Zhou Xuesong, Guo Qiyun, Xia Yuancai, et al. Inspection of FY-3D satellite temperature data based on horizontal drift round-trip sounding data. J Appl Meteor Sci, 2023, 34(1): 52-64. DOI:  10.11898/1001-7313.20230105.
Citation: Zhou Xuesong, Guo Qiyun, Xia Yuancai, et al. Inspection of FY-3D satellite temperature data based on horizontal drift round-trip sounding data. J Appl Meteor Sci, 2023, 34(1): 52-64. DOI:  10.11898/1001-7313.20230105.

Inspection of FY-3D Satellite Temperature Data Based on Horizontal Drift Round-trip Sounding Data

DOI: 10.11898/1001-7313.20230105
  • Received Date: 2022-08-28
  • Rev Recd Date: 2022-10-25
  • Publish Date: 2023-01-31
  • The horizontal drift round-trip sounding observation is a new sounding technology developed by China Meteorological Administration. By releasing one sounding balloon with this technology, three sections of observations can be obtained, including two sections of vertical tropospheric sounding(ascending and descending) with an interval of about 6 hours and a 4-hour horizontal sounding within the stratosphere. This technology effectively makes up for the insufficiency of conventional soundings, improving the time and space resolution of radiosonde data at a lower cost. The detection system adopts Beidou radiosonde, which significantly improves the accuracy of sounding and wind measurements. In addition, the drift section of horizontal drift round-trip sounding observation fills the gap of the stratospheric temperature detection technology in China. Therefore, horizontal drift round-trip sounding data can be used to verify the temperature profile and stratosphere temperature data of meteorological satellite.Fengyun series meteorological satellites are widely used in China, supporting the meteorological forecast in the Eastern Hemisphere. Among Fengyun satellites in use, FY-3D has the longest years of service. To test the accuracy of FY-3D satellite temperature products, an algorithm is designed according to the characteristics of the horizontal drift round-trip sounding data and satellite data, and the temporal and spatial thresholds are calculated. Based on this algorithm, FY-3D satellite retrieved atmospheric temperature data are verified using the horizontal drift round-trip sounding data in the middle and lower reaches of the Yangtze from March to September in 2021. It can be concluded from the inspection results that the temperature data of FY-3D satellite has a high accuracy, with an average absolute deviation of about 1.34℃ from the data of ascending section and 1.9℃ from the data of descending section. Above 100 hPa and below 850 hPa, the temperature errors of satellite data are 0.59℃ and 0.33℃ larger, respectively. The average absolute deviation of the stratosphere is about 3.92℃, which is slightly larger than the ascending section and descending section. Compared with the sounding profile, the satellite temperature profile has lower vertical resolution and smoother trend, so it cannot show more details of atmospheric vertical variation.
  • Fig. 1  Ascending section of Nanchang Station at 0730 BT 11 Apr 2021

    (a)temperature profiles from satellite and original sounding, (b)temperature profiles from satellite and sparse sounding, (c)temperature error varying with air pressure, (d)error distribution of temperature profile(red curve denotes fitting curve)

    Fig. 2  Ascending section of Ganzhou Station at 1930 BT 5 Apr 2021

    (a)temperature profiles from satellite and original sounding, (b)temperature profiles from satellite and sparse sounding, (c)temperature error varying with air pressure, (d)error distribution of temperature profile(red curve denotes fitting curve)

    Fig. 3  The horizontal drift section of Changsha Station at 1930 BT 11 June 2021

    (a)satellite and original sounding temperature profile, (b)satellite and sparse sounding temperature profile, (c)curve of temperature error changing with time, (d)error distribution of temperature profile(red curve denotes fitting curve)

    Fig. 4  Descending section of Wuhan Station at 1330 BT 25 Jun 2021

    (a)temperature profiles from satellite and original sounding, (b)temperature profiles from satellite and sparse sounding, (c)temperature error varying with air pressure, (d)error distribution of temperature profile(red curve denotes fitting curve)

    Fig. 5  Descending section of Yichang Station at 0130 BT 9 Apr 2021

    (a)temperature profiles from satellite and original sounding, (b)temperature profiles from satellite and sparse sounding, (c)temperature error varying with air pressure, (d)error distribution of temperature profile(red curve denotes fitting curve)

    Table  1  Inspection and evaluation of satellite data

    平漂探空数据段 匹配次数 平均绝对偏差/℃ 均方根误差/℃ 相关系数
    上升段 367 1.34 1.95 0.99
    平漂段 249 3.92 4.10 0.04
    下降段 769 1.93 2.46 0.99
    DownLoad: Download CSV

    Table  2  Inspection and evaluation of satellite data at ascending section

    探空站 07:30 19:30
    平均绝对偏差/℃ 均方根误差/℃ 平均绝对偏差/℃ 均方根误差/℃
    武汉 1.32 1.74 1.18 1.58
    南昌 1.32 1.99 1.12 1.88
    宜昌 1.22 1.60 1.30 1.66
    安庆 1.51 1.86 1.46 2.11
    赣州 1.12 1.48 1.38 2.95
    长沙 2.15 2.95 1.06 1.34
    DownLoad: Download CSV

    Table  3  Inspection and evaluation of satellite data at horizontal drift section

    探空站 平均绝对偏差/℃ 均方根误差/℃
    武汉 3.33 3.56
    南昌 3.03 3.20
    宜昌 3.24 3.41
    安庆 4.42 4.60
    赣州 3.56 3.72
    长沙 5.97 6.09
    DownLoad: Download CSV

    Table  4  Inspection and evaluation of satellite data at descending section

    探空站 13:30 01:30
    平均绝对偏差/℃ 均方根误差/℃ 平均绝对偏差/℃ 均方根误差/℃
    武汉 3.67 4.43 2.16 2.73
    南昌 1.33 1.79 3.32 4.30
    宜昌 1.67 2.06 1.04 1.38
    安庆 1.54 2.00 1.41 2.16
    赣州 1.60 2.09 1.03 1.30
    长沙 3.26 3.79 1.13 1.51
    DownLoad: Download CSV

    Table  5  Test of satellite data at different altitudes

    高度 平均绝对偏差/℃ 均方根误差/℃
    地面至850 hPa* 1.68 1.93
    850 hPa至100 hPa** 1.16 1.62
    100 hPa至10 hPa 1.75 2.21
    注:*表示含850 hPa, **表示含100 hPa。
    DownLoad: Download CSV

    Table  6  Influence of statistical cloud on satellite inversion temperature

    探空数据段 云状态 探空湿度廓线云判识算法 FY-3D成像仪云数据
    平均绝对偏差/℃ 均方根误差/℃ 平均绝对偏差/℃ 均方根误差/℃
    上升段 有云 1.60 3.01 1.63 2.92
    无云 1.28 1.70 1.32 1.91
    下降段 有云 2.08 2.59 1.74 2.22
    无云 1.73 2.31 1.28 1.71
    DownLoad: Download CSV
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    • Received : 2022-08-28
    • Accepted : 2022-10-25
    • Published : 2023-01-31

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