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An argo‐based experiment providing near‐real‐time subsurface oceanic environmental information for fishery data
Fisheries Oceanography ( IF 1.9 ) Pub Date : 2020-09-21 , DOI: 10.1111/fog.12504
Chun‐Ling Zhang 1 , Zhen‐Feng Wang 2 , Yu Liu 1, 3
Affiliation  

A better understanding of the relationships between oceanic environments and fishing conditions could make the utilization of fish more efficient, profitable, and sustainable. The current lack of high‐precision subsurface seawater information has long been a constraint on fishery research. Using near‐real‐time Argo observations, this paper presents a new approach called gradient‐dependent optimal interpolation. This approach provides daily subsurface oceanic environmental information according to fishery dates and locations. An experiment was conducted in the western and central Pacific Ocean using yellowfin tuna (YFT) catch data in August 2017. The results of seawater temperature and salinity represented differences of less than ±0.5°C and ±0.05, respectively, according to verification of error analysis and truth‐finding comparisons. After applying the constructed temperature and salinity profiles, we described the relationship between subsurface information and yellowfin tuna catch distribution. Statistical analysis revealed that yellowfin tuna were more adapted to warmer and saltier seawater. At the near‐surface (<5 m), the most suitable temperature was 28–29°C, although yellowfin tuna can endure a temperature range from 11 to 12°C at a depth of 300 m. The corresponding upper boundary of the thermocline was approximately 75 m, with a mean strength of 0.074°C/m, and the most suitable salinity for yellowfin tuna was 34.5–36.0 at depths shallower than 300 m. These results indicated that the constructed subsurface information was very close to the true values and they had high spatial and temporal accuracy.

中文翻译:

一个基于Argo的实验,为渔业数据提供近实时的地下海洋环境信息

更好地了解海洋环境和捕鱼条件之间的关系可以使鱼类的利用更加有效,有利可图和可持续。当前缺乏高精度的地下海水信息长期以来一直是渔业研究的制约因素。利用近实时Argo观测,本文提出了一种新的方法,称为梯度相关最优插值。该方法根据渔业日期和位置每天提供地下海洋环境信息。利用黄鳍金枪鱼(YFT)捕获数据于2017年8月在太平洋西部和中部进行了一项实验。根据误差验证,海水温度和盐度的结果分别表示分别小于±0.5°C和±0.05。分析和真相比较。应用构造的温度和盐度剖面后,我们描述了地下信息与黄鳍金枪鱼渔获量分布之间的关系。统计分析表明,黄鳍金枪鱼更适合温暖和咸的海水。在近地表(<5 m),最合适的温度是28–29°C,尽管黄鳍金枪鱼可以在300 m的深度处承受11至12°C的温度范围。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。我们描述了地下信息与黄鳍金枪鱼渔获量分布之间的关系。统计分析表明,黄鳍金枪鱼更适合温暖和咸的海水。在近地表(<5 m),最合适的温度是28–29°C,尽管黄鳍金枪鱼可以在300 m的深度处承受11至12°C的温度范围。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。我们描述了地下信息与黄鳍金枪鱼渔获量分布之间的关系。统计分析表明,黄鳍金枪鱼更适合温暖和咸的海水。在近地表(<5 m),最合适的温度是28–29°C,尽管黄鳍金枪鱼可以在300 m的深度处承受11至12°C的温度范围。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。统计分析表明,黄鳍金枪鱼更适合温暖和咸的海水。在近地表(<5 m),最合适的温度是28–29°C,尽管黄鳍金枪鱼可以在300 m的深度处承受11至12°C的温度范围。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。统计分析表明,黄鳍金枪鱼更适合温暖和咸的海水。在近地表(<5 m),最合适的温度是28–29°C,尽管黄鳍金枪鱼可以在300 m的深度处承受11至12°C的温度范围。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。相应的温跃层上限约为75 m,平均强度为0.074°C / m,对于黄鳍金枪鱼,最浅的盐度在深度小于300 m时为34.5–36.0。这些结果表明构造的地下信息非常接近真实值,并且具有很高的时空精度。
更新日期:2020-09-21
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