FY-3C/VIRR数据中国周边海域区域SST反演算法开发

已有的验证结果显示风云三号C星（Fengyun-3C，FY-3C）搭载的可见光红外辐射仪（visible and infrared radiometer，VIRR）反演的业务化海洋表面温度（sea surface temperature，SST）产品存在较大偏差。根据FY-3C/VIRR的热红外通道设置，分别选择非线性SST算法（non-linear SST，NLSST）和三通道非线性算法（triple window NLSST，TNLSST）开发适用于中国周边海域的白天和夜间区域SST反演算法。通过对卫星热红外波段的亮温和现场数据进行晴空海洋匹配样本数据构建，利用回归拟合方法获得NLSST和TNLSST的算法系数。采用独立样本数据对区域算法进行验证，白天数据的偏差和标准差分别为0.082 ℃和0.633 ℃，夜间为?0.007 ℃和0.557 ℃。以OISST（optimum interpolation SST）为参考值，将区域算法反演的SST与国家卫星气象中心的业务产品进行对比，结果显示区域算法将白天SST的偏差和标准偏差从0.047 ℃和0.743 ℃减小到0.031 ℃和0.641 ℃，夜间从0.184 ℃和0.708 ℃减小到0.034 ℃和0.556 ℃。

Development of regional SST algorithm for FY-3C/VIRR data in the seas around China

Previous validation results showed that there was large bias in the operational sea surface temperature (SST) products from the visible and infrared radiometer (VIRR) onboard the Fengyun-3C (FY-3C) polar-orbiting meteorological satellite released by the national satellite meteorological center (NSMC). According to the setting of thermal infrared channels of FY-3C/VIRR, the regional algorithms to estimate daytime and nighttime SST in the seas around China were developed based on the non-linear SST (NLSST) and triple window NLSST (TNLSST). The clear-sky sea matchup data was generated from the bright temperature of satellite thermal infrared channels and in situ data, and the coefficients of NLSST and TNLSST were acquired by the regression fitting method. The regional SST algorithm was validated using the independent matchup data, the results showed that the bias and standard deviation (SD) were 0.082 ℃ and 0.633 ℃ in daytime, ?0.007 ℃ and 0.557 ℃ in nighttime. Also, taking the optimum interpolation SST as reference value, the regional SST was compared with the operational products from the NSMC, the results demonstrated the bias and SD were decreased from 0.047 ℃ and 0.743 ℃ to 0.031 ℃ and 0.641 ℃ for daytime data, and from 0.184 ℃ and 0.708 ℃ to 0.034 ℃ and 0.556 ℃ for nighttime data, respectively.