Operational ocean prediction experiments for smart coastal fishing

Satoshi Nakada, Naoki Hirose, Tomoharu Senjyu, Ken ichi Fukudome, Toshihiro Tsuji, Noriyuki Okei

    Research output: Contribution to journalArticlepeer-review

    16 Citations (Scopus)

    Abstract

    This paper describes a new combination of in situ, high-density observations gathered by fishermen, and a real-time, high-resolution (approx. 1.5. km) prediction model developed toward more efficient fishing. Flow field data can be successfully collected by observations from acoustic Doppler current profilers installed on commercial fishing boats, which uncover sub-mesoscale structures such as small (approx. 10. km) eddies in the eastern boundary current region of the Japan/East Sea. Frequent vertical temperature profiles observed by sensors attached to casting trawl nets indicate fine feature of summertime upwelling area associated with fishing grounds. These observational assets back up routine observations conducted by using stationary buoys, research vessels, commercial passenger lines, and tide gauges. These assets enable evaluation of system predictability and improvement through calibration of physical model parameters in addition to data assimilation using low-resolution remote-sensing satellites. Our prediction system is automated with high-end computers and enables better understanding of sub-mesoscale phenomena for more accurate determination of fishing conditions. High-resolution forecasts of hazardous rapid currents can be delivered via mobile phone to prevent damage to nets.

    Original languageEnglish
    Pages (from-to)125-140
    Number of pages16
    JournalProgress in Oceanography
    Volume121
    DOIs
    Publication statusPublished - Feb 2014

    All Science Journal Classification (ASJC) codes

    • Aquatic Science
    • Geology

    Fingerprint Dive into the research topics of 'Operational ocean prediction experiments for smart coastal fishing'. Together they form a unique fingerprint.

    Cite this