Vol.29, NO.5, 2018
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Article Navigation >  Journal of Applied Meteorological Science  > 2018  >  29(5): 546-558
Wang Hong, Kong Fanyou, Jung Youngsun, et al. Quality control of S-band polarimetric radar measurements for data assimilation. J Appl Meteor Sci, 2018, 29(5): 546-558. DOI:  10.11898/1001-7313.20180504.
Citation: Wang Hong, Kong Fanyou, Jung Youngsun, et al. Quality control of S-band polarimetric radar measurements for data assimilation. J Appl Meteor Sci, 2018, 29(5): 546-558. DOI:  10.11898/1001-7313.20180504.
shu

Quality Control of S-band Polarimetric Radar Measurements for Data Assimilation

DOI: 10.11898/1001-7313.20180504
  • 1.

    Guangzhou Institute of Tropical and Marine Meteorology/Key Laboratory of Regional Numerical Weather Prediction, CMA, Guangzhou 510080

  • 2.

    State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081

  • 3.

    Center for Analysis and Prediction of Storms, University of Oklahoma, Oklahoma 73072, USA

  • Received Date: 2018-05-15
  • Rev Recd Date: 2018-07-19
  • Publish Date: 2018-09-30
    Abstract
  • The polarimetric radar is an important detection device whose measurements can be used for severe convective weather analysis and cloud microphysics progress research. Upgrading the traditional Doppler weather radar to polarimetric radar is a key part of severe convective weather monitoring program of China in the next few years, and the quality control of polarimetric radar measurements is key technical issue of the monitoring program. In Guangdong Province, based on the domestic and international mainstream quality control algorithms and relevant experience, a quality control system is developed for S-band polarimetric radars, to deal with the non-meteorological echo, non-standard blockage and high frequency noise in the radar radial, which have negative impacts on application of polarimetric radar measurements in data assimilation. The system is applied to the typical severe convective weather case in South China monsoon region, including a rainfall case, a severe convection case and a typhoon case in 2017. Evaluation results show that a combination of the hydrometeor classification screening based on fuzzy logic, co-polar cross-correlation coefficient (ρHV), signal-to-noise ratio (SNR) and specific differential phase (KDP) thresholding and despeckling can remove most non-meteorological echoes, and suppress virtual echo caused by anomalous propagation efficiently. Non-meteorological echoes include ground clutter, biological scatters, partial clear-air echo and radiographic noise due to anomalous propagation. A linear interpolation is employed to fill the small gap (the width of which is less than 5°) caused by non-standard blockage. A median filter and radial smooth are found effective in filtering out high frequency noise in the radar radial while maintaining polarimetric radar characteristics. After quality control, the meteorological echo is clearer and more prominent, and accounts for about 40% of valid observation which is defined by reflectivity (ZH) being larger than -30 dBZ. ZH of the meteorological echo is larger than 5 dBZ, ρHV is larger than 0.8 and less than 1.0, and the differential reflectivity (ZDR) is between -0.2 and 4 dB. Batch tests are needed to keep the quality control system stable and effective in the further work. And how to combine multiple polarimetric radar measurements to form a three-dimensional gridded product is also another important prerequisite for application of polarimetric radars measurements in the numerical model.
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  • Fig. 1  Flow diagram of quality control for the polarimetric radar

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    Fig. 2  Accumulated reflectivity at different elevations of Guangzhou polarimetric radar from 0600 UTC to 2100 UTC on 8 May 2017

    (a)0.5°, (b)1.5°, (c)2.4°

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    Fig. 3  The effect of a different quality control component on measurements from Guangzhou polarimetric radar of 0.5° elevation at 1000 UTC 8 May 2017

    (a)raw reflectivity, (b)raw differential reflectivity, (c)reflectivity after non-standard blockage correction, (d)differential reflectivity after non-standard blockage correction, (e)reflectivity after hydrometeor classification filtering, (f)differential reflectivity after hydrometeor classification filtering, (g)reflectivity after thresholding, (h)differential reflectivity after thresholding, (i)reflectivity after despeckling, (j)differential reflectivity after despeckling, (k)reflectivity after median filter, (l)differential reflectivity after median filter

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    Fig. 4  Hydrometeor classification type for Guangzhou radar of 0.5° elevation at 1000 UTC 8 May 2017

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    Fig. 5  The result of the median filtering and radial smooth for measurements

    (a)reflectivity, (b)differential reflectivity, (c)pecific differential phase

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    Fig. 6  Measurements before and after quality control for Guangzhou polarimetric radar of 0.5° elevation at 2154 UTC 6 May 2017

    (a)reflectivity before quality control, (b)differential reflectivity before quality control, (c)pecific differential phase before quality control, (d)reflectivity after quality control, (e)differential reflectivity after quality control, (f)pecific differential phase after quality control

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    Fig. 7  Measurements before and after the quality control for Yangjiang polarimetric radar of 0.5° elevation at 0054 UTC 23 Aug 2017

    (a)reflectivity before quality control, (b)differential reflectivity before quality control, (c)specific differential phase before quality control, (d)reflectivity after quality control, (e)differential reflectivity after quality control, (f)specific differential phase after quality control

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    Fig. 8  The scatter plot of ZH-ρHV during quality control for different case

    (a)Guangzhou radar of 0.5° elevation at 2154 UTC 6 May 2017, (b)Guangzhou radar of 0.5° elevation at 1000 UTC 8 May 2017, (c)Yangjiang radar of 0.5° elevation at 0054 UTC 23 Aug 2017

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    Fig. 9  Frequency distribution of ZDR and ZH after quality control

    (a)Guangzhou radar of 0.5° elevation at 2154 UTC 6 May 2017,
    (b)Guangzhou radar of 0.5° elevation at 1000 UTC 8 May 2017,
    (c)Yangjiang radar of 0.5° elevation at 0054 UTC 23 Aug 2017

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    Table  1  The rejection rate for various ρHV, SNR and KDP thresholds for Guangzhou polarimetric radar at 1000 UTC 8 May 2017(unit:%)

    仰角/(°) ρHV检查 SNR检查 KDP检查
    ZH ZDR KDP ZH ZDR KDP KDP
    0.5 7.09 3.16 17.30 5.58 5.55 5.44 27.29
    1.5 5.34 1.75 15.35 6.69 6.67 6.52 28.19
    2.4 7.51 3.15 18.20 5.66 5.64 5.51 25.77
    3.3 6.59 2.45 16.59 6.22 6.21 6.02 22.37
    4.3 5.92 2.42 12.56 7.75 7.74 7.57 25.59
    6.0 6.93 3.51 13.74 9.14 9.14 8.88 36.33
    9.9 8.78 5.34 20.46 9.33 9.20 8.61 38.52
    14.6 13.06 9.83 29.64 10.58 10.49 9.57 44.04
    19.5 28.00 23.92 39.50 11.43 11.35 10.32 59.74
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    • Received : 2018-05-15
    • Accepted : 2018-07-19
    • Published : 2018-09-30
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