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NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China

Authors :
Petteri Uotila
Andrea M. U. Gierisch
Yu Yan
Yingjun Xu
Wei Gu
Institute for Atmospheric and Earth System Research (INAR)
Source :
Geoscientific Model Development, Vol 15, Pp 1269-1288 (2022)
Publication Year :
2022
Publisher :
Copernicus Publications, 2022.

Abstract

Severe ice conditions in the Bohai Sea could cause serious harm to maritime traffic, offshore oil exploitation, aquaculture, and other economic activities in the surrounding regions. In addition to providing sea ice forecasts for disaster prevention and risk mitigation, sea ice numerical models could help explain the sea ice variability within the context of climate change in marine ecosystems, such as spotted seals, which are the only ice-dependent animal that breeds in Chinese waters. Here, we developed NEMO-Bohai, an ocean–ice coupled model based on the Nucleus for European Modelling of the Ocean (NEMO) model version 4.0 and Sea Ice Modelling Integrated Initiative (SI3) (NEMO4.0-SI3) for the Bohai Sea. This study will present the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of the ocean and sea ice. The model simulations agree with the observations with respect to sea surface height (SSH), temperature (SST), salinity (SSS), currents, and temperature and salinity stratification. The seasonal variation of the sea ice area is well simulated by the model compared to the satellite remote sensing data for the period of 1996–2017. Overall agreement is found for the occurrence dates of the annual maximum sea ice area. The simulated sea ice thickness and volume are in general agreement with the observations with slight overestimations. NEMO-Bohai can simulate seasonal sea ice evolution and long-term interannual variations. Hence, NEMO-Bohai is a valuable tool for long-term ocean and ice simulations and climate change studies.

Details

Language :
English
ISSN :
19919603
Volume :
15
Database :
OpenAIRE
Journal :
Geoscientific Model Development
Accession number :
edsair.doi.dedup.....156a8d2994d8748dfab1ba552e7e141a