An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer

Xiaoheng Mou Wenming Lin

Xiaoheng Mou, Wenming Lin. An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-024-2322-y
Citation: Xiaoheng Mou, Wenming Lin. An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-024-2322-y

doi: 10.1007/s13131-024-2322-y

An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer

Funds: The National Key Research and Development Program of China under Grant 2022YFC3104900 and 2022YFC3104902.
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  • Figure  1.  Wind speed bias as a function CSCAT wind speed and the sorted percentiles by MLE for the near-real-time wind product (a) and the reprocessed wind data (b). The black dashed curve indicates the rejection ratio of the operational MLE-based QC.

    Figure  2.  Illustration of the WVCs at different swaths, where black, blue and red circles represent the outer swath, the sweet swath and the nadir region, respectively.

    Figure  3.  VRMS difference between CSCAT and NWP (upper panels), and the percentage of rain-contaminated data (GPM RR > 0 mm/h) (lower panels), as a function of the sorted percentiles by MLE (blue), MLEm (red), and SE (orange) for the nadir region (a and d), the sweet region (b and e), and the outer swath (c and f), respectively.

    Figure  4.  Percentage of rain-contaminated data (GPM RR > 1 mm/h) as a function CSCAT wind speed and the sorted percentiles by MLE (a), MLEm (b), and SE (c). The black dashed curve indicates the (objective) rejection ratio of the operational MLE-based QC.

    Figure  5.  CSCAT wind vectors superimposed on the map of wind speed (a–c) and the collocated GPM RR (d). White (black) arrows indicate the winds rejected (accepted) by the MLE-based QC (a), the MLEm-based QC (b), and the SE-based QC (c).

    6.  CSCAT reprocessed winds versus buoy wind speed (a) and wind direction(b) accepted by the operational MLE-based QC. (c) and (d), (e) and (f), (g), and (h) are the same, but for MLEm-based QC, SE-based QC and the proposed new QC, respectively.

    Table  1.   VRMS difference between CSCAT and NWP winds categorized by different QC methods under different wind speed conditions


    Wind speed/(m · s-1)
    Statistical results
    over the QC accepted data/(m · s-1)
    Statistical results
    over the QC rejected data/(m · s-1)
    MLEMLEmSEMLEMLEmSE
    w < 21.961.961.962.242.222.28
    2< w <141.921.911.903.543.603.74
    w > 142.162.142.082.882.953.19
    下载: 导出CSV

    Table  2.   VRMS difference between CSCAT and buoy winds categorized by different QC methods in different wind speed bins


    Wind speed/(m · s-1)
    Statistical results
    over the QC accepted data/(m · s-1)
    Statistical results
    over the QC rejected data/(m · s-1)
    MLEMLEmSEMLEMLEmSE
    w < 22.262.252.234.844.545.71
    2< w< 142.562.542.505.495.475.92
    w > 145.374.874.646.517.407.62
    下载: 导出CSV

    Table  3.   VRMS difference between CSCAT and buoy winds categorized by different QC methods


    Swath
    Statistical results over the QC accepted data/(m · s-1)Statistical results over the QC rejected data/(m · s-1)
    MLEMLEmSEMLEMLEmSE
    Nadir region2.812.872.714.725.315.83
    Sweet region2.622.732.565.415.855.73
    Outer swath2.983.112.885.815.796.19
    Note: The first row shows the statistics for the nadir region WVCs, the second row for the sweet region WVCs, and the third row for the outer swath WVCs.
    下载: 导出CSV

    Table  4.   Percentage of rain contaminated data (with GPM RR > 0 mm/h or GPM RR >1 mm/h) for the QC-rejected data by different quality indicators over the three swath regions


    Swath
    Percentage of GPM RR > 0 mm/h over the QC rejected data/%Percentage of GPM RR > 1 mm/h over the QC rejected data/%
    MLEMLEmSEMLEMLEmSE
    Nadir region51.058.547.724.128.120.0
    Sweet region54.361.350.426.129.822.4
    Outer swath48.955.253.023.426.825.0
    下载: 导出CSV

    Table  5.   Percentage of rain contaminated data (with GPM RR > 0 mm/h or GPM RR >1 mm/h) over the QC-rejected data by different QC indicators in different wind speed bins

    Wind speed/
    (m · s-1)
    Percentage of GPM RR > 0 mm/h over the QC rejected data/%Percentage of GPM RR > 1 mm/h over the QC rejected data/%
    MLEMLEmSEMLEMLEmSE
    w<28.523.331.51.24.75.8
    2<w<1454.561.050.128.131.423.7
    w>1452.353.357.717.718.721.1
    下载: 导出CSV

    Table  6.   Percentage of rain-contaminated data (with GPM RR > 0 or 1 mm/h) over the QC-rejected WVCs for different swaths


    Swath
    Percentage of GPM RR > 0 mm/h
    over all rain contaminated data/%
    Percentage of GPM RR > 1 mm/h
    over all rain contaminated data/%
    MLEMLEmSEMLEMLEmSE
    Nadir region17.119.016.18.19.16.7
    Sweet region18.620.317.38.99.97.7
    Outer swath16.818.318.28.08.98.6
    下载: 导出CSV

    Table  7.   Percentage of rain contaminated data (with GPM RR > 0 or 1 mm/h) over the QC-rejected WVCs for different wind speed bins


    Wind speed/ (m · s-1)
    Percentage of GPM RR > 0 mm/h
    over all rain contaminated data/%
    Percentage of GPM RR > 1 mm/h
    over all rain contaminated data/%
    MLEMLEmSEMLEMLEmSE
    w<21.63.96.10.20.81.2
    2<w<1417.719.916.69.110.27.8
    w>1419.119.020.76.56.77.5
    下载: 导出CSV
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  • 收稿日期:  2023-12-26
  • 录用日期:  2024-02-28
  • 网络出版日期:  2024-04-30

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