Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Ar...Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).展开更多
The study of Arctic sea ice has traditionally been focused on large-scale such as reductions of ice coverage,thickness,volumes and sea ice regime shift.Research has primarily concentrated on the impact of large-scale ...The study of Arctic sea ice has traditionally been focused on large-scale such as reductions of ice coverage,thickness,volumes and sea ice regime shift.Research has primarily concentrated on the impact of large-scale external factors such as atmospheric and oceanic circulations,and solar radiation.Additionally,Arctic sea ice also undergoes rapid micro-scale evolution such as gas bubbles formation,brine pockets migration and massive formation of surface scattering layer.Field studies like CHINARE(2008-2018)and MOSAiC(2019-2020)have confirmed these observations,yet the full understanding of those changes remain insufficient and superficial.In order to cope better with the rapidly changing Arctic Ocean,this study reviews the recent advances in the microstructure of Arctic sea ice in both field observations and laboratory experiments,and looks forward to the future objectives on the microscale processes of sea ice.The significant porosity and the cyclical annual and seasonal shifts likely modify the ice's thermal,optical,and mechanical characteristics,impacting its energy dynamics and mass balance.Current thermodynamic models,both single-phase and dual-phase,fail to accurately capture these microstructural changes in sea ice,leading to uncertainties in the results.The discrepancy between model predictions and actual observations strongly motivates the parameterization on the evolution in ice microstructure and development of next-generation sea ice models,accounting for changes in ice crystals,brine pockets,and gas bubbles under the background of global warming.It helps to finally achieve a thorough comprehension of Arctic sea ice changes,encompassing both macro and micro perspectives,as well as externaland internal factors.展开更多
In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that o...In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.展开更多
A new viscoelastic-plastic （VEP） constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components： Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding cr...A new viscoelastic-plastic （VEP） constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components： Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding criterion, associated normality flow rule for plastic rehololgy, and hydrostatic pressure. The numerical simulations for ice motion in an idealized rectangular basin were made using smoothed particle hydrodynamics （SPH） method, and compared with the analytical solution as well as those based on the modified viscous plastic（VP） model and static ice jam theory. These simulations show that the new VEP model can simulate ice dynamics accurately. The new constitutive model was further applied to simulate ice dynamics of the Bohai Sea and compared with the traditional VP, and modified VP models. The results of the VEP model are compared better with the satellite remote images, and the simulated ice conditions in the JZ20-2 oil platform area were more reasonable.展开更多
Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind s...Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.展开更多
The coupled ice- ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat bal- ance at the sea- ice, air- ice, and air- sea interfaces of the Bohai Sea during...The coupled ice- ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat bal- ance at the sea- ice, air- ice, and air- sea interfaces of the Bohai Sea during the entire winter in 1998￣1999 and 2000￣2001. The cou- pled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.展开更多
The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperat...The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature(Had ISST) observations. Version 5.0 of CICE with elastic-viscous-plastic(EVP) dynamics simulates a September Arctic sea ice concentration(SASIC) trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend(-0.585 × 1012 m2 per decade). Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend(-0.470 × 1012 m2 per decade). Version 5.0 has a higher correlation(0.742) with observation than version 4.0(0.653). Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier(phase advancing) in both versions. Simulations also show that the September Arctic sea ice volume(SASIV) has a faster decreasing trend than SASIC.展开更多
Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large u...Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.展开更多
According to the earlier international studies on the coupled iceocean model and the hydrology, meteorology, and icefeatures in the Bohai Sea, a coupled iceocean model is developed based on the National Marine Environ...According to the earlier international studies on the coupled iceocean model and the hydrology, meteorology, and icefeatures in the Bohai Sea, a coupled iceocean model is developed based on the National Marine EnvironmentForecast Centers (NMEFC) numerical forecasting ice model of the Bohai Sea and the Princeton ocean model (POM).In the coupled model, the transfer of momentum and heat between ocean and ice is two-way, and the change of icethickness and concentration depends on heat budget not only at the surface and bottom of ice, but also at the surfaceof open water between ices. The dynamic and thermodynamic coupling process is expatiated emphatically. Somethermodynamic parameters are discussed as well.展开更多
Considering the discontinuous characteristics of sea ice on various scales,a modified discrete element model（DEM） for sea ice dynamics is developed based on the granular material rheology.In this modified DEM,a soft...Considering the discontinuous characteristics of sea ice on various scales,a modified discrete element model（DEM） for sea ice dynamics is developed based on the granular material rheology.In this modified DEM,a soft sea ice particle element is introduced as a self-adjustive particle size function.Each ice particle can be treated as an assembly of ice floes,with its concentration and thickness changing to variable sizes under the conservation of mass.In this model,the contact forces among ice particles are calculated using a viscous-elastic-plastic model,while the maximum shear forces are described with the Mohr-Coulomb friction law.With this modified DEM,the ice flow dynamics is simulated under the drags of wind and current in a channel of various widths.The thicknesses,concentrations and velocities of ice particles are obtained,and then reasonable dynamic process is analyzed.The sea ice dynamic process is also simulated in a vortex wind field.Taking the influence of thermodynamics into account,this modified DEM will be improved in the future work.展开更多
Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this stud...Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness(PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer(MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index(DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.展开更多
Emphasizing the model's ability in mean climate reproduction in high northern latitudes, results from an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model can simulate the mai...Emphasizing the model's ability in mean climate reproduction in high northern latitudes, results from an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model can simulate the main characteristics of annual mean global sea surface temperature and sea level pressure well, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The main distribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northern latitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproduce the Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the Northern Hemisphere is rational and its main distribution features in winter agree well with those from observations. But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Ocean is much larger than the observation. There are significant interannual variation signals in the simulated sea ice concentration in winter in high northern latitudes and the most significant area lies in the Greenland Sea, followed by the Barents Sea. All of these features agree well with the results from observations.展开更多
Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variabl...Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.展开更多
Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s.The prediction of sea ice is highly important,but accurate simulation of sea ice v...Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s.The prediction of sea ice is highly important,but accurate simulation of sea ice variations remains highly challenging.For improving model performance,sensitivity experiments were conducted using the coupled ocean and sea ice model(NEMO-LIM),and the simulation results were compared against satellite observations.Moreover,the contribution ratios of dynamic and thermodynamic processes to sea ice variations were analyzed.The results show that the performance of the model in reconstructing the spatial distribution of Arctic sea ice is highly sensitive to ice strength decay constant(C^(rhg)).By reducing the C^(rhg) constant,the sea ice compressive strength increases,leading to improved simulated sea ice states.The contribution of thermodynamic processes to sea ice melting was reduced due to less deformation and fracture of sea ice with increased compressive strength.Meanwhile,dynamic processes constrained more sea ice to the central Arctic Ocean and contributed to the increases in ice concentration,reducing the simulation bias in the central Arctic Ocean in summer.The root mean square error(RMSE)between modeled and the CryoSat-2/SMOS satellite observed ice thickness was reduced in the compressive strength-enhanced model solution.The ice thickness,especially of multiyear thick ice,was also reduced and matched with the satellite observation better in the freezing season.These provide an essential foundation on exploring the response of the marine ecosystem and biogeochemical cycling to sea ice changes.展开更多
Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surf...Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.展开更多
The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Interco...The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.展开更多
Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a ...Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factor a and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of Ca to Cw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean, Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level （0.2-0.25） for large floes in the central ice zone. The wind factor a increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%. And the deflection angle ~ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than 20% without a steady level like a. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient （Cs＇/Cs） and the ratio of ridge form drag coefficient （Cr＇/Cr） to the value of Ca/Cw, a, and 8, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.展开更多
Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and se...Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.展开更多
The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic mo...The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.展开更多
The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaska...The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaskan coast. The dynamics of this coupled ice-ocean system is important for both regional scale oceanography and large-scale global climate change research. A mumber of moorings were deployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A regional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depthaveraged annual mean ocean currents along the Beaufort Sea coast and shelf hreak compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model resuits captured the sea,real variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an ahnost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking hy the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice.展开更多
基金supported by the Chinese–Norwegian Collaboration Projects within Climate Systems jointly funded by the National Key Research and Development Program of China (Grant No.2022YFE0106800)the Research Council of Norway funded project,MAPARC (Grant No.328943)+2 种基金the support from the Research Council of Norway funded project,COMBINED (Grant No.328935)the National Natural Science Foundation of China (Grant No.42075030)the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX23_1314)。
文摘Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).
