Analysis on long-term change of sea surface temperature in the China Seas

Analysis on long-term change of sea surface temperature in the China Seas
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中国海海表温度长期变化分析

DOI:
10.1007/s11802-013-2172-2
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发表时间:
2013-03
影响因子:
1.6
通讯作者:
Zhang Qi
Zhang Qi
中科院分区:
地球科学2区
文献类型:
--
作者:
Liu Qinyu;Zhang Qi

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基于两个不同的观测数据集(HadISST1和HadSST3)研究了1900年至2006年中国海海表温度(SST)的长期变化。与大西洋类似,中国海的海温在过去 107 年中得到了很好的观测。重建数据集(HadISST1)和未插值数据集(HadSST3)之间的比较表明,两个数据集的海温变暖趋势在中国大部分海域是一致的。冬季增温趋势强于夏季,根据HadISST1,东海和台湾海峡冬季海温增幅最大超过2.7°(100年)−1。然而,1999年之后,两个数据集中的中国海海温都经历了突然下降。在东海和台湾岛东部,HadISST1的估计趋势强于HadSST3的估计趋势,分别使用HadISST1和HadSST3数据集时,线性海温变暖趋势的差异约为1°(100年)−1。与陆地表面气温线性冬季增温趋势(1.6°(100年)−1)相比,HadSST3在长江口表现出小于2.1°(100年)−1的趋势,比HadISST1大于2.7°(100年)−1的趋势更为合理。结果还表明海温变暖模式的估计存在很大的不确定性。
Long-term change of sea surface temperature (SST) in the China Seas from 1900 to 2006 is examined based on two different observation datasets (HadISST1 and HadSST3). Similar to the Atlantic, SST in the China Seas has been well observed during the past 107 years. A comparison between the reconstructed (HadISST1) and un-interpolated (HadSST3) datasets shows that the SST warming trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7° (100 year)−1in the East China Sea and the Taiwan Strait during winter based on HadISST1. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadISST1 is stronger than that from HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1° (100 year)−1when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warming trend of the land surface air temperature (1.6° (100 year)−1), HadSST3 shows a more reasonable trend of less than 2.1° (100 year)−1than HadISST1’s trend of larger than 2.7° (100 year)−1at the mouth of the Yangtze River. The results also indicate large uncertainties in the estimate of SST warming patterns.
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