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张玉荣, 姚晓娟, 狄迪, 等. 2023. 联合静止气象卫星成像仪和高光谱红外大气探测仪观测的三维水平风场反演[J]. 大气科学, 47(6): 1891−1906. doi: 10.3878/j.issn.1006-9895.2209.22093
引用本文: 张玉荣, 姚晓娟, 狄迪, 等. 2023. 联合静止气象卫星成像仪和高光谱红外大气探测仪观测的三维水平风场反演[J]. 大气科学, 47(6): 1891−1906. doi: 10.3878/j.issn.1006-9895.2209.22093
ZHANG Yurong, YAO Xiaojuan, DI Di, et al. 2023. Three-Dimensional Wind Field Retrieval by Combining Measurements from Imager and Hyperspectral Infrared Sounder Onboard the Same Geostationary Platform [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(6): 1891−1906. doi: 10.3878/j.issn.1006-9895.2209.22093
Citation: ZHANG Yurong, YAO Xiaojuan, DI Di, et al. 2023. Three-Dimensional Wind Field Retrieval by Combining Measurements from Imager and Hyperspectral Infrared Sounder Onboard the Same Geostationary Platform [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(6): 1891−1906. doi: 10.3878/j.issn.1006-9895.2209.22093

联合静止气象卫星成像仪和高光谱红外大气探测仪观测的三维水平风场反演

Three-Dimensional Wind Field Retrieval by Combining Measurements from Imager and Hyperspectral Infrared Sounder Onboard the Same Geostationary Platform

  • 摘要: 风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期间FY-4A加密观测(15分钟间隔)的GIIRS数据开展晴空和部分云区的三维水平风场算法研究,重点研究如何联合同一卫星平台的多光谱成像仪(AGRI)改进GIIRS部分云视场区的三维风场反演结果。利用ERA5独立测试集、CRA40再分析和空投探空数据开展对晴空和云区的三维风场反演结果的检验,基于该个例的反演结果表明:(1)基于GIIRS亮温信息反演得到对流层水平风场,在晴空区均方根误差小于1.5 m s−1,方向绝对差基本在15°左右,在部分云视场区,均方根误差为1.5~1.7 m s−1,方向绝对差基本在20°左右。与光流法相比,基于GIIRS亮温的直接反演表现出更好的优势,其均方根误差和方向绝对差明显小于光流法的结果。(2)按云量和云顶高度分类后,表现出云量越多、云顶高度越高则RMSE(Root Mean Square Error)越大。在部分云视场区,进一步在反演模型输入中加入来自同平台上成像仪(AGRI)云量和云高信息后,RMSE有所减小,表明更高空间分辨率的AGRI产品可以改进GIIRS部分云覆盖区的风场反演精度。(3)基于GIIRS亮温信息反演的风廓线与CRA40再分析、空投探测风廓线有较好的一致性,表明利用静止卫星红外高光谱大气探测仪观测亮温反演风场的合理性和可行性。

     

    Abstract: The Geosynchronous Interferometric Infrared Sounder (GIIRS) onboard Fengyun-4A (FY-4A) is the first geostationary hyperspectral infrared IR sounder. It can provide continuous three-dimensional (3D) data on atmospheric temperature, water vapor, and atmospheric horizontal wind fields at various altitudes by tracking water vapor movements. In this study, GIIRS data from FY-4A observations at 30-min intervals during Typhoon Maria (2018) were used. Our aim was to test a 3D horizontal wind field algorithm in both clear and partially cloudy skies, emphasizing the enhancement of 3D wind field retrieval from partially cloud-filled GIIRS footprints by incorporating collocated high-spatial resolution cloud products from the Advanced Geostationary Radiation Imager (AGRI) onboard the same platform. Independent ERA5 and CRA40 analyses, as well as radiosonde data, were used as reference data for verifying 3D horizontal wind field retrievals in both clear and partially cloudy skies. The results indicate that tropospheric wind fields can be obtained from GIIRS brightness temperature (BT) measurements from two consecutive times. In clear skies, the root mean square error (RMSE) is less than 1.5 m s−1, with an absolute direction difference between retrievals and reference data of approximately 15° in this case. In partially cloudy skies, the RMSE is 1.5–1.7 m s−1, with an absolute direction difference of approximately 20°. Compared with the traditional optical flow method, the GIIRS BT-based direct retrieval method exhibits superior accuracy, with smaller RMSE and direction absolute difference. When classified by cloud coverage (CC) and cloud-top pressure (CTP), a larger cloud cover or higher cloud top results in a greater RMSE. However, when CC and CTP are included as additional input parameters, RMSE decreased, indicating that high-spatial resolution AGRI cloud products can improve wind field retrieval accuracy in some cloud-covered areas. Finally, wind profile retrievals from the GIIRS BT-based method are consistent with wind profiles obtained through CRA40 analysis and dropsonde data, indicating the feasibility of deriving 3D horizontal wind fields from geostationary hyperspectral IR BT measurements.

     

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