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Preliminary Results of 4-D Water Vapor Tomography in the Troposphere Using GPS


doi: 10.1007/s00376-006-0551-y

  • Slant-path water vapor amounts (SWV) from a station to all the GPS (Global Positioning System) satellites in view can be estimated by using a ground-based GPS receiver. In this paper, a tomographic method was utilized to retrieve the local horizontal and vertical structure of water vapor over a local GPS receiver network using SWV amounts as observables in the tomography. The method of obtaining SWV using ground-based GPS is described first, and then the theory of tomography using GPS is presented. A water vapor tomography experiment was made using a small GPS network in the Beijing region. The tomographic results were analyzed in two ways: (1) a pure GPS method, i.e., only using GPS observables as input to the tomography; (2) combining GPS observables with vertical constraints or a priori information, which come from average radiosonde measurements over three days. It is shown that the vertical structure of water vapor is well resolved with a priori information. Comparisons of profiles between radiosondes and GPS show that the RMS error of the tomography is about 1–2mm. It is demonstrated that the tomography can monitor the evolution of tropospheric water vapor in space and time. The vertical resolution of the tomography is tested with layer thicknesses of 600 m, 800 m and 1000 m. Comparisons with radiosondes show that the result from a resolution of 800m is slightly better than results from the other two resolutions in the experiment. Water vapor amounts recreated from the tomography field agree well with precipitable water vapor (PWV) calculated using GPS delays. Hourly tomographic results are also shown using the resolution of 800 m. Water vapor characteristics under the background of heavy rainfall development are analyzed using these tomographic results. The water vapor spatio-temporal structures derived from the GPS network show a great potential in the investigation of weather disasters.
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    [2] CAO Yunchang, CHEN Yongqi, LI Pingwha, 2006: Wet Refractivity Tomography with an Improved Kalman-Filter Method, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 693-699.  doi: 10.1007/s00376-006-0693-y
    [3] Houaria NAMAOUI, Salem KAHLOUCHE, Ahmed Hafid BELBACHIR, Roeland Van MALDEREN, Hugues BRENOT, Eric POTTIAUX, 2017: GPS Water Vapor and Its Comparison with Radiosonde and ERA-Interim Data in Algeria, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 623-634.  doi: 10.1007/s00376-016-6111-1
    [4] ZHANG Meng, NI Yunqi, ZHANG Fuqing, 2007: Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso- Scale Heavy Precipitation Event During the 2002 Mei-Yu Season, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 509-526.  doi: 10.1007/s00376-007-0509-8
    [5] Ling WANG, Xiuqing HU, Na XU, Lin CHEN, 2021: Water Vapor Retrievals from Near-infrared Channels of the Advanced Medium Resolution Spectral Imager Instrument onboard the Fengyun-3D Satellite, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1351-1366.  doi: 10.1007/s00376-020-0174-8
    [6] Ha-Taek KWON, Eui-Hyun JUNG, Gyu-Ho LIM, 2010: A Comparison of GPS- and NWP-derived PW Data over the Korean Peninsula, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 871-882.  doi: 10.1007/s00376-009-9069-4
    [7] Junhong Wang, Harold L. Cole, David J. Carlson, 2001: Water Vapor Variability in the Tropical Western Pacific from 20-year Radiosonde Data, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 752-766.
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    [9] WANG Xin, Lü Daren, 2005: Retrieval of Water Vapor Profiles with Radio Occultation Measurements Using an Artificial Neural Network, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 759-764.  doi: 10.1007/BF02918719
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    [11] YUE Caijun, GAO Shouting, LIU Lu, LI Xiaofan, 2015: A Diagnostic Study of the Asymmetric Distribution of Rainfall during the Landfall of Typhoon Haitang (2005), ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1419-1430.  doi: 10.1007/s00376-015-4246-0
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Manuscript History

Manuscript received: 10 July 2006
Manuscript revised: 10 July 2006
通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Preliminary Results of 4-D Water Vapor Tomography in the Troposphere Using GPS

  • 1. Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871

Abstract: Slant-path water vapor amounts (SWV) from a station to all the GPS (Global Positioning System) satellites in view can be estimated by using a ground-based GPS receiver. In this paper, a tomographic method was utilized to retrieve the local horizontal and vertical structure of water vapor over a local GPS receiver network using SWV amounts as observables in the tomography. The method of obtaining SWV using ground-based GPS is described first, and then the theory of tomography using GPS is presented. A water vapor tomography experiment was made using a small GPS network in the Beijing region. The tomographic results were analyzed in two ways: (1) a pure GPS method, i.e., only using GPS observables as input to the tomography; (2) combining GPS observables with vertical constraints or a priori information, which come from average radiosonde measurements over three days. It is shown that the vertical structure of water vapor is well resolved with a priori information. Comparisons of profiles between radiosondes and GPS show that the RMS error of the tomography is about 1–2mm. It is demonstrated that the tomography can monitor the evolution of tropospheric water vapor in space and time. The vertical resolution of the tomography is tested with layer thicknesses of 600 m, 800 m and 1000 m. Comparisons with radiosondes show that the result from a resolution of 800m is slightly better than results from the other two resolutions in the experiment. Water vapor amounts recreated from the tomography field agree well with precipitable water vapor (PWV) calculated using GPS delays. Hourly tomographic results are also shown using the resolution of 800 m. Water vapor characteristics under the background of heavy rainfall development are analyzed using these tomographic results. The water vapor spatio-temporal structures derived from the GPS network show a great potential in the investigation of weather disasters.

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