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FY-4A/AGRI Sea Surface Temperature Product and Quality Validation
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摘要: 风云四号气象卫星A星(FY-4A)是我国第2代静止气象卫星首发星，搭载的先进静止轨道辐射成像仪AGRI是迄今为止我国静止轨道最先进的辐射成像仪。海表温度产品是FY-4A/AGRI基础定量产品之一，采用非线性海表温度算法在业务系统实时反演得到。以现场实测海表温度数据为参考，选择观测时间为30 min、观测空间距离为4 km的时空匹配窗口，对FY-4A/AGRI海表温度产品进行质量检验，评估结果表明：质量为优的像元平均偏差为-0.45~-0.42℃，标准差为0.81~0.88℃，相关系数在0.985以上。以Himawari-8/AHI海表温度数据为参考，按观测时间为1 h、空间距离为4 km的时空匹配窗口，对FY-4A/AGRI海表温度进行质量检验，质量为优的像元平均偏差为-0.26~-0.07℃，标准差为0.68~0.82℃，两者相关系数在0.985以上，达到0.001显著性水平。
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关键词:
- FY-4A/AGRI;
- 海表温度;
- 质量控制
Abstract: Fengyun-4A (FY-4A) is the first satellite of China's second-generation geostationary orbit meteorological satellites. The advanced geostationary radiation imager (AGRI), a multiple channel radiation imager, is one of the primary payloads onboard FY-4A. As one basic quantitative remote sensing product, the operational sea surface temperature (SST) is derived with the split-window nonlinear SST (NLSST) algorithm in real time. The operational NLSST procedures and products are described in detail. The FY-4A/AGRI SST products provide full-disk SST with spatial resolution of 4 km at the nadir. The quality level information is delivered with each pixel to provide information about the conditions of the processing. Quality level for each pixel information is defined as follows: Excellent, good, bad and unprocessed (cloud, land, no satellite data etc.). The users can select the SST data with certain quality level according to their application purposes (e.g., for climate-related studies, only the SST data with the excellent quality level in the time series are used, and for identifying and tracking specific ocean features, users may be more tolerant of lower-quality SST data). The accuracy of FY-4A/AGRI SST algorithm is assessed by determining the standard deviation and bias errors from the regression procedure of the matchup database between satellite data and quality controlled SST data from NOAA in situ SST quality monitor, from July 2021 to June 2022. The validation methods and results are described in detail. The matchup database combining FY-4A/AGRI measurements and in situ SST have been built on a routine basis. At the stage of the matchup database in association with the drifter temperatures, the matchup database is composed of pixels under clear sky conditions. The FY-4A/AGRI SST data with excellent quality level are compared with drifting and tropical moored buoy data. The matchup space-time window is 4 km and 30 min from the buoy location to the center of the SST pixel. The comparison shows a bias of -0.45 to -0.42℃ and a standard deviation of 0.81-0.88℃ for FY-4A/AGRI SST with excellent quality. The correlation coefficients between FY-4A/AGRI SST and buoy SST are better than 0.985. The FY-4A/AGRI SST are also compared with the ACSPO SST produced at NOAA/STAR from the Himawari-8/AHI (advanced Himawari imager). The comparison shows a bias of -0.26 to -0.07℃ and a standard deviation of 0.68-0.82℃ with excellent quality level. The correlation coefficients between FY-4A/AGRI SST and Himawari-8/AHI are better than 0.985. The correlation coefficients shows that there is a good correlation between FY-4A/AGRI SST and Himawari-8/AHI SST.-
Key words:
- FY-4A/AGRI;
- sea surface temperature;
- quality control
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图 1 2021年7月—2022年6月FY-4A/AGRI海表温度和浮标海表温度偏差直方图
Fig. 1 Histogram of difference between FY-4A/AGRI SST and buoy SST from Jul 2021 to Jun 2022
图 2 2021年7月—2022年6月FY-4A/AGRI海表温度和浮标海表温度散点密度图
Fig. 2 Scatter density map of FY-4A/AGRI SST and buoy SST from Jul 2021 to Jun 2022
图 3 2021年7月—2022年6月5°×5°经纬度方块内FY-4A/AGRI海表温度和浮标海表温度偏差空间分布
Fig. 3 Biases in 5°×5° square of FY-4A/AGRI SST against buoy SST from Jul 2021 to Jun 2022
图 4 2021年7月—2022年6月以浮标海表温度为参考的FY-4A/AGRI海表温度误差时间序列
Fig. 4 Time series of bias and standard deviation of FY-4A/AGRI SST relative to buoy SST from Jul 2021 to Jun 2022
图 5 2021年7月—2022年6月以Himawari-8/AHI海表温度为参考的质量等级为优的FY-4A/AGRI海表温度误差时间序列
Fig. 5 Time series of bias and standard deviation of excellent quality FY-4A/AGRI SST relative to Himawari-8/AHI SST from Jul 2021 to Jun 2022
图 6 FY-4A/AGRI海表温度和Himawari-8/AHI海表温度散点图
(a)2021年7月1日、8月1日和9月1日，(b)2021年10月1日、11月1日和12月1日，(c)2022年1月1日、2月1日和3月1日，(d)2022年4月1日、5月1日和6月1日
Fig. 6 Scatter density map of FY-4A/AGRI SST and Himawari-8/AHI SST
(a)1 Jul, 1 Aug and 1 Sep in 2021, (b)1 Oct, 1 Nov and 1 Dec in 2021, (c)1 Jan, 1 Feb and 1 Mar in 2022, (d)1 Apr, 1 May and 1 Jun in 2022
表 1 FY-4A/AGRI NLSST算法误差信息
Table 1 SST deviation of FY-4A/AGRI NLSST algorithm
统计量 白天 夜间 偏差/℃ 0.01 0.05 绝对偏差/℃ 0.5 0.53 标准差/℃ 0.61 0.66 样本量 7381 7803 
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表 2 以浮标海表温度为参考的FY-4A/AGRI海表温度误差统计
Table 2 Error information of FY-4A/AGRI SST relative to buoy SST
时段 统计量 优 良 差 白天 平均偏差/℃ -0.45 -1.00 -2.25 标准差/℃ 0.81 0.94 1.94 样本量 171473 81570 35607 夜间 平均偏差/℃ -0.42 -0.99 -2.94 标准差/℃ 0.88 1.03 1.99 样本量 199364 92084 76844 晨昏 平均偏差/℃ -0.42 -1.02 -2.80 标准差/℃ 0.85 0.99 1.97 样本量 28501 12386 8598
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