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中国南部海域遥感海表层温度应用研究
时间:2011-04-06 浏览次数:1873次 无忧论文网
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海洋物理
海洋环境动力学海洋环境动力学
    本研究发展了一种适用于中国南部海域的云探测算法用于高分辨率AVHRR 海表层温度(Sea Surface Temperature, SST)的反演。高、低分辨率AVHRR SST产品在中国南部海域的检验结果表明,尽管低分辨率的AVHRR PFSST在反映强烈的温度梯度时存在不足,趋向于削弱实际的温度锋,但整体上AVHRR遥感SST数据适用于分析台湾海峡及其邻近海域的时间变动趋势及空间变化特征。
    通过对AVHRR PFSST、TMI SST遥感数据与NOAA OI.v2 SST再分析数据三组数据源计算所得南海暖池面积及强度指数逐月、季节与年际变动特征的比较分析,发现三组记录在所有时间尺度上基本吻合,体现了基本一致的南海暖池季节与年际变动规律,特别是与ENSO指数MEI的关系,它们都只对高MEI指数响应,提示南海暖池很可能有其自身的主要受东亚季风异常影响的波动规律,只当ENSO事件较强时,局地驱动的信号才可能被淹没。总的看来,云覆盖、雨及陆地辐射对AVHRR与TMI遥感数据的影响并未造成它们与OI.v2在估算南海暖池面积和强度时间变动上的显著差异。但在某些时段出现的不同数据记录之间的不一致目前尚难以解释,不同传感器遥感数据的融合可能是发展一个令人信服的南海暖池指数时序列的一种有效方法。
    基于AVHRR SST的分析表明,南海SST年际变动还存在着空间上的差异,最显著的差异体现在1997年~1999年的暖事件中。结合ERS风应力遥感数据,分析表明南海北部海区在1999年冬季可能受黑潮入侵的影响而持续高温,而在南海南部及中部海区,ENSO影响较之南海北部更为显著些,南部海区与热带太平洋的暖事件同时结束。SeaWiFS遥感叶绿素数据却表明,北部海区在1999年冬季仍持续的强暖事件并未使叶绿素维持在1998年的低浓度水平,而是有显著上升。南海的时空复杂性由此可见一斑。
     [英文摘要]:     An algorithm for cloud detection was developed for the southern region of China Sea and used to retrieve AVHRR MCSST (Multi-Channel SST) of high resolution (1km x 1km). By comparing low resolution (9km x 9km) AVHRR PFSST (Pathfinder SST) products and high resolution AVHRR MCSST products with corresponding in situ measured SST in the Taiwan Strait and the northern South China Sea, it was demonstrated that the PFSST of low resolution seems to reduce the real SST fronts in the areas of strong temperature gradients. Nevertheless, in general the AVHRR SST was capable to produce a temporal and spatial pattern of SST consistent with in situ observations in the region under study. 
    An intensive comparative analysis was then conducted in order to evaluate the consistency between remote sensing AVHRR SST and TMI SST and the reanalysis OI.v2 SST when they are used to derive temporal variability of the size and intensity of the South China Sea Warm Pool. Records of monthly, seasonal and interannual pattern of South China Sea Warm Pool (SCSWP) areal index and intensity index were produced from these three SST datasets, respectively. They were found generally changing in accordance with each other at various temporal scales, especially that all of them show bad correspondence with MEI (Multivariate ENSO Index) except during strong ENSO warm phases in 1987~1988 and 1997~1998. It was suggested that the SCSWP might have its own interannual pattern potentially and mainly driven by the East Asian Monsoon, with ENSO effects shown only when the ENSO signals were strong. In general, influences due to cloud cover, raining and land contamination upon AVHRR and TMI remote sensing data seem not producing significant differences in the SCSWP temporal pattern from that derived from OI.v2. Yet differences between the results of AVHRR and OI.v2 did exist especially in autumn from 1990 to 1996, of which no reasonable explanation could be invoked. It was suggested that merging of AVHRR and TMI was probably a better resolution for deriving a more convincing time series of SCSWP indices compared to the current records derived from individual datasets.
    A spatial pattern of SST interannual variability in the SCS was further revealed by AVHRR. The most striking signal was found during the period of 1997~1999 when the strongest SCS warm event on record occurred. Accompanying by the stop of the 1997~1998 warm event in the tropical Pacific, the warm event ceased in summer 1998 in the southern SCS, while it persisted till spring 1999 in the northern SCS. Changes in wind stress and wind stress curl as observed by ERS from winter 1997 to winter 2000 suggested that the continuous warming in the northern SCS in 1999 was very likely associated with strengthening Kuroshio intrusion during this time. On the other hand, it was shown that surface chlorophyll as observed by SeaWiFS increased in the warmest winter of 1999 on record in the northern SCS, partly lending support to the notion that the mechanism driving warming in 1998 was different from that in 1999.    
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