CMIP5모형에서 나타난 북인도양 상층 오차

Title
CMIP5모형에서 나타난 북인도양 상층 오차
Alternative Title
Biases in the upper ocean in the northern Indian Ocean simulated by CMIP5 models
Author(s)
장찬주; 김철호; 김민우; 신호정
KIOST Author(s)
Jang, Chan Joo(장찬주)Kim, Minwoo(김민우)
Publication Year
2017-08-31
Abstract
Through its recent fifth assessment report, IPCC (Intergovernmental Panel on Climate Change) provides up-to-date scientific knowledge and socio-economic aspects of global climate change, mostly based on observational data and CMIP5 (Coupled Model Intercomparison Project Phase 5) global models. This study evaluates the upper ocean processes in the Indian Ocean in the Northern Hemisphere simulated by 19 CMIP5 models by comparing their historical run simulation with observed climatology. We found that, although significant progresses have been achieved through CMIP projects, there are still considerable common biases in simulation of the upper ocean in the northern Inian Ocean. For example, most of the analyzed CMIP5 models tend to have a cold bias in the sea surface temperature (SST), a fresh bias in the sea surface salinity, and a deep bias in the winter mixed layer depth (MLD). More importantly, the cold SST bias and deep bias in the winter MLD seem to be related with a strong wind bias, suggesting importance of proper wind representation for realistic upper ocean simulation in the northern Indian Ocean. Model Intercomparison Project Phase 5) global models. This study evaluates the upper ocean processes in the Indian Ocean in the Northern Hemisphere simulated by 19 CMIP5 models by comparing their historical run simulation with observed climatology. We found that, although significant progresses have been achieved through CMIP projects, there are still considerable common biases in simulation of the upper ocean in the northern Indian Ocean. For example, most of the analyzed CMIP5 models tend to have a cold bias in the sea surface temperature (SST), a fresh bias in the sea surface salinity, and a deep bias in the winter mixed layer depth (MLD). More importantly, the cold SST bias and deep bias in the winter MLD seem to be related with a strong wind bias, suggesting importance of proper wind representation for realistic upper ocean simulation in the northern Indian Ocean.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23854
Bibliographic Citation
Joint IAPSO-IAMAS-IAGA Assembly, pp.1173, 2017
Publisher
IUGG
Type
Conference
Language
English
Publisher
IUGG
Related Researcher
Research Interests

Ocean Modeling,Ocean Data Management,해양모형운용,해양자료처리

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