基金supported by the National Natural Science Foundation of China(Grant nos.42320104004 and 42276242)the National Key Research and Development Program of China(Grant no.2023YFC2809102).
文摘The study of Arctic sea ice has traditionally been focused on large-scale such as reductions of ice coverage,thickness,volumes and sea ice regime shift.Research has primarily concentrated on the impact of large-scale external factors such as atmospheric and oceanic circulations,and solar radiation.Additionally,Arctic sea ice also undergoes rapid micro-scale evolution such as gas bubbles formation,brine pockets migration and massive formation of surface scattering layer.Field studies like CHINARE(2008-2018)and MOSAiC(2019-2020)have confirmed these observations,yet the full understanding of those changes remain insufficient and superficial.In order to cope better with the rapidly changing Arctic Ocean,this study reviews the recent advances in the microstructure of Arctic sea ice in both field observations and laboratory experiments,and looks forward to the future objectives on the microscale processes of sea ice.The significant porosity and the cyclical annual and seasonal shifts likely modify the ice's thermal,optical,and mechanical characteristics,impacting its energy dynamics and mass balance.Current thermodynamic models,both single-phase and dual-phase,fail to accurately capture these microstructural changes in sea ice,leading to uncertainties in the results.The discrepancy between model predictions and actual observations strongly motivates the parameterization on the evolution in ice microstructure and development of next-generation sea ice models,accounting for changes in ice crystals,brine pockets,and gas bubbles under the background of global warming.It helps to finally achieve a thorough comprehension of Arctic sea ice changes,encompassing both macro and micro perspectives,as well as externaland internal factors.
基金supported by the National Natural Science Foundation of China(No.41075030,41106004,41106159 and 41206013)the Ocean Public Welfare Science Research Project,State Oceanic Administration,People's Republic of China(No.201005019)
文摘In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.
基金The authors would like to acknowledge the supports by the National Natural Science Foundation of China under contract No.40206004partly by the East-Asia and Pacific Program of US National Science Foundation under contract No.INT-9912246.
文摘A new viscoelastic-plastic （VEP） constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components： Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding criterion, associated normality flow rule for plastic rehololgy, and hydrostatic pressure. The numerical simulations for ice motion in an idealized rectangular basin were made using smoothed particle hydrodynamics （SPH） method, and compared with the analytical solution as well as those based on the modified viscous plastic（VP） model and static ice jam theory. These simulations show that the new VEP model can simulate ice dynamics accurately. The new constitutive model was further applied to simulate ice dynamics of the Bohai Sea and compared with the traditional VP, and modified VP models. The results of the VEP model are compared better with the satellite remote images, and the simulated ice conditions in the JZ20-2 oil platform area were more reasonable.
基金The National Natural Science Foundation of China under contract No.41571510the Fundamental Research Funds for the Central Universities of China under contract No.2014KJJCB02
文摘Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.
基金supported by the National Natural Science Foundation of China under contract Nos 40233032 and 40376006the National High Technolo-gy Research and Development Program of China(“863")under contract Nos 2002AA639340 and 2001 AA631070the Principal Project under contract Nos 2001DIA50040 and 2001CB7l1006.
