Skill assessment of Korea operational oceanographic system (KOOS)

Title
Skill assessment of Korea operational oceanographic system (KOOS)
Author(s)
김진아; 박광순
KIOST Author(s)
Kim, Jinah(김진아)
Publication Year
2016-02-22
Abstract
For the ocean forecast system in Korea, the Korea operational oceanographic system (KOOS) has been developed and pre-operated since 2009 by the Korea institute of ocean science and technology (KIOST) funded by the Korean government. KOOS provides real time information and forecasts for marine environmental conditions in order to support all kinds of activities in the sea. Furthermore, more significant purpose of the KOOS information is to response and support to maritime problems and accidents such as oil spill, red-tide, shipwreck, extraordinary wave, coastal inundation and so on. Accordingly, it is essential to evaluate prediction accuracy and efforts to improve accuracy. The forecast accuracy should meet orexceed target benchmarks before its products are approved for release to the public. In this paper, we conduct error quantification of the forecasts using skill assessment technique for judgement of the KOOS performance. Skill assessmentstatistics includes the measures of errors and correlations such as root-mean-square-error (RMSE), mean bias (MB), correlation coefficient (R), and index of agreement (IOA) and the frequency with which errors lie within specified limits termed the central frequency (CF).ovides real time information and forecasts for marine environmental conditions in order to support all kinds of activities in the sea. Furthermore, more significant purpose of the KOOS information is to response and support to maritime problems and accidents such as oil spill, red-tide, shipwreck, extraordinary wave, coastal inundation and so on. Accordingly, it is essential to evaluate prediction accuracy and efforts to improve accuracy. The forecast accuracy should meet orexceed target benchmarks before its products are approved for release to the public. In this paper, we conduct error quantification of the forecasts using skill assessment technique for judgement of the KOOS performance. Skill assessmentstatistics includes the measures of errors and correlations such as root-mean-square-error (RMSE), mean bias (MB), correlation coefficient (R), and index of agreement (IOA) and the frequency with which errors lie within specified limits termed the central frequency (CF).
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/24948
Bibliographic Citation
Ocean Science Meeting 2016, pp.1 - 2, 2016
Publisher
American
Type
Conference
Language
English
Publisher
American
Related Researcher
Research Interests

AI/Machine Learning,Climate Change,Marine Disaster,인공지능/기계학습,기후변화,해양기상재해

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