Abstract
Abstract. The Arctic regional coupled sea-ice–ocean–atmosphere model (ArcIOAM) has been developed to provide reliable Arctic sea ice prediction on seasonal timescales. The description and implementation of ArcIOAM and its preliminary results for the year of 2012 are presented in this paper. In the ArcIOAM configuration, the Community Coupler 2 (C-Coupler2) is used to couple the Arctic sea-ice–oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. A scalability test is performed to investigate the parallelization of the coupled model. As the first step toward reliable Arctic seasonal sea ice prediction, ArcIOAM, implemented with two-way coupling strategy along with one-way coupling strategy, is evaluated with respect to available observational data and reanalysis products for the year of 2012. A stand-alone MITgcm run with prescribed atmospheric forcing is performed for reference. From the comparison, all the experiments simulate reasonable evolution of sea ice and ocean states in the Arctic region over a 1-year simulation period. The two-way coupling has better performance in terms of sea ice extent, concentration, thickness and sea surface temperature (SST), especially in summer. This result indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.
Highlights
It is widely recognized that coupling between different Earth system components provides improved forecasts of oceanic and atmospheric states on various timescales (Neelin et al, 1994)
Arctic sea ice extent grew to maximum value of 14.5 million km2 in March 2012 and dropped to minimum value of 3.5 million km2 in September 2012 (Fig. 6a) according to the Multisensor Analyzed Sea Ice Extent – North Hemisphere (MASIE-NH) data (U.S National Ice Center and National Snow and Ice Data Center, 2010)
Because the sea ice initial condition on 1 January 2012 is derived from a stand-alone MITgcm simulation which is forced by the JRA55 data, the change of atmospheric forcing data from the JRA55 to the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) induces a model state adjustment period which lasts about 2 weeks
Summary
It is widely recognized that coupling between different Earth system components (ocean, atmosphere, sea ice and land) provides improved forecasts of oceanic and atmospheric states on various timescales (Neelin et al, 1994). As an essential component in the climate system, sea ice plays a crucial role in the global energy and water budget and has a substantial impact on atmospheric and oceanic circulation. Due to the projected increase in marine traffic through the Arctic marginal seas as climate change continues, there is amplified demand for reliable polar sea ice and marine environmental predictions from synoptic timescales to seasonal and interannual timescales. Climate models comprising phase 6 of the Coupled Model Intercomparison Project (CMIP6) are used for state-of-the-art sea ice prediction on seasonal to longer timescales.
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