摘要
在全球变暖背景下,北极海冰的面积与厚度正逐渐减小,为北极通航提供了可能,而重要海峡的冰情直接影响到北极航道的开通。以东北航道和西北航道上14个重要海峡近35年的海冰密集度为研究对象,利用核K-means方法进行时空聚类,通过经验模态分解模型研究不同聚类模式下的时间序列趋势,探究冰情变化异质性,结果如下:①各海峡海冰密集度呈3种聚类结果,同一聚类结果中海峡的密集度变化具有较强一致性,不同聚类结果之间差异较大,海冰密集度低的海峡全部位于东北航道。②全年尺度中除白令海峡和德米特里拉普捷夫海峡之外,其他海峡海冰密集度呈下降趋势。呈上升趋势的两个海峡均为海冰密集度低的海峡。③夏季融冰期尺度中各海峡海冰密集度变化趋势类型多样,除单纯的上升、下降趋势外,还出现了包括“U”形曲线在内的各种波动型趋势。
In the context of global warming,the area and thickness of Arctic sea ice is gradually decreasing,which provides the possibility for Arctic navigation.As an important transportation hub of sea transportation,the Arctic Strait has a direct impact on the opening of the Arctic Channel.In this study,the sea ice density in the Northeast Passage and the Northwest Passage of the Arctic region in recent 35 years was used as the research object,and the sea ice concentration was clustered by using Kernel K-means clustering.The trend of time se⁃ries of sea ice intensity under different clustering models is analyzed by Empirical Mode Decomposition(EMD),and the heterogeneity of ice regime changes in important straits is explored.Then taking the summer melting ice age as the study period,the cluster and heterogeneity analysis were carried out,and the following conclusions were drawn:①The sea ice concentration of 14 straits in the North Pole showed three spatio-tempo⁃ral clustering models.The variation of sea ice concentration in the same clustering model has strong consisten⁃cy,and the variation of sea ice concentration is quite different among different models.All the straits with low sea ice concentration are in the Northeast Passage.②The sea ice density of the other straits except the Bering Strait and the Dimitri Laptev Strait shows a decreasing trend in the whole year.The two straits with a decreas⁃ing trend are the straits with low sea ice concentration.③The variation trends of sea ice concentration in each strait during the summer melting ice period are various.in addition to the simple increasing and decreasing trends,there are also various fluctuating trends,including the U-shape trend.
作者
张天媛
黄季夏
曹云锋
王利
孙宇晗
杨林生
Zhang Tianyuan;Huang Jixia;Cao Yunfeng;Wang Li;Sun Yuhan;Yang Linsheng(Beijing key Laboratory of Precision Forestry,Beijing Forestry University,Beijing 100083,China;State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University,Beijing 100875,China;Key Laboratory of Land Surface Pattern and Simulation,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China)
出处
《遥感技术与应用》
CSCD
北大核心
2019年第6期1162-1172,共11页
Remote Sensing Technology and Application
基金
中国科学院重点部署项目(ZDRW-ZS-2017-4)
中国科学院先导科技专项(XDA19070502)
