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Volume 30 Issue 2

Mar.  2013

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2013 >  30(2): 291-305

Two-Dimensional Variational Analysis of Near-Surface Moisture from Simulated Radar Refractivity-Related Phase Change Observations

  • 1.

    Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, Department of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan;Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, School of Meteorology, University of Oklahoma, Norman OK, USA;School of Meteorology, University of Oklahoma, Norman OK, USA, Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA;Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, National Severe Storms Laboratory, NOAA, Norman OK, USA;Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA;School of Meteorology, University of Oklahoma, Norman OK, USA, Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA


doi: 10.1007/s00376-012-2087-7

  • Because they are most sensitive to atmospheric moisture content, radar refractivity observations can provide high-resolution information about the highly variable low-level moisture field. In this study, simulated radar refractivity-related phase-change data were created using a radar simulator from realistic high-resolution model simulation data for a dryline case. These data were analyzed using the 2DVAR system developed specifically for the phase-change data. Two sets of experiments with the simulated observations were performed, one assuming a uniform target spacing of 250 m and one assuming nonuniform spacing between 250 m to 4 km. Several sources of observation error were considered, and their impacts were examined. They included errors due to ground target position uncertainty, typical random errors associated with radar measurements, and gross error due to phase wrapping. Without any additional information, the 2DVAR system was incapable of dealing with phase-wrapped data directly. When there was no phase wrapping in the data, the 2DVAR produced excellent analyses, even in the presence of both position uncertainty and random radar measurement errors. When a separate pre-processing step was applied to unwrap the phase-wrapped data, quality moisture analyses were again obtained, although the analyses were smoother due to the reduced effective resolution of the observations by interpolation and smoothing involved in the unwrapping procedure. The unwrapping procedure was effective even when significant differences existed between the analyzed state and the state at a reference time. The results affirm the promise of using radar refractivity phase-change measurements for near-surface moisture analysis.
  • [1] Jidong GAO, Keith BREWSTER, Ming XUE, 2008: Variation of Radio Refractivity with Respect to Moisture and Temperature and Influence on Radar Ray Path, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 1098-1106.  doi: 10.1007/s00376-008-1098-x
    [2] Jun LI, Hongbin CHEN, Zhanqing LI, Pucai WANG, Xuehua FAN, Wenying HE, Jinqiang ZHANG, 2019: Analysis of Low-level Temperature Inversions and Their Effects on Aerosols in the Lower Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1235-1250.  doi: 10.1007/s00376-019-9018-9
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    [4] Chunguang CUI, Wen ZHOU, Hao YANG, Xiaokang WANG, Yi DENG, Xiaofang WANG, Guirong XU, Jingyu WANG, 2023: Analysis of the Characteristics of the Low-level Jets in the Middle Reaches of the Yangtze River during the Mei-yu Season, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 711-724.  doi: 10.1007/s00376-022-2107-1
    [5] Xingchao CHEN, Kun ZHAO, Juanzhen SUN, Bowen ZHOU, Wen-Chau LEE, 2016: Assimilating Surface Observations in a Four-Dimensional Variational Doppler Radar Data Assimilation System to Improve the Analysis and Forecast of a Squall Line Case, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1106-1119.  doi: 10.1007/s00376-016-5290-0
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    [7] Zhong Zhong, Wang Hanjie, 2000: A Study of the Relationship between Low-level Jet and Inversion Layer over an Agroforest Ecosystem in East China Plain?, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 299-310.  doi: 10.1007/s00376-000-0011-z
    [8] Marco Y. T. LEUNG, Wen ZHOU, Chi-Ming SHUN, Pak-Wai CHAN, 2018: Large-scale Circulation Control of the Occurrence of Low-level Turbulence at Hong Kong International Airport, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 435-444.  doi: 10.1007/s00376-017-7118-y
    [9] Peiling FU, Kefeng ZHU, Kun ZHAO, Bowen ZHOU, Ming XUE, 2019: Role of the Nocturnal Low-level Jet in the Formation of the Morning Precipitation Peak over the Dabie Mountains, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 15-28.  doi: 10.1007/s00376-018-8095-5
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    [12] Xuanyu LIU, Guixing CHEN, Sijia ZHANG, Yu DU, 2023: Formation of Low-Level Jets over Southern China in the Mei-yu Season, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1731-1748.  doi: 10.1007/s00376-023-2358-5
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    • Manuscript History

    Manuscript received: 10 March 2013
    Manuscript revised: 10 March 2013
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Two-Dimensional Variational Analysis of Near-Surface Moisture from Simulated Radar Refractivity-Related Phase Change Observations

    • 1. Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, Department of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan;Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, School of Meteorology, University of Oklahoma, Norman OK, USA;School of Meteorology, University of Oklahoma, Norman OK, USA, Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA;Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK, USA, National Severe Storms Laboratory, NOAA, Norman OK, USA;Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA;School of Meteorology, University of Oklahoma, Norman OK, USA, Atmospheric Radar Research Center, University of Oklahoma, Norman OK, USA
    • Manuscript received: 2013-03-10
    • Manuscript revised: 2013-03-10

    Abstract: Because they are most sensitive to atmospheric moisture content, radar refractivity observations can provide high-resolution information about the highly variable low-level moisture field. In this study, simulated radar refractivity-related phase-change data were created using a radar simulator from realistic high-resolution model simulation data for a dryline case. These data were analyzed using the 2DVAR system developed specifically for the phase-change data. Two sets of experiments with the simulated observations were performed, one assuming a uniform target spacing of 250 m and one assuming nonuniform spacing between 250 m to 4 km. Several sources of observation error were considered, and their impacts were examined. They included errors due to ground target position uncertainty, typical random errors associated with radar measurements, and gross error due to phase wrapping. Without any additional information, the 2DVAR system was incapable of dealing with phase-wrapped data directly. When there was no phase wrapping in the data, the 2DVAR produced excellent analyses, even in the presence of both position uncertainty and random radar measurement errors. When a separate pre-processing step was applied to unwrap the phase-wrapped data, quality moisture analyses were again obtained, although the analyses were smoother due to the reduced effective resolution of the observations by interpolation and smoothing involved in the unwrapping procedure. The unwrapping procedure was effective even when significant differences existed between the analyzed state and the state at a reference time. The results affirm the promise of using radar refractivity phase-change measurements for near-surface moisture analysis.

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