摘要
利用ERA_interim再分析资料以及OISST高分辨率海面温度(Sea surface temperature,SST)卫星观测数据,通过小波分析、二维模态相关(Pattern correlation)等方法系统地分析了黑潮延伸体区域涡旋尺度SST信号的季节内变化特征。发现涡旋尺度SST季节内变化信号在冬季最强、夏季最弱。该信号主要分布在黑潮-亲潮海洋锋面区域,在日本沿岸振幅最强、并沿黑潮、亲潮锋面向东延伸,其标准差高达1℃,是该海域冬季SST的重要变化信号。涡旋尺度SST的季节内变化周期以40~100 d周期为主,会引起大气边界层的响应,激发海气界面湍流热通量、海面气温、边界层高度等同位相的季节内变化。在该区域涡旋信号较强个数较多的时间段SST异常的季节内变化信号更明显,边界层大气与涡旋尺度SST季节内变化信号的相关程度更大。
Based on ERA_interim reanalysis data and OISST high resolution sea surface temperature(SST)satellite observation data,intraseasonal variation of mesoscale sea surface temperature(SST)in the Kuroshio Extension(KE)region were investigated using wavelet analysis and two-dimensional pattern correlation analysis.The intraseasonal variation of mesoscale SST and its temporal and spatial characteristics were investigated.The signal is stronger in winter and mainly distributes along the Kuroshio and Oyashio fronts in the extension region,stretching from the Japan coast towards Pacific.Its standard deviation is as high as 1℃in winter,contributing as the main variation signal in SST fields in the KE during winter.The significant period of intraseasonal variability in mesoscale SST is 40~100 d,inducing intraseasonal variation in boundary layer atmosphere.The mesoscale anomalies of turbulent heat flux,sea surface temperature and boundary layer height vary with mesoscale SST in the same phase both spatially and temporally.Moreover,it is confirmed that during the period when there are more stronger eddies,the intraseasonal variation signal in mesoscale SST and boundary layer atmosphere are all more significant than those during weak eddy scenarios.
作者
杨小绘
贾英来
YANG Xiao-Hui;JIA Ying-Lai(Department of Marine Meteorology, College of Oceanic and Atmospheric Science, Ocean University of China, Qingdao 266100, China)
出处
《中国海洋大学学报(自然科学版)》
CAS
CSCD
北大核心
2020年第7期26-36,共11页
Periodical of Ocean University of China
基金
国家重点基础研究发展计划项目(2017YFC1404101)
国家自然科学基金项目(41975065)资助。
关键词
黑潮延伸体
涡旋尺度海面温度
季节内变化特征
边界层大气
Kuroshio extension
mesoscale sea surface temperature
intraseasonal variability
boundary layer atmosphere