基于非线性算法的FY-3A/VIRR SST反演  

FY-3A/VIRR SST Retrieval Using Nonlinear Algorithm

作　　者：何全军[1,2,3] 曹静[2] 陈翔[2] 张月维 

机构地区：[1]中国科学院南海海洋研究所热带海洋环境国家重点实验室,广州510301 [2]广州气象卫星地面站,广州510640 [3]中国科学院研究生院,北京100049

出　　处：《气象》2013年第1期74-79,共6页Meteorological Monthly

基　　金：中国气象局气象关键技术集成与应用项目(CMAGJ2011M38);广东省气象局气象科技项目(201018)共同资助

摘　　要：利用非线性算法实现了FY-3A/VIRR数据的海洋表面温度SST产品的反演。对2010年的全球船舶站观测数据和FY-3A/VIRR数据建立匹配数据集,选择单月的匹配数据采用多元回归模型计算得到了适用于FY-3A/VIRR数据的非线性海表温度反演算法NLSST的系数,能够实现FY-3A/VIRR数据的高精度SST产品反演。并利用独立于反演算法的双月匹配数据采用最小绝对偏差方法通过线性模型对SST算法的精度进行检验,结果显示白天和夜间的偏差分别为0.05℃和-0.05℃,绝对偏差在0.50℃以下,标准偏差在0.65℃以下。通过文中实现的算法反演了VIRR数据的SST产品,并和MODIS的官方产品进行比较,结果显示两种SST产品具有很高的一致性。The sea surface temperature （SST） was retrieved by nonlinear algorithm for Visible and Infra- Red Radiometer （VIRR） onboard the Chinese Fengyun 3A （FY-3A） polar-orbiting meteorological satel- lite. In this paper, the matchup dataset was created by the SST measurements from global ship observation and FY-3A/VIRR data in 2010, and the coefficients for the nonlinear SST （NLSST） equation applicable to FY-3A/VIRR data were derived by using multiple linear regression, which could be used to retrieve accu- rate SST products for FY-3A/VIRR data. An independent matchup dataset was used to assess the accura- cy of NLSST algorithm by linear model using a robust least absolute deviation method, and the result showed that the biases were 0.05℃ and --0.05℃ for daytime and nighttime, respectively. The absolute deviation was less than 0.5℃ and the standard deviation was less than 0.65℃. The VIRR SST was calcu- lated by the SST algorithm presented in this paper to contrast with official MODIS SST products, showing that there was a good correlation between VIRR SST and MODIS SST. All these have indicated that the SST algorithm realized in this paper could provide reliable VIRR SST products to ocean and climate varia- bility studies.

关 键 词：遥感 海洋表面温度 非线性算法 FY-3A VIRR 

分 类 号：P412[天文地球—大气科学及气象学]