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Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China

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Geodesy and Geodynamics 2023年第2期14卷 111-120页

作者： Liangke Huang Xiaoyang Fang Tengxu Zhang Haoyu Wang Lei Cui Lilong Liu College of Geomatics and Geoinformation Guilin University of TechnologyGuilin 541006China School of Resources and Environmental Science and Engineering Hubei University of Science and TechnologyXianning 437100China

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.

关键词： Temperature and pressure Global navigation satellite system precipitable water vapor MERRA-2 ERA5

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Decadal trends in precipitable water vapor over the Indus River Basin using ERA5 reanalysis data

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Journal of Mountain Science 2023年第10期20卷 2928-2945页

作者： Seema RANI Jyotsna SINGH Subhash SINGH Purushottam TIWARI Suraj MAL Department of Geography Institute of ScienceBanaras Hindu UniversityUttar Pradesh 221005India Department of Geography Shaheed Bhagat Singh CollegeUniversity of DelhiNew Delhi 110017India Center for the Study of Regional Development Jawaharlal Nehru UniversityNew DelhiDelhi 11oo6zIndia

precipitable water vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.

关键词： Himalaya precipitable water vapor Indus River Basin Atmosphere Climate Change ERA5 Reanalysis data

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Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin,China

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Satellite Navigation 2021年第1期2卷 175-191页

作者： Liangke Huang Zhixiang Mo Shaofeng Xie Lilong Liu Chuanli Kang Shitai Wang College of Geomatics and Geoinformation Guilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Spatial Information and Geomatics Guilin 541004China.3 School of Geodesy and GeomaticsWuhan UniversityWuhan 430079China.

precipitable water vapor(PWV),as an important indicator of atmospheric water vapor,can be derived from Global Navigation Satellite System(GNSS)observations with the advantages of high precision and all-weather capacity.GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in mete-orology,particularly for severe weather conditions,for water vapor is not well sampled in the current meteorological observing systems.In this study,an empirical atmospheric weighted mean temperature(Tm)model for Guilin is estab-lished using the radiosonde data from 2012 to 2017.Then,the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017.The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square(RMS)of−0.51 and 2.12 K,respectively,compared with other widely used models.Moreover,the GNSS PWV estimates are validated with the data at Guilin radiosonde station.Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of−0.9 and 3.53 mm,respectively.Finally,an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed.It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements,and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall.It also reveals the moisture variation in several regions of Guilin during a heavy rainfall,which is significant for the moni-toring of rainfalls and weather forecast.

关键词： GNSS precipitable water vapor Heavy rainfall Spatiotemporal characteristic Atmospheric weighted mean temperature

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Seasonal Difference of the Spatio-Temporal Variation of precipitable water vapor in China

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Journal of Geoscience and Environment Protection 2023年第5期11卷 159-173页

作者： Qixu Li Qianqian Song Zhitong Qian Ying Huang Key Laboratory of Meteorological Disaster Ministry of Education (KLME) Joint International Research Laboratory of Climate and Environment Change (ILCEC) Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science and Technology Nanjing China Meteorological Observatory of Tibet Autonomous Region Lhasa China Ningxia Climate Center Yinchuan China

This study analyzes the spatial and temporal distribution characteristics of seasonal precipitable water vapor (PWV) in China between 1979 and 2008. To achieve this, the observed temperature dew point difference and atmospheric pressure at various altitudes of 102 radiosonde stations were utilized. The analysis involved calculating and examining the PWV variations across the different seasons in the study period. The results are illustrated as follows: 1) The annual mean and seasonal mean PWV over China is characterized by decreasing from southeast to northwest. The PWV has obvious seasonal features. It is the least in winter, which is mainly affected by latitude and altitude, and the most in summer, which is mainly affected by the monsoon. It is the medium in spring and autumn, with more in autumn than in spring. 2) The spatial distribution pattern of four seasonal PWV is approximately opposite to its variation coefficient distribution pattern, that is, the monsoon (non-monsoon) areas with more (less) PWV have a smaller (larger) variation amplitude. 3) The distribution pattern of four seasonal PWV shows a consistent distribution pattern in the whole region and the winter characteristics are the most significant. The abnormal variation of PWV shows consistent interdecadal oscillation, and it exhibits an obvious phase transition around 2002 when the PWV has an increasing shift in winter, spring, and summer, while it is more complicated in autumn.

