南海珊瑚礁区34年卫星遥感海表温度变化的时空特征分析

选取NOAA OISST数据集的1982-2015年南海月平均海洋表面温度（SST），先对东沙、西沙和南沙礁区海域的多年SST进行时间尺度上的统计，然后对该数据集进行距平场的经验正交函数（EOF）分解，研究南海海表温度的时间和空间年际变化特征。研究显示:（1）不同的礁区海域SST升温趋势不同，东沙礁区海域SST升温趋势最明显（0.216℃/（10 a）），西沙和南沙礁区SST的升温趋势分别为0.180℃/（10 a）和0.096℃/（10 a）；（2）西沙和南沙礁区全年处于珊瑚生长的最适海温范围内，东沙一年中有4个月海温较低，SST最高的月份分别集中在7月（东沙礁区）、6月（西沙礁区）和5月（南沙礁区）；（3） EOF第一模态的空间分布显示南海SST变化是同相位的，由西北—东南振幅量值递减，在礁区振幅从大到小依次为东沙、西沙、南沙；（4） EOF第一模态时间系数显示南海SST变化与El Niño事件相关。南海海表温度异常场与Niño3.4指数的相关性分析显示两者关联度最高为0.723，平均关联度也高达0.655；南海SST的变化滞后Niño3.4区7~8个月。综上，在全球变暖背景下，南海SST的变化不仅受到El Niño事件的影响，其不断上升也在悄然威胁珊瑚的正常生长。

Analysis of temporal and spatial characteristics of sea surface temperature variabilities over the past 34 years in coral reef areas of the South China Sea

A monthly sea surface temperature(SST)data from 1982 to 2015 of the South China Sea(SCS)was extracted based on the NOAA OISST data set in this study. First count up the SST at the Dongsha, Xisha and Nansha reef islands on time scale. Then the empirical orthogonal function(EOF)method was applied to the monthly anomaly field of the data set to analyze the characteristics of the yearly spatial and temporal variabilities of the SCS SST distribution. The study showed as follows:(1) The SST warming trends were differed at different reef areas. The rising trend of SST in the Dongsha reef area was the most significant(about 0.216℃/(10 a)). The following trends were 0.18℃/(10 a) at Xisha reef area and 0.096℃/(10 a) at Nansha reef area, respectively; (2) The SST in the Xisha and Nansha reef areas were in the optimum growth temperature of hermatypic corals in the whole year. There were about 4 months lower SST for hermatypic corals in the Dongsha reef area. The hottest month were focus on July(Dongsha), June(Xisha)and May(Nansha), respectively; (3) The first mode of EOF showed that SST over the SCS was spatially in phase and declined from northwest to southeast. That was Dongsha > Xisha > Nansha; (4) The first mode temporal distribution of EOF showed that the variation of SST in the SCS was related to the El Niño. The correlation analysis between SSTA over the SCS and the index of Niño3.4 showed that the average incidence was 0.655, and the highest correlation degree was 0.723. The SSTA over the SCS was lag of Niño3.4 about 7-8 months. In summary, under the background of global warming, the change of SST in the SCS is not only affected by the El Niño, but the continued rising is quietly threaten the growth of corals.