文摘The coupled ice- ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat bal- ance at the sea- ice, air- ice, and air- sea interfaces of the Bohai Sea during the entire winter in 1998￣1999 and 2000￣2001. The cou- pled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.
基金supported by the National Basic Research Program of China(Grant No.2010CB951804)the China Meteorological Administration Special Fund for Scientific Research in the Public Interest(Grant No.GYHY201206008)
文摘The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature(Had ISST) observations. Version 5.0 of CICE with elastic-viscous-plastic(EVP) dynamics simulates a September Arctic sea ice concentration(SASIC) trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend(-0.585 × 1012 m2 per decade). Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend(-0.470 × 1012 m2 per decade). Version 5.0 has a higher correlation(0.742) with observation than version 4.0(0.653). Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier(phase advancing) in both versions. Simulations also show that the September Arctic sea ice volume(SASIV) has a faster decreasing trend than SASIC.
基金funded by the National Basic Research Program of China(Grant Nos.2010CB950102 and 2009CB421406)the Nansen Scientific Society(Norway)part of the SeaLev projects at the Centre of Climate Dynamics/Bjerknes Center in Bergen
文摘Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.
基金the National Natural Science Foundation of China under contract Nos40233032 , 40376006the National High Technology Research and Development Program(863) of China under contract Nos 2002AA639340 , 2001AA631070 the Principal Project under contract Nos2001DIA50040 , 2001CB711006.
文摘According to the earlier international studies on the coupled iceocean model and the hydrology, meteorology, and icefeatures in the Bohai Sea, a coupled iceocean model is developed based on the National Marine EnvironmentForecast Centers (NMEFC) numerical forecasting ice model of the Bohai Sea and the Princeton ocean model (POM).In the coupled model, the transfer of momentum and heat between ocean and ice is two-way, and the change of icethickness and concentration depends on heat budget not only at the surface and bottom of ice, but also at the surfaceof open water between ices. The dynamic and thermodynamic coupling process is expatiated emphatically. Somethermodynamic parameters are discussed as well.
基金Special Fund of Marine Commonweal Industry under contact Nos 201105016 and 201205007supported by National Marine Environment Forecasting Centrethe National Natural Science Foundation of China under contact No.41176012
文摘Considering the discontinuous characteristics of sea ice on various scales,a modified discrete element model（DEM） for sea ice dynamics is developed based on the granular material rheology.In this modified DEM,a soft sea ice particle element is introduced as a self-adjustive particle size function.Each ice particle can be treated as an assembly of ice floes,with its concentration and thickness changing to variable sizes under the conservation of mass.In this model,the contact forces among ice particles are calculated using a viscous-elastic-plastic model,while the maximum shear forces are described with the Mohr-Coulomb friction law.With this modified DEM,the ice flow dynamics is simulated under the drags of wind and current in a channel of various widths.The thicknesses,concentrations and velocities of ice particles are obtained,and then reasonable dynamic process is analyzed.The sea ice dynamic process is also simulated in a vortex wind field.Taking the influence of thermodynamics into account,this modified DEM will be improved in the future work.
基金Under the auspices of the National Natural Science Foundation of China(No.41306091)Public Science and Technology Research Funds Projects of Ocean(No.201505019-2)
文摘Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness(PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer(MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index(DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.
基金sponsored by the Knowledge Innovation Project of the Chinese Academy of Sciences (ZKCX2-SW-210)the National Natural Science Foundation of China (40233031)the National Key Project of Fundamental Research of China(G2000078502)
文摘Emphasizing the model's ability in mean climate reproduction in high northern latitudes, results from an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model can simulate the main characteristics of annual mean global sea surface temperature and sea level pressure well, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The main distribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northern latitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproduce the Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the Northern Hemisphere is rational and its main distribution features in winter agree well with those from observations. But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Ocean is much larger than the observation. There are significant interannual variation signals in the simulated sea ice concentration in winter in high northern latitudes and the most significant area lies in the Greenland Sea, followed by the Barents Sea. All of these features agree well with the results from observations.