关键词： precipitable water vapor Distribution Characteristics Four Seasons

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Retrieval of Oceanic Total precipitable water vapor and Cloud Liquid water from Fengyun-3D Microwave Sounding Instruments

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Journal of Meteorological Research 2021年第2期35卷 371-383页

作者： Yang HAN Jun YANG Hao HU Peiming DONG State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 National Satellite Meteorological Center China Meteorological AdministrationBeijing 100081

Fengyun-3 D(FY-3 D) satellite is the latest polar-orbiting meteorological satellite launched by China and carries 10 instruments onboard. Its microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS) can acquire a total of 28 channels of brightness temperatures, providing rich information for profiling atmospheric temperature and moisture. However, due to a lack of two important frequencies at 23.8 and 31.4 GHz, it is difficult to retrieve the total precipitable water vapor(TPW) and cloud liquid water path(CLW) from FY-3 D microwave sounder data as commonly done for other microwave sounding instruments. Using the channel similarity between Suomi National Polar-orbiting Partnership(NPP) advanced technology microwave sounder(ATMS) and FY-3 D microwave sounding instruments, a machine learning(ML) technique is used to generate the two missing low-frequency channels of MWTS and MWHS. Then, a new dataset named as combined microwave sounder(CMWS) is obtained,which has the same channel setting as ATMS but the spatial resolution is consistent with MWTS. A statistical inversion method is adopted to retrieve TPW and CLW over oceans from the FY-3 D CMWS. The intercomparison between different satellites shows that the inversion products of FY-3 D CMWS and Suomi NPP ATMS have good consistency in magnitude and distribution. The correlation coefficients of retrieved TPW and CLW between CMWS and ATMS can reach 0.95 and 0.85, respectively.

关键词： precipitable water vapor cloud liquid water Fengyun-3D(FY-3D) microwave machine learning(ML)

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Variational Assimilation of GPS precipitable water vapor and Hourly Rainfall Observations for a Meso-βScale Heavy Precipitation Event During the 2002 Mei-Yu Season

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Advances in Atmospheric Sciences 2007年第3期24卷 509-526页

作者：张盟倪允琪张福青 Department of Atmospheric Sciences Nanjing University State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Department of Atmospheric Sciences Texas A & M University College StationTexas 77843-3150USA

Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.

关键词： GPS precipitable water vapor four-dimensional variational assimilation meso-β-scale con- vective system

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The GNSS PWV retrieval using non-observation meteorological parameters based on ERA5 and its relation with precipitation

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Geodesy and Geodynamics 2024年第3期15卷 302-313页

作者： Weifeng Yang Zhiping Chen Kaiyun Lv Pengfei Xia Tieding Lu School of Surveying and Geoinformation Engineering East China University of TechnologyNanchang 330013China Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources East China University of TechnologyNanchang 330013China State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China Jiangxi Province Engineering Research Center of Surveying Mapping and Geographic InformationNanchang 330025China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China

The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.

关键词： ERA5 GNSS precipitable water vapor Precipitation Wavelet coherence analysis

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Increasing Trend of precipitable water vapor in Antarctica and Greenland

Increasing Trend of Precipitable Water Vapor in Antarctica a...

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第十三届中国卫星导航年会

作者： Junsheng Ding Junping Chen Wenjie Tang Shanghai Astronomical Observatory Chinese Academy of Sciences University of Chinese Academy of Sciences

