Application of Gradient-Dependent Optimal Interpolation in Fishery Analysis of Neon Flying Squid (

A key issue in fishery forecasting is the collection of high-precision subsurface environmental data. A data assimilation method, named gradient-dependent optimal interpolation, was used to construct the near-real-time vertical temperature and salinity structure of a squid fishery ground based on Argo observations. The results were verified by truth-finding comparisons and applied to analyze the relationship between neon flying squid and the subsurface environment in the Kuroshio-Oyashio Confluence Region. The temperature and salinity differences between the constructed results and survey data were less than ±0.5 °C and ±0.02, respectively. Most of the relative analysis errors were less than the observational errors. Statistical analysis revealed that the most suitable temperature for squid was 18-24 °C at the near-surface (<5 m), although the squid can endure a temperature range from 11 to 12 °C at a depth of 300 m. There was an obvious thermocline in the fishery ground, with a thermocline depth of 65 m and a mean strength of approximately 0.10 °C/m. The regressive relationship between vertical temperature (thermocline parameters) and squid catch per unit effort (CPUE) followed the exponential (Gaussian) function. The most suitable salinity was 33.0-34.2 at depths shallower than 300 m.