Skill Assessment of the Operational Ocean Forecasting System in North Western Pacific Ocean

Title
Skill Assessment of the Operational Ocean Forecasting System in North Western Pacific Ocean
Author(s)
김진아; 정상훈; 박광순; 조경호
KIOST Author(s)
Kim, Jinah(김진아)Jeong, Sang Hun(정상훈)
Publication Year
2015-05-19
Abstract
In order to evaluate a performance of the Korea operational oceanographic system (KOOS), skill assessment has been conducted using both objective standards and measures against other prediction methods. Skill assessment requires a set of skill quantities and procedures in order to compare forecast outputs with the observation data. There are two quantities to measure both how model predictions differ from the observations such as root-mean-square error (RMSE), RMSE percentage (RMSE%), root-mean-square difference (RMSD), and mean bias (MB) and how model predictions are correlated with the observations such as correlation coefficient (R), index of agreement (IOA), and coefficient efficiency (E). As a representative measure and quality assurance standard, central frequency (CF) is used to indicate how often model errors fall within acceptable limits which was proposed by Zhang et al. (2010) and used in the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). In table 1, the statistics for skill assessment and acceptance criteria for the skill quantities are described and target criteria for CF are also presented according to atmospheric and hydrodynamic variables including atmospheric pressure, wind, water elevation, current velocity, water temperature, and salinity (Cho et al., 2014).ill quantities and procedures in order to compare forecast outputs with the observation data. There are two quantities to measure both how model predictions differ from the observations such as root-mean-square error (RMSE), RMSE percentage (RMSE%), root-mean-square difference (RMSD), and mean bias (MB) and how model predictions are correlated with the observations such as correlation coefficient (R), index of agreement (IOA), and coefficient efficiency (E). As a representative measure and quality assurance standard, central frequency (CF) is used to indicate how often model errors fall within acceptable limits which was proposed by Zhang et al. (2010) and used in the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). In table 1, the statistics for skill assessment and acceptance criteria for the skill quantities are described and target criteria for CF are also presented according to atmospheric and hydrodynamic variables including atmospheric pressure, wind, water elevation, current velocity, water temperature, and salinity (Cho et al., 2014).
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/25563
Bibliographic Citation
The 6th China-Korea Joint Workshop on Marine Environmental Forecasting for the Yellow Sea and East China Sea, pp.1 - 6, 2015
Publisher
NMEFC(China),
Type
Conference
Language
English
Publisher
NMEFC(China),
Related Researcher
Research Interests

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

Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse