Lei Yong, Guo Qiyun, Qian Yuan, et al. Evaluation and quality mark of radiosonde geopotential height of L-band radar. J Appl Meteor Sci, 2018, 29(6): 710-723. DOI:  10.11898/1001-7313.20180607.
Citation: Lei Yong, Guo Qiyun, Qian Yuan, et al. Evaluation and quality mark of radiosonde geopotential height of L-band radar. J Appl Meteor Sci, 2018, 29(6): 710-723. DOI:  10.11898/1001-7313.20180607.

Evaluation and Quality Mark of Radiosonde Geopotential Height of L-band Radar

DOI: 10.11898/1001-7313.20180607
  • Received Date: 2018-04-27
  • Rev Recd Date: 2018-08-08
  • Publish Date: 2018-11-30
  • Using analysis data of NCEP FNL and forecast data of GRAPES_GFS as background fields, the error analysis of geopotential height(sounding height) data of Beijing sounding station are obtained from observation residuals, average deviations, standard deviation, probability density distributions, kurtosis coefficients, skewness coefficients, correlation coefficient and root mean square error. According to assessment results, data quality is marked, and parameters are solved according to results of the quality mark. Test results show whether based on NCEP FNL or GRAPES_GFS, the error of the sounding height is basically within ±5 dagpm, and the absolute value of observation residuals increases with the decrease of air pressure. Observation residuals below 100 hPa is basically within ±3 dagpm. Observation residuals are mostly negative at the top of 100 hPa. The average deviation, standard deviation, probability density distribution, kurtosis coefficient, skewness coefficient, correlation coefficient and root mean square error are analyzed and evaluated from characteristics and distribution characteristics of the seasonal error, all of which show that the quality of data at height of detection potential is good, and each parameter is close to their optimal state. However, at the high level (10-30 hPa), the average deviation and standard deviation show obviously that the evaluation result of GRAPES_GFS is better than that of NCEP FNL, and the other parameters are basically the same and the difference is small. The average deviations plus standard deviation of two times is selected as the suspicious threshold value of the potential height at a single moment, and average deviation plus standard deviation is selected as the error threshold of the potential height. This choice is not only meaningful in mathematical statistics, but also shows that the threshold value is based on the background field error feature and self-adaptive threshold value, which can help to find out the true error point for correction.
  • Fig. 1  The residuals error, wrong value profiles and suspicious value profiles of geopotential height between NCEP FNL and the sounding at 0000 UTC

    (a)15 Jul 2016, (b)15 Oct 2016, (c)15 Jan 2017, (d)15 Apr 2017

    Fig. 2  The residuals error, wrong value profiles and suspicious value profiles of geopotential height between GRAPES_GFS and the sounding at 0000 UTC

    (a)15 Jul 2016, (b)15 Oct 2016, (c)15 Jan 2017, (d)15 Apr 2017

    Fig. 3  The average deviation and the standard deviation of sounding height in different seasons at 0000 UTC

    (a)average deviation based on NCEP FNL, (b)standard deviation based on NCEP FNL, (c)average deviation based on GRAPES_GFS, (d)standard deviation based on GRAPES_GFS

    Fig. 4  The probability density distribution of 500 hPa sounding height deviation based on NCEP FNL at 0000 UTC

    (a)spring, (b)summer, (c)autumn, (d)winter, (e)kurtosis coefficient, (f)skewness coefficient

    Fig. 5  The probability density distribution of 500 hPa sounding height deviation based on GRAPES_GFS at 0000 UTC

    (a)spring, (b)summer, (c)autumn, (d)winter, (e)kurtosis coefficient, (f)skewness coefficient

    Fig. 6  The geopotential height scatter diagram of 500 hPa based on NCEP FNL in different seasons at 0000 UTC

    (a)spring, (b)summer, (c)autumn, (d)winter

    Fig. 7  The geopotential height scatter diagram of 500 hPa based on GRAPES_GFS in different seasons at 0000 UTC

    (a)spring, (b)summer, (c)autumn, (d)winter

    Fig. 8  Deviation distribution of sounding height after quality mark at 0000 UTC

    (a)based on NCEP FNL, (b)based on GRAPES_GFS

    Fig. 9  The average deviation and the standard deviation of sounding height after the quality mark in different seasons

    (a)average deviation based on NCEP FNL, (b)standard deviation based on NCEP FNL, (c)average deviation based on GRAPES_GFS, (d)standard deviation based on GRAPES_GFS

    Table  1  Root mean square error of sounding height based on NCEP FNL(unit:dagpm)

    季节 时间 1000 hPa 925 hPa 900 hPa 850 hPa 700 hPa 500 hPa
    春季 00:00 1.28 1.20 1.52 1.01 1.05 1.21
    12:00 1.28 1.05 1.48 1.02 1.09 1.11
    夏季 00:00 1.11 1.05 1.03 0.97 0.90 1.21
    12:00 1.08 1.04 1.33 0.92 0.95 1.20
    秋季 00:00 1.05 0.84 1.05 0.97 0.97 1.09
    12:00 1.07 0.92 1.37 0.90 0.97 1.24
    冬季 00:00 1.29 1.04 1.48 1.07 0.99 1.37
    12:00 1.15 1.07 1.82 0.89 1.05 1.18
    DownLoad: Download CSV

    Table  2  Root mean square error of sounding height based on GRAPES_GFS(unit:dagpm)

    季节 时间 1000 hPa 925 hPa 900 hPa 850 hPa 700 hPa 500 hPa
    春季 00:00 1.38 1.18 1.77 0.97 1.25 1.40
    12:00 1.15 1.03 1.53 1.07 1.15 1.39
    夏季 00:00 1.14 1.09 1.17 1.11 1.00 1.29
    12:00 0.95 1.04 1.45 1.14 0.98 1.30
    秋季 00:00 1.08 0.99 1.45 1.17 1.11 1.21
    12:00 1.21 1.14 1.58 0.92 1.04 1.41
    冬季 00:00 1.25 0.80 1.58 0.94 1.08 1.48
    12:00 1.17 1.17 1.94 0.92 1.35 1.43
    DownLoad: Download CSV
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    • Received : 2018-04-27
    • Accepted : 2018-08-08
    • Published : 2018-11-30

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