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APPLICATION OF NONLINEAR MULTI-CHANNEL ALGORITHMS FOR ESTIMATING SEA SURFACE TEMPERATURE WITH NOAA 14 AVHRR DATA 被引量:1
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作者 李晓峰 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2000年第3期199-207,共9页
NOAA global operational NOAA/AVHRR Nonlinear Sea Surface Temperature (NLSST) retrieval algorithms were used to generate Global Area Coverage (GAC) sea surface temperature (SST) measurements in the global ocean in 1998... NOAA global operational NOAA/AVHRR Nonlinear Sea Surface Temperature (NLSST) retrieval algorithms were used to generate Global Area Coverage (GAC) sea surface temperature (SST) measurements in the global ocean in 1998. The accuracy of SST retrieved from daytime split window NLSST algorithm and nighttime triple window NLSST algorithm for NOAA 14 AVHRR data was investigated in this study. A matchup dataset of drifting buoys and NOAA 14 satellite measurements in the global ocean was generated to validate these operational split window and triple window algorithms. For NOAA 14 in 1998, we had 14095 and 22643 satellite and buoy matchups that matched within 25 km and 4 hours for daytime and nighttime, respectively. The satellite derived SST had a bias of less than 0.1℃ and standard deviation of about 0.5℃. This study also showed that the NLSST algorithm provided the same order of SST accuracy in different time of the year and under a wide range of satellite zenith angle and water vapor represented by the channel 4 and 5 brightness temperature difference. Therefore, NLSST algorithms are usually independent of season, geographic location, or atmospheric moisture content. Comparison between the low resolution AVHRR GAC data accuracy and high resolution Local Area Coverage (LAC) data accuracy is also discussed. 展开更多
关键词 sea surface temperature (sst) NOAA/AVHRR nonlinear sst algorithm
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基于非线性算法的FY-3A/VIRR SST反演 被引量:6
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作者 何全军 曹静 +1 位作者 陈翔 张月维 《气象》 CSCD 北大核心 2013年第1期74-79,共6页
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... 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。 展开更多
关键词 遥感 海洋表面温度 非线性算法 FY-3A VIRR
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