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遥感数据在渔业分析中应用广泛,但它只能提供海洋表层参考信息,远洋捕捞常常需要次表层环境信息辅助渔场预测。Argo剖面数据提供了从表层到2 000 m以浅的数据,利用Argo数据建立的次表层海况数据库可以为渔业分析提供更多的参考信息。从GDacs服务器自动定时下载数据并更新数据库,利用Akima插值方法处理垂直剖面数据,通过分析温度和盐度的变化情况计算出温跃层和盐跃层,以及其深度、厚度、强度等信息,利用反距离权重插值法绘制海洋次表层环境信息图,结合渔业信息数据可以很好地应用于渔业分析。研究亮点:多数金枪鱼类生活在海洋表层至100 m,温跃层限制了鱼类的上下移动。文章研究了Argo数据自动化处理,使用AKIMA、IDW插值生成温跃层上(下)界温度、盐度、深度、强度;根据温跃层深度选择用于辅助分析的水层;分析渔获量分布、变化等与海洋次表层环境特点的关系。
Remote sensing data is widely used in fishery analysis, but it can only provide reference information for the ocean surface. For deep-sea fishing, subsurface environmental information is often needed to assist in the prediction of fisheries. Argo profile data provide shallow data from surface to 2000 m, and the subsurface sea state database established using Argo data can provide more information for fishery analysis. The GDacs server automatically and periodically downloads data and updates the database. The Akima interpolation method is used to process the vertical profile data. By analyzing the changes of temperature and salinity, the thermocline and salinity layers are calculated, and their depth, thickness and intensity are calculated. The inverse distance weighted interpolation method can draw the subsurface environmental information map of the ocean and can be applied to fishery analysis well with the fishery information data. Research highlights: Most tuna live on the ocean surface to 100 m, and the thermocline limits the movement of fish up and down. In this paper, the Argo data processing is studied. AKIMA and IDW interpolation are used to generate the upper and lower temperature, salinity, depth and intensity of the thermocline. The water layer for secondary analysis is selected according to the depth of the thermocline. , Changes and other marine subsurface environmental characteristics of the relationship.