북극항로 선박항행정보시스템의 중기예측시스템

Abstract

Due to global warming, the sea ice in the Arctic Ocean is melting dramatically in summer, which is providing a new opportunity to exploit the Northern Sea Route (NSR) connecting Asia and Europe ship route. Recent increases in logistics transportation through NSR and resource development reveal the possible threats of marine pollution and marine transportation accidents without real-time navigation system. To develop a safe Voyage Environmental Information System (VEIS) for vessels operating, the Korea Institute of Ocean Science and Technology (KIOST) which is supported by the Ministry of Oceans and Fisheries, Korea has initiated the development of short-term and middle range prediction system for the sea ice concentration (SIC) and sea ice thickness (SIT) in NSR since 2014. The sea ice prediction system of VEIS consists of AMSR2 satellite composite images (a day), short-term (a week) prediction system, and middle range (a month) prediction system using a statistical method with re-analysis data (TOPAZ) and short-term predicted model data. In this study, the middle range prediction system for the SIC and SIT in NSR is calibrated with another middle range predicted atmospheric and oceanic data (NOAA CFSv2). The system predicts one month SIC and SIT on a daily basis, as validated with dynamic composite SIC data extracted from AMSR2 L2 satellite images.sportation through NSR and resource development reveal the possible threats of marine pollution and marine transportation accidents without real-time navigation system. To develop a safe Voyage Environmental Information System (VEIS) for vessels operating, the Korea Institute of Ocean Science and Technology (KIOST) which is supported by the Ministry of Oceans and Fisheries, Korea has initiated the development of short-term and middle range prediction system for the sea ice concentration (SIC) and sea ice thickness (SIT) in NSR since 2014. The sea ice prediction system of VEIS consists of AMSR2 satellite composite images (a day), short-term (a week) prediction system, and middle range (a month) prediction system using a statistical method with re-analysis data (TOPAZ) and short-term predicted model data. In this study, the middle range prediction system for the SIC and SIT in NSR is calibrated with another middle range predicted atmospheric and oceanic data (NOAA CFSv2). The system predicts one month SIC and SIT on a daily basis, as validated with dynamic composite SIC data extracted from AMSR2 L2 satellite images.