南海三维温盐结构对海水透明度的影响分析
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摘要
无人水下航行器(UUV)试验作业、航行深度和航路选择等活动受海流、透明度、跃层、海水温度和盐度等海洋复杂水文环境的影响。研究结合卫星遥感和数值模式数据,从信息流的角度分析了南海海域三维温盐结构对海水透明度(SDD)的影响及区域分布特征,规避了在传统相关性分析中无法准确描述变量间因果影响关系的不足。结果表明,因受高温低盐海域叶绿素浓度较高的影响,表层盐度较低的中沙群岛及近岸海域,其SDD主要受浅层海水盐度的影响;表层高温低盐的南沙群岛附近海域SDD主要受20～30m深处的海水温度影响;表层高温高盐的西沙群岛附近海域SDD主要受60～70m深处的海水温度和盐度影响;由于受温度锋面和悬浮泥沙的影响,吕宋海峡附近海域SDD主要受30～50 m深处海水温度的影响。水下三维海水温度和盐度的变化影响甚至会加剧SDD的变化,因此建议UUV在航行和试验作业时应尽量选择最大SDD深度以下,同时避开水下三维海水温度和盐度对SDD影响较大的深度,以保证UUV航行的安全、可靠和隐蔽性。
The experiment, navigation depth and sea route of an Unmanned Undersea Vehicle(UUV) are affected by ocean current, transparency, spring layer, seawater temperature and salinity, as well as other complex hydrological environments. Based on the information flow concept, this paper investigates the cause-effect relation between the three-dimensional temperature and salinity structure and the Secci Disk Depth(SDD) by using the data of satellite remote sensing and numerical model in South China Sea, which avoids the disadvantage of the traditional correlation analysis that the causal relationship among variables cannot be accurately described. The results show that: 1) The SDD in the area around the Zhongsha Islands and offshore with lower salinity is mainly affected by the salinity of the shallow sea water because the chlorophyll concentrations are high in the seawater with higher temperature and lower salinity; 2) Seawater of the area around the Nansha Islands with high temperature and low salinity, so the SDD mainly affected by the temperature of the seawater at a depth of 20-30 meters; 3) The SDD in the area around the Xisha Islands with higher temperature and salinity is mainly affected by the temperature and salinity of the seawater at a depth of 60-70 meters; and 4) Due to the influences of temperature front and suspended sediment, the SDD around Luzon strait is mainly affected by the temperature of the seawater at a depth of 30-50 meters. Therefore, it is suggested that UUV should navigate and conduct experiment beneath the depth with maximum SDD and keep away from the depth range, where the underwater three-dimensional temperature and salinity structure has significant impact on the SDD, in order to ensure its safety, reliability and invisibility.
The experiment, navigation depth and sea route of an Unmanned Undersea Vehicle(UUV) are affected by ocean current, transparency, spring layer, seawater temperature and salinity, as well as other complex hydrological environments. Based on the information flow concept, this paper investigates the cause-effect relation between the three-dimensional temperature and salinity structure and the Secci Disk Depth(SDD) by using the data of satellite remote sensing and numerical model in South China Sea, which avoids the disadvantage of the traditional correlation analysis that the causal relationship among variables cannot be accurately described. The results show that: 1) The SDD in the area around the Zhongsha Islands and offshore with lower salinity is mainly affected by the salinity of the shallow sea water because the chlorophyll concentrations are high in the seawater with higher temperature and lower salinity; 2) Seawater of the area around the Nansha Islands with high temperature and low salinity, so the SDD mainly affected by the temperature of the seawater at a depth of 20-30 meters; 3) The SDD in the area around the Xisha Islands with higher temperature and salinity is mainly affected by the temperature and salinity of the seawater at a depth of 60-70 meters; and 4) Due to the influences of temperature front and suspended sediment, the SDD around Luzon strait is mainly affected by the temperature of the seawater at a depth of 30-50 meters. Therefore, it is suggested that UUV should navigate and conduct experiment beneath the depth with maximum SDD and keep away from the depth range, where the underwater three-dimensional temperature and salinity structure has significant impact on the SDD, in order to ensure its safety, reliability and invisibility.
引文
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[18]Deng Li-jing,Wei Hao,Wang Jia-ning.Vertical Distribution of Kuroshio Velocity at PN Section and Its Formation Mechanism[J].Marine Science Bulletin,2015,33(1):26-39.
[19]陈心一,郝增周,潘德炉,等.中国近海海面风场的时空特征分析[J].海洋学研究,2014,32(1):1-10.Chen Xin-yi,Hao Zeng-zhou,Pan De-1u,et al.Analysis of Temporal and Spatial Feature of Sea Surface Wind Field in China Offshore[J].Journal of Marine Sciences,2014,32(1):1-10.
[20]Liang X S.Unraveling the Cause-Effect Relation Between Time Series[J].Physical Review E Statistical Nonlinear&Soft Matter Physics,2014,90(5-1):052150.
[21]任焕莲.辛安泉系统岩溶地下水降水补给滞后分析研究[J].地下水,2007,29(5):59-63.Ren Huan-lian.Time Lag of Rainfall Recharge to the Karst Groundwater in Xin’an Springs[J].Ground water,2007,29(5):59-63.
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[2]王奎民.主要海洋环境因素对水下航行器航行影响分析[J].智能系统学报,2015,10(2):316-323.Wang Kui-min.Influence of Main Ocean Environments on the Navigation of Underwater Vehicles[J].CAAI Transactions on Intelligent Systems,2015,10(2):316-323.
