Journal of Infrared and Millimeter Waves, Volume. 41, Issue 2, 483(2022)

Research on summer Arctic cloud detection model based on FY-3D/MERSI-II infrared data

Xi WANG, Jian LIU*, and Bing-Yun YANG
Author Affiliations
  • Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites,FengYun Meteorological Satellite Innovation Center(FY-MSIC),National Satellite Meteorological Center,Beijing 100081,China
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    Figures & Tables(11)
    Simulated results of Arctic summer clear and cloudy conditions over sea ice cover by Streamer model(a)brightness temperature and(b)brightness temperature difference of selected channels from FY3D in this study
    Probability Distribution Functions for clear and cloudy pixels of different cloud detecting tests over land regions based on the data from FY3D/MERSI-II(black lines:clear;blue lines:cloudy)
    Same as Fig. 2 for ocean regions
    Same as Fig. 2 for sea ice regions
    Thresholds of different cloud detecting tests for ocean,land,and sea ice regions. The gray horizontal line represents the clear condition;the blue horizontal line represents the cloudy condition. The starting point of the horizontal line represents the maximum and minimum value of the distribution;the center of the line represents the median of the distribution;the vertical line represents the threshold(black:ocean;red:land;green:sea ice)
    A case of(a)final confidence level of cloud detection and(b)brightness temperature of infrared window channel 10.8 μm at 0625UTC on June 10,2020
    Same case as Fig. 6 for brightness temperature of infrared window channel 10.8 μm and its matching CALIPSO scanning track(yellow line)
    Same case as Fig. 6.(a)final confidence level of cloud detection(black lines)vs. CALIPSO cloud top height(blue lines);(b)ratios of clear and cloudy pixels in the corresponding interval of confidence level,where the interval is set as:0~0.2,0.2~0.4,0.4~0.6,0.6~0.8,0.8~1.0
    • Table 1. Characteristics of channels of FY-3D/ MERSI-II applied in this study

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      Table 1. Characteristics of channels of FY-3D/ MERSI-II applied in this study

      通道号

      中心波长

      /μm

      光谱带宽

      /nm

      空间

      分辨率

      /m

      动态范围

      /K

      203.81801 000200~350
      214.0501551 000200~380
      227.25001 000180~280
      238.5503001 000180~300
      2410.81000250180~330
      2512.01000250180~330
    • Table 2. Thresholds and loss functions of different cloud detecting tests for different surface types

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      Table 2. Thresholds and loss functions of different cloud detecting tests for different surface types

      海洋陆表海冰永久冰川积雪
      阈值损失率阈值损失率阈值损失率阈值损失率阈值损失率
      BT10.8271.110.457271.900.342270.490.371263.370.535270.990.311
      BT7.2252.190.574251.300.467251.480.489250.000.424251.050.400
      BTD3.8-122.340.2779.810.3534.710.2328.000.2618.370.341
      BTD10.8-3.8-2.070.263-8.410.346-4.270.230-7.910.266-7.750.342
      BTD8.55-10.8-0.340.795-1.290.623-1.950.8310.310.891-1.540.786
      BTD3.8-4.053.330.2906.320.4054.340.2316.720.3026.590.407
    • Table 3. HR results and weighting functions of cloud detecting tests by FY-3D/MERSI-II for Arctic summer

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      Table 3. HR results and weighting functions of cloud detecting tests by FY-3D/MERSI-II for Arctic summer

      检测方案海洋陆表海冰永久冰川积雪
      HR权重HR权重HR权重HR权重HR权重
      BT10.80.7480.1600.6870.1580.2170.0510.4950.1210.7630.171
      BT7.20.3410.0730.6730.1550.6880.1630.5470.1340.7100.159
      BTD3.8-120.9540.2040.8130.1870.9270.2200.8290.2030.8700.195
      BTD10.8-3.80.9450.2020.8100.1870.9120.2160.8470.2080.8530.191
      BTD8.55-10.80.7300.1560.6130.1410.5530.1310.6000.1470.6410.144
      BTD3.8-4.050.9510.2040.7420.1710.9230.2190.7600.1860.6290.141
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    Xi WANG, Jian LIU, Bing-Yun YANG. Research on summer Arctic cloud detection model based on FY-3D/MERSI-II infrared data[J]. Journal of Infrared and Millimeter Waves, 2022, 41(2): 483

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    Paper Information

    Category: Research Articles

    Received: Jun. 21, 2021

    Accepted: --

    Published Online: Jul. 8, 2022

    The Author Email: Jian LIU (liujian@cma.cn)

    DOI:10.11972/j.issn.1001-9014.2022.02.015

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