基金This study was initialized during DAMOCLES project(Grant no.18509)which was funded by the 6th Framework Programme of the European Commission+2 种基金The initial data analysis was funded by the Research Council of Norway’s AMORA project(Grant no.#193592)The modelling work has been supported by the Academy of Finland(Contract 317999)The finalization of this work was supported by the European Union’s Horizon 2020 research and innovation programme(Grant no.727890–INTAROS).
文摘Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.
基金Supported by the National Natural Science Foundation of China(Nos.41630969,41941013,41806225)the Tianjin Municipal Natural Science Foundation(No.20JCQNJC01290)。
文摘Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s.The prediction of sea ice is highly important,but accurate simulation of sea ice variations remains highly challenging.For improving model performance,sensitivity experiments were conducted using the coupled ocean and sea ice model(NEMO-LIM),and the simulation results were compared against satellite observations.Moreover,the contribution ratios of dynamic and thermodynamic processes to sea ice variations were analyzed.The results show that the performance of the model in reconstructing the spatial distribution of Arctic sea ice is highly sensitive to ice strength decay constant(C^(rhg)).By reducing the C^(rhg) constant,the sea ice compressive strength increases,leading to improved simulated sea ice states.The contribution of thermodynamic processes to sea ice melting was reduced due to less deformation and fracture of sea ice with increased compressive strength.Meanwhile,dynamic processes constrained more sea ice to the central Arctic Ocean and contributed to the increases in ice concentration,reducing the simulation bias in the central Arctic Ocean in summer.The root mean square error(RMSE)between modeled and the CryoSat-2/SMOS satellite observed ice thickness was reduced in the compressive strength-enhanced model solution.The ice thickness,especially of multiyear thick ice,was also reduced and matched with the satellite observation better in the freezing season.These provide an essential foundation on exploring the response of the marine ecosystem and biogeochemical cycling to sea ice changes.
基金This study was a part of the Sino-Finnish long-term sea-ice research cooperationsupported by the National Natural Science Foundation of China under contract Nos 40233032 and 40376006.
文摘Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.
基金supported by the National Key R&D Program of China(Grant No.2018YFA0605904)the National Natural Science Foundation of China(Grant No.41701411).
文摘The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.
基金The National Natural Science Foundation of China under contracts Nos 41276191 and 41306207the Public Science and Technology Research Funds Projects of Ocean under contract No.201205007-05the Global Change Research Program of China under contract No.2015CB953901
文摘Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factor a and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of Ca to Cw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean, Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level （0.2-0.25） for large floes in the central ice zone. The wind factor a increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%. And the deflection angle ~ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than 20% without a steady level like a. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient （Cs＇/Cs） and the ratio of ridge form drag coefficient （Cr＇/Cr） to the value of Ca/Cw, a, and 8, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.
基金supported by the EC-funded project DAMOCLES (grant 18509)which is part of the Sixth Framework Program of DFG(grant LU 818/1-1)Natural Science Foundation of China(grants No.40233032,40376006).
文摘Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.
基金The National Natural Science Foundation of China under contract Nos 41576178 and 41630963the National Basic Research Program(973 program)of China under contract No.2015CB954004
文摘The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.
基金We acknowledge the support provided by the Minerals Management Service and the Coastal Marine Institute of University of Alaska Fair-banks project2004-061We would also like to acknowledge support from the International Arctic Research Center (IARC) of the University of AlaskaFairbanks and Japan Marine Science and Technology Center (JAMSTEC) and the mooring data from JAMSTECThis is GLERL Contribution No.1466
文摘The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaskan coast. The dynamics of this coupled ice-ocean system is important for both regional scale oceanography and large-scale global climate change research. A mumber of moorings were deployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A regional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depthaveraged annual mean ocean currents along the Beaufort Sea coast and shelf hreak compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model resuits captured the sea,real variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an ahnost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking hy the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice.