Polar precipitable water vapor（PWV） is expected to increase under a warming climate. However, the conventional approach cannot provide sufficient long-term PWV records due to the high maintenance costs. Fortunately, the exponential explosion in the number of geodetic-quality Global Navigation Satellite System（GNSS） stations has broken this deadlock. Utilizing radiosonde and GNSS data over two decades（1994-2020）, we analyzed and evaluated the spatial and temporal variability characteristics of PWV in Antarctica and Greenland. The multi-year mean PWV values for Antarctica and Greenland were 5.63 ± 1.67 mms and 7.63 ± 1.35 mms, respectively, with annual standard deviations（STD） of PWV of 1.60 ± 0.77 mms and 3.44 ± 0.92 mms, respectively. In both Antarctica and Greenland, the PWV annual STD shows a gradual increase from the land center to the edge;while the PWV mean decreases with increasing latitude in Greenland, there is no significant latitudinal correlation in Antarctica. There is no significant regional difference in PWV trends, and from the statistical results, both Antarctica and Greenland show an increasing trend from year to year. The PWV trends in Antarctica and Greenland were 0.29 ± 0.77 mm/decade and 0.27 ± 0.64 mm/decade, respectively, with relative PWV trends of 5.98 ± 12.93%/decade and 3.87 ± 8.45%/decade, respectively.

关键词： precipitable water vapor GNSS Radiosonde Antarctica and Greenland

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Change Features of GPS/MET precipitable water vapor in Different Precipitation in Lianyungang

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Meteorological and Environmental Research 2015年第7期6卷 1-4,9页

作者： Hao Ling Zhao Liang Zhu Minhua Bai Xue Ma Chenchen Lianyungang Meteorological Bureau

Based on the GPS/MET water vapor monitoring data and conventional meteorological data at Lianyungang station from April to July, 2015, the relationship between precipitable water vapor and real precipitation was studied. According to different precipitation, change trends of precipitable water vapor in convective precipitation and steady precipitation were analyzed. Results showed that necessary condition of precipitation generation was high precipitable water vapor value in the air. precipitable water vapor change presented wave-shape and phased characters. In convection precipitation, precipitable water vapor changed frequently and had larger change amplitude, while its change was slow in steady precipi- tation. The appearing time of the maximum values of rainfall intensity and precipitable water vapor was not necessarily consistent, but it was known that severe rainfall usually began at the high-value stage of precipitable water vapor, and high-value stage of precipitable water vapor often corresponded to higher precipitation probability. In addition, precipitable water vapor showed different characteristics in the above two different precipitation, and these results could provide a reference for precipitation forecast.

关键词： GPS/MET precipitable water vapor Variation features China

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The Application Study about Ground-Based GPS precipitable water vapor in Shijiazhuang and Qinhuangdao Region

The Application Study about Ground-Based GPS Precipitable Wa...

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Wang Yong 1 2 1.College of Traffic and Surveying Hebei Polytechnic University Tangshan China 2.Key Laboratory of Mine Spatial Information Technologies (Henan Polytechnic University Henan Bureau of Surveying and Mapping) State Bureau of Surveying and Mapping Jiaozuo China Ding Keliang School of Surveying and Civil Spatial Information Beijing University of Civil Engineering and Architecture Beijing China He Rong School of Surveying and Land Infomation Engineering Henan Polytechnic University Jiaozuo China Liu Yanping College of Traffic and Surveying Hebei Polytechnic University Tangshan China

water vapor is a highly variable parameter in atmospheric processes and it plays a crucial role in atmospheric motions on a wide range of scales in space and time. GPS technique has been widely used in retrieving precipitable water vapor. Firstly the article has retrieved precipitable water vapor of Qinhuangdao and Shijiazhuang stations by GPS technique. Then it has researched two aspects of precipitable water vapor. One is the spatial and temporal distribution characters of precipitable water vapor;the other is the relation between precipitable water vapor and actual rainfall. The value of GPS precipitable water vapor of Shijiazhuang is higher than the value of GPS precipitable water vapor of Qinhuangdao, which is accord to the formula that the precipitable water vapor is reduced from south to north. During the different time of a day, there are differ degree fluctuate which the min value present to morning and the max value present to evening. It also compared the GPS precipitable water vapor and actual rainfall. Although the time of max value about rainfall is not identical to the time of max value about precipitable water vapor, rainfall has occurred mostly in the time while the value of precpitable water vapor is high.

关键词： Global positioning system precipitable water vapor Zenith tropospheric delay Zenith wet delay

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