| An ocean model developed by the Bergen University in Norway (BOM, Bergen Ocean Model) was coupled with a state of art sea ice model CSIM4 (Community Sea Ice Model Version 4). The Coupled model was used to simulate the Arctic Ocean sea ice climate variability. Based on the data analysis and numerical simulation, the Arctic sea ice climate variability was researched, the result were as following:(1) The analysis on the seasonal cycle of the Arctic Ocean and atmosphere showed that: (a) The seasonal surface wind is somewhat trade wind like in some regions in the Arctic, (b) The surface air temperature is robustly determined from the underlying environments such as sea ice and Greenland glaciers, (c) In the sea ice region the precipitation rate is larger than that of evaporation. Furthermore, the Arctic Ocean hydrology is profoundly influenced by the surrounding rivers discharge. These are the decisive factors on the ocean salinity pattern, (d) Sea ice flux through the Fram Strait is larger in winter than in summer. From the 40s in the 20th century on, the ice volume flux has an increasing trend, (e) The Arctic rivers flood season is about the melt period, the winter rivers discharge has a significant increasing, (f) Correlation analysis shows that 7 to 10 years is a characteristic time scale that rivers discharge leads Fram Strait ice volume export.(2) Considering 9 major arctic rivers, the Arctic Ocean circulation was simulated through BOM. The result shows that: (a) The BOM can reproduce the main Arctic Ocean circulation pattern, (b) The "Islandization" which is commonly used in OGCMs to treat the North Pole, not only influences the ocean current near the pole, but also influences the current in the Northern Atlantic Ocean, thus the bogus island might influence global climate through thermohaline circulation in the Atlantic Ocean.(3) Using the CSIM4, the Arctic sea ice equilibrium state was simulated reasonably. The simulated ice thickness distribution pattern very like that detected by submarine investigations. The simulated ice concentration and motion are similar to the observation.(4) According to the energy conservation theory, BOM and CSIM4 were coupled, (a) The BOM has no treatment on transmission solar radiation, which is of great importance when the model is adapted to Arctic Ocean. So the treatment was introduced to BOM. (b) Through numerical test on different lead albedos, it was found that sea ice thickness is not so sensitive to lead albedo, which may be contribute to the lead occupies little ratio within multiyear sea ice pack, (c) The reason of summerover-melt of arctic sea ice is the NCEP reanalysis downward solar radiation being larger than its reality. Then the arctic sea ice climate variability was simulated. Results showed that: (a) simulated ice thickness change is in accord with the submarine investigated mean sea-ice draft changes, (b) Simulated annually maximum ice thickness along the Eurasian continental oceans are closely related to the observed ones, (c) The long-term mean simulated ice motion has the same features of the SSM/I derived ice motion, (d) Sea ice extents in differential sub-regions have same trends comparing to the satellite passive-microwave data derived ones, (e) Simulated ice concentration is closely related to the observed in the Arctic sub-regions, (f) Sea ice flux through the Fram Strait involves ice concentration, motion and thickness. It is a composite criterion for sea ice model evaluation. The simulated ice area and volume export through the strait accord with the satellite derived or statistically reconstructed ones.(5) The simulated ice thickness climate variability and mean sea surface current of the coupled model were analyzed, results showed: (a) the total ice volume in the Arctic Ocean has a significant decreasing trend. The volume variability is of a 10-year timescale oscillation, with two major periods of 12~13a and 18~20a. (b) Mean ice thickness in the arctic sub-seas has different tendencies. It has an increasing trend in the Barents-K...
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