雙譜濾波算法在FY-4B/AGRI海表溫度反演中的應用
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民用航天技術預先研究項目(D040405)資助


Application of Bispectral Approach in FY-4B/AGRI Sea Surface Temperature
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    風云四號氣象衛星B星(FY-4B)作為風云四號系列衛星的首發業務星,其搭載的先進的靜止軌道輻射成像儀(Advanced Geostationary Radiation Imager,AGRI)是FY-4B核心載荷之一,目前FY-4B/AGRI采用非線性海表溫度算法(NonLinear Sea Surface Temperature,NLSST)進行海表溫度產品反演處理。為去除FY-4B/AGRI海表溫度產品中出現的條紋噪聲,將雙譜濾波算法應用于NLSST算法中的紅外分裂窗通道亮溫差數據進行濾波。雙譜濾波算法采用的核函數基于輻射傳輸物理過程,可去除海表溫度產品中存在的條紋噪聲和隨機噪聲,且不會降低產品的空間分辨率。以現場實測海表溫度數據為參考海溫,對FY-4B/AGRI分裂窗亮溫差去條紋后的海表溫度產品進行檢驗,時空匹配窗口選擇時間30 min、空間距離4 km。評估表明:雙譜濾波算法可以有效抑制條紋噪聲,提高海表溫度產品圖像可視化質量,改善海表溫度產品的精度。

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    Fengyun-4B is the first operational satellite of the second-generation FengYun geostationary meteorological satellite. The Advanced Geostationary Radiation Imager (AGRI), a multiple channel radiation imager, which adds a low-level water vapour detection channel and an adjusted spectrum range of four channels to improve the quality of observation, is one of the primary payloads onboard FY-4B. As one of the basic quantitative remote sensing products of FY-4B/AGRI, the operational sea surface temperature (SST) derives from the split-window nonlinear SST (NLSST) algorithm in real time. The stripe noise is a common issue in sea surface temperatures (SSTs) retrieved from thermal infrared data obtained by satellite-based multidetector radiometers. It degrades not only image quality but also the accuracy of retrieved SSTs. The stripe noise is observed in FY-4B/AGRI SSTs. It is more obvious in the brightness temperature difference (BTD) of the split window data, but the stripe noise is invisible in brightness temperature (BT) images. The stripe noise originates from the relative noise in the BTD. It propagates into SSTs by degrading the atmospheric correction. The bispectral filter approach for removing the stripe noise is applied to FY-4B/AGRI data. The bispectral filter is a Gaussian filter and an optimal estimation method for the differences between the data obtained at the split window. A kernel function based on the physical processes of radiative transfer has made it possible to reduce stripe and random noise in retrieved SSTs without degrading the spatial resolution or generating bias. For the assessment of the bispectral filter approach, the retrieved FY-4B/AGRI SST is validated against in-situ SST measurements available from in-situ SST Quality Monitor (iQUAM). Robust statistics are used to assess the impacts of the bispectral filter on SST accuracy. The accuracy and precision of the bispectral filter approach are assessed by determining the robust standard deviation and median bias between FY-4B/AGRI SST and quality-controlled in-situ SST from May to Norember 2023. The matchup space-time window is 4 km and 30 mins from the buoys’ location to the centre of the SST pixel. The validation results demonstrate the effectiveness of the bispectral filter, which reduces stripe noise in the retrieved FY-4B/AGRI SSTs. The image of a bispectral-filtered BTD is clearer than that of an unfiltered BTD. It also improves the accuracy of the SSTs by about 0.04 K to 0.06 K in the robust standard deviation. Furthermore, the bispectral filter approach is based on a simple Gaussian filter and is easy to implement. However, the bispectral filter cannot remove the stripe noise in BT. Such noise should be removed before applying the bispectral filter.

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崔鵬,王素娟.雙譜濾波算法在FY-4B/AGRI海表溫度反演中的應用[J].氣象科技,2024,52(6):763~774

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  • 收稿日期:2024-03-22
  • 定稿日期:2024-09-02
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  • 在線發布日期: 2024-12-25
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