Chen Ze, Tian Yufang, Lü Daren. Improving the processing algorithm of Beijing MST radar power spectral density data. J Appl Meteor Sci, 2020, 31(6): 694-705. DOI:  10.11898/1001-7313.20200605.
Citation: Chen Ze, Tian Yufang, Lü Daren. Improving the processing algorithm of Beijing MST radar power spectral density data. J Appl Meteor Sci, 2020, 31(6): 694-705. DOI:  10.11898/1001-7313.20200605.

Improving the Processing Algorithm of Beijing MST Radar Power Spectral Density Data

DOI: 10.11898/1001-7313.20200605
  • Received Date: 2020-04-17
  • Rev Recd Date: 2020-08-10
  • Publish Date: 2020-10-27
  • Beijing MST radar is a unique large instrument for atmospheric dynamic structure detection in Chinese Meridian Project. It plays an essential role in the in-depth understanding of the vertical structure of atmospheric wind, waves and turbulence in the troposphere, lower stratosphere, mesosphere, and lower thermosphere in North China. Since the completion of Beijing MST radar in 2011, wind data have been well acquired. However, there is still a need for improving the extraction of some elements. To achieve this goal, the power spectral density data processing algorithms is improved mainly from two aspects including accurate noise level estimation and target signal recognition. The improved algorithm derived data, radar products, radiosonde data and ERA5 reanalysis data from 1 January to 31 December in 2012 are statistically analyzed and compared. A log-linear fitting scheme is put forward and applied to realize rapid implementation of objective determination of the noise level. The root mean square error(RMSE) of noise values between the log-linear fitting and the conventional scheme is about 0.43 dB and mean values are 168.6 dB and 168.5 dB, respectively. Results show that the noise level estimation can be fast and accurate using the log-linear fitting scheme. Based on the property that atmospheric signals have spatio-temporal consistency and diffident signals show different spectral characteristics, the target signal can be accurately identified and extracted by the improved algorithms. The RMSE of zonal wind speed between the improved algorithm derived data and radiosonde data at different height are in the range of 2-3 m·s-1 while the RMSE of zonal wind speed between radar products and radiosonde data at different height are 3-4 m·s-1. Moreover, the mean value of the spectral width derived by the improved algorithm is 2.5 m·s-1, which is less than the mean value of radar products. Under precipitation weather condition, the mean bias and RMSE of horizontal wind speed between the improved algorithm derived data and radiosonde data at different height are both less than values between radar products and radiosonde data. Results show that the improved algorithm can reduce non-atmospheric signals such as noise and intermittent clutter and effectively suppress signals caused by precipitation. Thus the effectiveness and reliability of the improved algorithm are verified, and it is relatively easy to implement.
  • Fig. 1  Beijing MST radar raw and preprocessed power spectral density and averaged noise value estimated by objective method and segment method at 0010 UTC 4 Jan 2012(eastern beam at height of 15 km)

    Fig. 2  R2 and lgR2 varying with dP using Beijing MST radar at 1510 UTC 16 Mar 2012

    Fig. 3  The comparison of noise level estimated by log-linear scheme and dichotomy scheme using power spectral density at 7.8-12 km height of Beijing MST radar in May 2012

    Fig. 4  Power spectral density of eastern and western beams at 5 heights of Beijing MST radar data processed by improved algorithm at 0010 UTC 4 Jan 2012(bold curve denotes recognized target echo)

    Fig. 5  Comparison of the horizontal wind speed and wind direction between radiosonde(1115 UTC) and Beijing MST radar products before and after improved algorithm processed(1140 UTC) on 16 Mar 2012

    Fig. 6  Comparison of annual mean(the curve) and standard deviation(the shaded) of SNR(a) and spectral width(b) between Beijing MST radar data(from 1 Jan to 31 Dec in 2012) obtained using original and improved algorithms

    Fig. 7  Comparison of the zonal and meridional wind between radiosonde and Beijing MST radar data obtained using original and improved algorithms from 1 Jan to 31 Dec in 2012

    Fig. 8  Comparison of the vertical velocity between ERA5 reanalysis and Beijing MST radar data obtained using original and improved algorithms from 1 Jan to 31 Dec in 2012

    Fig. 9  Comparison of mean values and root mean square error of zonal and meridional wind between radiosonde and Beijing MST radar data obtained using original and improved algorithms under 16-group precipitation weather conditions in 2012

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    • Received : 2020-04-17
    • Accepted : 2020-08-10
    • Published : 2020-10-27

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