conditions(to yield evaporation)could be the main agents producing this variability;PWV variability in inland stations are mainly represented by this mode.The second mode of PWV variability shows a maximum amplitude at midnight,a possible explanation of this behavior is the effect of the sea/valley breeze.The coastal and valley stations are affected by this mode in most cases.Finally,the"undefined"stations,surrounded by several water bodies,are mainly affected by the second mode with negative eigenvectors.In the seasonal analysis,both the undefined and valley stations constitute the main cases that show a sea or valley breeze only during some seasons,while the rest of the year they present a behavior according to their temperature and the surface conditions.As a result,the PCA proves to be a useful numerical tool to represent the main sub-daily PWV variabilities.
文摘针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附近的大气颗粒物浓度数据进行分析.结果显示,在非沙尘暴条件下,GNSS解算的大气可降水量(precipitable water vapor,PWV)精度表现良好,其与ERA5模型的PWV的差值均值和标准差均约在2 mm,证明了解算结果的可靠性.沙尘暴发生前,各站点PWV与大气颗粒物浓度的相关性均低于20%,表现出较弱的相关性.在沙尘暴期间,该相关性显著提高,尤其在BJFS和CHAN站点,PWV与大气颗粒物浓度的相关性超过60%.相位滞后消除后,NXZW站点的相关性更是达到70.25%.进一步分析还发现,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性也显著提高,其中BJFS和CHAN站点的相关性超过70%.综合分析表明,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性进一步增高,这表明大气颗粒物对PWV差值的贡献比对PWV本身的贡献显著增加,从而说明了PWV差值方法在大气颗粒物浓度监测方面的潜在应用价值.因此,本研究提供了一种新的研究思路和方法,为大气颗粒物浓度和气象条件之间复杂交互关系的进一步研究奠定了基础.
文摘基于海上移动平台GNSS动态精密单点定位技术(precise point positioning,PPP),对海洋上空可降水量(precipitable water vapor,PWV)探测的影响因素进行了研究,主要分析了采样间隔,卫星截止高度角,PPP解算方式(固定解或浮点解)以及有无北斗卫星系统组合对海洋PWV反演的影响。结果显示,采样间隔为30 s时,PWV反演的精度最高;可用卫星数较少的情况下,截止高度角设为5°~10°时,PWV反演精度更优,随着卫星截止高度角的增大,反演精度逐渐降低;定位解是否固定对PWV反演精度影响较小;在GPS GLONASS系统组合的基础上,加入北斗卫星观测值,将提高观测的冗余度,有利于PWV反演精度的提高。
