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耿晓雯, 闵锦忠, 杨春, 等. 2020. FY-4A AGRI辐射率资料偏差特征分析及订正试验[J]. 大气科学, 44(4): 679−694. doi: 10.3878/j.issn.1006-9895.1907.18254
引用本文: 耿晓雯, 闵锦忠, 杨春, 等. 2020. FY-4A AGRI辐射率资料偏差特征分析及订正试验[J]. 大气科学, 44(4): 679−694. doi: 10.3878/j.issn.1006-9895.1907.18254
GENG Xiaowen, MIN Jinzhong, YANG Chun, et al. 2020. Analysis of FY-4A AGRI Radiance Data Bias Characteristics and a Correction Experiment [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 679−694. doi: 10.3878/j.issn.1006-9895.1907.18254
Citation: GENG Xiaowen, MIN Jinzhong, YANG Chun, et al. 2020. Analysis of FY-4A AGRI Radiance Data Bias Characteristics and a Correction Experiment [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 679−694. doi: 10.3878/j.issn.1006-9895.1907.18254

FY-4A AGRI辐射率资料偏差特征分析及订正试验

Analysis of FY-4A AGRI Radiance Data Bias Characteristics and a Correction Experiment

  • 摘要: 风云四号A星(Fengyun-4A,简称FY-4A)作为我国最新一代静止气象卫星,各方面技术指标都体现了“高、精、尖”特色,处于国际领先地位。其上搭载的多通道扫描成像辐射计(Advanced Geosynchronous Radiation Imager,简称AGRI)较上一代静止卫星风云二号的可见光红外自旋扫描辐射仪观测精度更高、扫描时间更短,充分体现AGRI观测资料将有效提高“一带一路”沿线国家和地区的天气预报和灾害预警水平。偏差订正是卫星资料处理的重要环节之一,因此本文通过在WRFDA v3.9.1(Weather Research and Forecasting model’s Data Assimilation v3.9.1)搭建AGRI同化接口,利用RTTOV v11. 3辐射传输模式和GFS全球预报系统(Global Forecast System)分析场研究了FY-4A AGRI红外通道8~14晴空辐射率资料的偏差特征并进行偏差订正对比试验,分析了卫星天顶角对AGRI资料偏差订正的影响,为将来实现AGRI红外通道辐射率资料在中尺度模式中的同化应用奠定基础。结果表明:(1)通道8~10及14为正偏差,通道11~13为负偏差。水汽通道9和10偏差及其标准差相对较小,偏差海陆差异不明显。通道11~14探测高度较低,陆地上观测受地表发射率影响大,质量控制时可剔除这些通道陆地上的观测。(2)各通道偏差随卫星天顶角变化的拟合直线斜率都小于0.035,对比试验结果表明偏差与卫星天顶角的关系不明显,预报因子中无需考虑卫星天顶角的作用。(3)通道8及11~14的偏差随着目标亮温的变化比水汽通道9~10明显,偏差有较强的目标亮温依赖特征。(4)根据分析的偏差特征对2018年5月13日18时(协调世界时,下同)至15日18时进行变分偏差订正试验,系统性偏差得到了有效的订正。

     

    Abstract: As the latest generation of geostationary meteorological satellites in our country, a significant development has been made for Fengyun-4A (FY-4A). Compared with the previous generation (Fengyun-2), FY-4A has better observation accuracy and a shorter scanning time. Taking full advantage of the advanced geosynchronous radiation imager (AGRI) data, the level of weather and meteorological disasters forecasting in countries along the “The Belt and Road Initiatives” will be effectively improved. The interface for the FY-4A AGRI data assimilation is complemented in Weather Research and Forecasting Data Assimilation (WRFDA) v3.9.1 model before investigating the bias characteristics based on RTTOV v11.3 model and GFS analysis. Bias-correction experiments of FY-4A AGRI data in infrared Channels 8–14 were further conducted. The results show that: (1) Channels 8–10 and 14 have warm biases. There are cold biases in Channels 11–13. The biases and standard deviation of the water vapor Channels 9 and 10 are small. The characteristics of the biases show obvious differences between land and ocean in Channels 11–14. Land’s biases are more complex than the ocean’s. For these channels, observations on land can be eliminated in quality control. (2) The slope of the linear regression equation between bias and satellite zenith angle is less than 0.035. There is no obvious dependence of biases on the satellite zenith angle. (3) The bias in Channels 8 and 11–14 show more obvious dependence on the scene temperature than those in Channels 9 and 10. (4) The variational bias correction tested during 1800 UTC on May 13–15, 2018 shows that the systematic bias was effectively corrected.

     

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