南海及周边海域融合海表温度产品的验证与互较  

Validation and inter- comparison of multi-satellite merged sea surface temperature products in the South China Sea and its adjacent waters

作　　者：胡晓悦[1,2,3,4] 张彩云[1,2] 商少凌[1] 

机构地区：[1]厦门大学海洋与地球学院,福建厦门361005 [2]福建省海陆界面生态环境重点实验室(厦门大学),福建厦门361005 [3]中国科学院海洋研究所海洋环流与波动重点实验室,山东青岛266071 [4]中国科学院大学,北京100049

出　　处：《遥感学报》2015年第2期328-338,共11页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:U1305231;40706041);福建省自然科学基金(编号:2011J01278);海洋赤潮灾害立体监测技术与应用国家海洋局重点实验室开放基金资助项目(编号:MATHAB20100313)

摘　　要：利用2008年—2009年Argo、Argos现场观测海表面温度SST,对OSTIA、MISST、MWSST以及NGSST4种融合SST产品在南海及其周边海域的适用性进行评估。验证结果表明,4种融合SST产品在外海的均方根误差RMS介于0.3—1.0℃,bias介于-0.1—0.6℃;除了NGSST在近岸出现明显暖偏外,其他3种融合SST与现场SST基本一致,OSTIA与现场SST的偏差为最小。对4种融合SST产品彼此间的互较也表明,它们在水深大于80 m的海区没有显著性差异,但彼此间的偏差会随水深变浅而增大。此外,各产品间偏差在冬季最大,夏季最小。本文为具有高时空覆盖度的融合SST产品在南海及其周边海域的应用提供了一个可靠的依据。Sea Surface Temperature （SST） is a basic parameter in characterizing the ocean-atmosphere system and serves an important function in climate change. Many types of cloud-free, high-spatial, and temporal coverage merged SST products have been generated by the Group for High Resolution Sea Surface Temperature. These products provide important data sources that can be used in a wide variety of operational and scientific applications. However, differences are existed among these products, due to their specific research requirements, different blending algorithms, different satellite SST sources for blending, and quality control methods. Therefore, monitoring the quality of these products is necessary, particularly at shelf and coastal seas around China, which are characterized by complex atmospheric conditions and hydrodynamics. This study compares four types of merged SST products in the South China Sea and adjacent waters in the years 2008 and 2009. Four multi-satellite merged SST products--the Operational SST and Sea lee Analysis （OSTIA） , microwave/infrared optimally interpolated SST, microwave optimally interpolated SST, and new generation SST （NGSST）--are validated with the Argo SST in the shelf sea and Argos SST in the shallow coast. The match-up data are collected on the same day and location. The Root Mean Square （RMS） , bias, and correlation coefficients are calculated and used to quantify the errors. These products are projected into the same grid of NGSST using the nearest-neighbor sampling method for comparison. OSTIA is selected as the basis, and the rela- tive differences between OSTIA and the other three products are computed and visualized using maps, box-plot, and time series plots. The statistical results show that the RMS between the merged SSTs and Argo temperature ranged between 0.3 ~C and 1.0 ~C, whereas the bias ranged between - 0.1 ~C and O. 6 ~C in the shelf sea （water depth 〉 80 m）. The other three merged SSTs were consistent with the in situ data in the coastal area,

关 键 词：融合SST 验证 互较 遥感 南海 

分 类 号：P715.7[天文地球—海洋科学] P714