[3]李凡,郭新毅,张毅,等.水下声传播的发展及其应用[J].物理,2014,43(10):658-666.Li Fan,Guo Xin-yi,Zhang Yi,et al.Development and Applications of Underwater Acoustic Propagation[J].Physics,2014,43(10):658-666.
[4]Richards S D,Heathershaw A D,Thorne P D.The Effect of Suspended Particulate Matter on Sound Attenuation in Seawater[J].Journal of the Acoustical Society of America,1996,100(3):1447-1450.
[5]文洪涛,杨燕明,刘贞文,等.混浊水的声衰减研究进展及应用前景[J].海洋通报,2008,27(6):88-94.Wen Hong-tao,Yang Yan-ming,Liu Zhen-wen,et al.Recent Advance and Application Prospects of Sound Attenuation in Turbid Water[J].Marine Science Bulletin,2008,27(6):88-94.
[6]彭临慧,王桂波.中国近海悬浮颗粒物海水声波衰减[J].声学学报,2008,33(5):389-395.Peng Lin-hui,Wang Gui-bo.Sound Attenuation in Suspended Particulate Matter Seawater of Chinese Sea Offshor[J].ACTA Acustica,2008,33(5):389-395.
[7]姜璐,朱海,李松.机载激光雷达最大探测深度同海水透明度的关系[J].激光与红外,2005,35(6):397-399.Jiang Lu,Zhu Hai,Li Song,The Relationship Between Max Survey Depth of Airborne Ocean Lidar and Secchi Depth[J].Laser&Infrared,2005,35(6):397-399.
[8]钟晓春,李源慧.激光在海水中的衰减特性[J].电子科技大学学报,2010,39(4):574-577.Zhong Xiao-chun,Li Yuan-hui,Attenuation Characteristics of Laser in the Seawater[J].Journal of University of Electronic Science and Technology of China,2010,39(4):574-577.
[9]Yanagi T,Inoue K I.A Numerical Experiment on the Sedimentation Processes in the Yellow Sea and the East China Sea[J].Journal of Oceanography,1995,51(5):537-552.
[10]张晨,戚建华,左军成,等.黄、渤海温跃层三维数值模拟[J].海洋学报,1997,19(6):12-20.
[11]杜岩.南海混合层和温跃层的季节动力过程[D].青岛:中国海洋大学,2002.
[12]费尊乐.渤海海水透明度与水色的研究[J].黄渤海海洋,1986,4(1):36-43.Fei Zun-le.Study on the Water Colour and Transparency in the Bohai Sea[J].Journal of Oceanography of HuangHai&BoHai Seas,1986,4(1):36-43.
[13]黎洁溪.南海北部海水透明度分布变化概况[J].海洋通报,1985(4):3-6.Li Jie-xie.Outline of the Distribution and Variation of Water Transparency in the Northern South China Sea[J].Marine Science Bulletin,1985(4):3-6.
[14]张春桂,曾银东.台湾海峡海水透明度遥感监测及时空变化分析[J].气象与环境学报,2015,31(2):73-81.Zhang Chun-gui,Zeng Yin-dong.Remote Sensing Monitoring and Spatial-temporal Change of Seawater Transparency in Taiwan Strait[J].Journal of Meteorology and Environment,2015,31(2):73-81.
[15]高磊,姚海燕,张蒙蒙,等.青岛近岸海域海水透明度时空变化及与环境因子之间的关系[J].海洋学研究,2017,35(3):79-84.Gao Lei,Yao Hai-yan,Zhang Meng-meng,et al,Temporal and Spatial Variation of Seawater Transparency and Its Relationship with Environmental Factors in Qingdao Coastal Area[J].Journal of Marine Sciences,2017,35(3):79-84.
[16]郑晓琴,丁平兴,胡克林.长江口及邻近海域夏季温盐分布特征数值分析[J].华东师范大学学报(自然科学版),2008(6):14-23.Zhang Xiao-qin,Ding Ping-xing,Hu Ke-lin.Numerical Analysis of Characteristics of Temperature-salinity Distributions at the Changjiang Estuary and Its Adjacent Areas in Summer[J].Journal of East China Normal University(Natural Science),2008(6):14-23.
[17]何贤强,潘德炉,黄二辉,等.中国近海透明度卫星遥感监测[C]//海洋监测高技术2003年度战略研讨会.北京:中国21进程管理中心,2003.
[18]Deng Li-jing,Wei Hao,Wang Jia-ning.Vertical Distribution of Kuroshio Velocity at PN Section and Its Formation Mechanism[J].Marine Science Bulletin,2015,33(1):26-39.
[19]陈心一,郝增周,潘德炉,等.中国近海海面风场的时空特征分析[J].海洋学研究,2014,32(1):1-10.Chen Xin-yi,Hao Zeng-zhou,Pan De-1u,et al.Analysis of Temporal and Spatial Feature of Sea Surface Wind Field in China Offshore[J].Journal of Marine Sciences,2014,32(1):1-10.
[20]Liang X S.Unraveling the Cause-Effect Relation Between Time Series[J].Physical Review E Statistical Nonlinear&Soft Matter Physics,2014,90(5-1):052150.
[21]任焕莲.辛安泉系统岩溶地下水降水补给滞后分析研究[J].地下水,2007,29(5):59-63.Ren Huan-lian.Time Lag of Rainfall Recharge to the Karst Groundwater in Xin’an Springs[J].Ground water,2007,29(5):59-63.
[22]Schreiber T.Measuring Information Transfer[J].Physical Review Letters,2000,85(2):461-464.
[23]Stips A,Macias D,Coughlan C,et al.On the Causal Structure between CO2 and Global Temperature[J].Scientific Reports,2016,6:21691.