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基于Argo浮标数据的水文特征三维可视化分析——以南大洋印度洋扇区为例 被引量:1

3D Visual Analysis of Hydrographic Features Based on Argo Float Data:A Case Study of the Indian Section of the Southern Ocean
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摘要 利用南大洋2009—2020年的Argo浮标温盐剖面数据,通过绘制温度和盐度空间分布图的定性分析以及三维聚类可视化分析等方法,揭示了南大洋印度洋扇区的多水团空间分布特征。结果表明,在60°S~67°S,60°E~80°E之间的海域,海水温度在-1.9~2.5℃之间,盐度在32~34.75 psu之间。整个研究区域海水温度随深度分布均呈现明显的跃层结构,在高纬度区域冷水团厚度较大,随着纬度降低,冷水团的厚度逐渐减小。在100 m层,63°S~65°S的纬度带存在明显的温度锋面,区域内海水温度比南北两侧温度高。在100 m、200 m和500 m层,63°S~65°S的纬度带存在盐度锋面,在该锋面海水盐度达到极大值。根据位于南大洋印度洋扇区普里兹湾区域附近的水团的划分方法,在研究区域内0~2000 m的深度存在南极夏季表层水、冬季水、绕极深层水等水团。根据聚类结果,在63°S以北的表层水区域以下还存在一个盐度和温度较高的水团。 The spatial distribution characteristics of multiple water masses in the Indian Section of the Southern Ocean are revealed by qualitative analysis of temperature and salinity maps and 3 D cluster visualization analysis based on the Argo float profile data including temperature and salinity data from2009 to 2020 The results show that the temperature and salinity of sea water are in the range of-19—25℃and 32—347 psu,respectively,in the sea area between 60°S—67°S and 60°E—80°E The distribution of sea water temperature with depth in the whole study area presents obvious thermocline structure The thickness of cold water mass is larger at high latitude region,and decreases with the decrease of latitude At the depth of 100 m,there is a temperature front in the region of 63°S—65°S,where the sea water temperature is higher than that in its north and south sides At the depth of100 m,200 m and 500 m,there is a salinity front in the region of 63°S—65°S,where the salinity reaches the maximum According to the classification method of water masses in Prydz Bay in the Indian Section of the Southern Ocean,Antarctic summer surface water,winter water and Antarctic circumpolar deep water are found in the depth between 0 m and 2000 m Moreover,clustering result shows that there is a water mass with high salinity and temperature below surface water region in the north of 63°S.
作者 艾松涛 丁曦 AI Songtao;DING Xi(Chinese Antarctic Center of Surveying and Mapping,Wuhan University,Wuhan 430079,China)
出处 《测绘地理信息》 CSCD 2022年第1期24-29,共6页 Journal of Geomatics
基金 国家自然科学基金(41941010)。
关键词 聚类分析 三维可视化 南印度洋 普里兹湾 水团 cluster analysis 3D visualization South Indian Ocean Prydz Bay water mass
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