Sea ice is a sensitive indicator of climate change and an important component of climate system models. The Los Alamos Sea Ice Model 5.0(CICE5.0) was introduced to the Beijing Climate Center Climate System Model(BCC_C...Sea ice is a sensitive indicator of climate change and an important component of climate system models. The Los Alamos Sea Ice Model 5.0(CICE5.0) was introduced to the Beijing Climate Center Climate System Model(BCC_CSM) as a new alternative to the Sea Ice Simulator(SIS). The principal purpose of this paper is to analyze the impacts of these two sea ice components on simulations of basic Arctic sea ice, atmosphere, and ocean states. Two sets of experiments were conducted with the same configurations except for the sea ice component used, i.e., SIS and CICE. The distributions of sea ice concentration and thickness reproduced by the CICE simulations in both March and September were closer to actual observations than those reproduced by SIS simulations, which presented a very thin sea ice cover in September. Changes in sea ice conditions also brought about corresponding modifications to the atmosphere and ocean circulation. CICE simulations showed higher agreement with the reference datasets than did SIS simulations for surface air temperature, sea level pressure, and sea surface temperature in most parts of the Arctic Ocean. More importantly, compared with simulations with SIS, BCC_CSM with CICE revealed stronger Atlantic meridional overturning circulation(AMOC), which is more consistent with actual observations. Thus, CICE shows better performance than SIS in BCC_ CSM. However, both components demonstrate a number of common weaknesses, such as overestimation of the sea ice cover in winter, especially in the Nordic Sea and the Sea of Okhotsk. Additional studies and improvements are necessary to develop these components further.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
The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an ...The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions(CICE4.0 and CICE5.0),the advantages of CICE6.0(the latest version)are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.展开更多
In this study,we perform a stand-alone sensitivity study using the Los Alamos Sea ice model version 6(CICE6)to investigate the model sensitivity to two Ice-Ocean(IO)boundary condition approaches.One is the two-equatio...In this study,we perform a stand-alone sensitivity study using the Los Alamos Sea ice model version 6(CICE6)to investigate the model sensitivity to two Ice-Ocean(IO)boundary condition approaches.One is the two-equation approach that treats the freezing temperature as a function of the ocean mixed layer(ML)salinity,using two equations to parametrize the IO heat exchanges.Another approach uses the salinity of the IO interface to define the actual freezing temperature,so an equation describing the salt flux at the IO interface is added to the two-equation approach,forming the so-called three-equation approach.We focus on the impact of the three-equation boundary condition on the IO heat exchange and associated basal melt/growth of the sea ice in the Arctic Ocean.Compared with the two-equation simulation,our three-equation simulation shows a reduced oceanic turbulent heat flux,weakened basal melt,increased ice thickness,and reduced sea surface temperature(SST)in the Arctic.These impacts occur mainly at the ice edge regions and manifest themselves in summer.Furthermore,in August,we observed a downward turbulent heat flux from the ice to the ocean ML in two of our three-equation sensitivity runs with a constant heat transfer coefficient(0.006),which caused heat divergence and congelation at the ice bottom.Additionally,the influence of different combinations of heat/salt transfer coefficients and thermal conductivity in the three-equation approach on the model simulated results is assessed.The results presented in this study can provide insight into sea ice model sensitivity to the three-equation IO boundary condition for coupling the CICE6 to climate models.展开更多
Sea ice is the predominant natural threat to marine structures and oil-gas exploitation in the Arctic.However,for ice-resistant structural design,long-term successive level ice thickness measurements are still lacking...Sea ice is the predominant natural threat to marine structures and oil-gas exploitation in the Arctic.However,for ice-resistant structural design,long-term successive level ice thickness measurements are still lacking.To fill this gap in the southern Kara Sea,the Los Alamos Sea Ice Model(CICE)is applied to achieve better simulation at the local and regional scales.Based on the validation against ice thickness observations in March and April in 1980-1986,the statistical root-mean-square error is determined to be less than 0.2 m.Then,based on the hindcast data,the spatiotemporal distributions of level ice thickness are analyzed annually,seasonally,and monthly,with thicker level ice of 1.2-1.5 m in spring and large ice-free zones in September and October.For floating platforms,a novel ice grade criterion with five classifications,namely,excellent,good,moderate,severe,and catastrophic,is pro-posed.The first two grades are most suitable for offshore activities,particularly from August to October,and the moderate grade is acceptable if with ice-resistant protections.Furthermore,hostile ice conditions are discussed in terms of the generalized extreme value distribution.The statistics reveal that at a return period of 100 yr,extreme level ice is primarily between 0.6 m and 1.0 m in December.The present investigation could be a useful reference for a feasibility study of the potential risk analysis and ice-resistant operation of oil-gas exploitation in the Arctic.展开更多
基金supported by the National Basic Research Program of China (No. 2015CB953904)the Welfare Program of Meteorology (No. GYHY201506011)the National Key R&D Program (Nos. 2016YFA060 2602, 2018YFC1407104)
文摘Sea ice is a sensitive indicator of climate change and an important component of climate system models. The Los Alamos Sea Ice Model 5.0(CICE5.0) was introduced to the Beijing Climate Center Climate System Model(BCC_CSM) as a new alternative to the Sea Ice Simulator(SIS). The principal purpose of this paper is to analyze the impacts of these two sea ice components on simulations of basic Arctic sea ice, atmosphere, and ocean states. Two sets of experiments were conducted with the same configurations except for the sea ice component used, i.e., SIS and CICE. The distributions of sea ice concentration and thickness reproduced by the CICE simulations in both March and September were closer to actual observations than those reproduced by SIS simulations, which presented a very thin sea ice cover in September. Changes in sea ice conditions also brought about corresponding modifications to the atmosphere and ocean circulation. CICE simulations showed higher agreement with the reference datasets than did SIS simulations for surface air temperature, sea level pressure, and sea surface temperature in most parts of the Arctic Ocean. More importantly, compared with simulations with SIS, BCC_CSM with CICE revealed stronger Atlantic meridional overturning circulation(AMOC), which is more consistent with actual observations. Thus, CICE shows better performance than SIS in BCC_ CSM. However, both components demonstrate a number of common weaknesses, such as overestimation of the sea ice cover in winter, especially in the Nordic Sea and the Sea of Okhotsk. Additional studies and improvements are necessary to develop these components further.
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This research is supported jointly by the National Key R&D Program of China[grant numbers 2016YFA0602100 and 2018YFC1407104]the china Special Fund for Meteorological Research in the Public Interest[grant number GYHY201506011]the National Natural Science Foundation of China[grant number 41975134].
文摘The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions(CICE4.0 and CICE5.0),the advantages of CICE6.0(the latest version)are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.
基金the National Key R&D Program of China(Grant No.2018YFA0605901)the National Natural Science Foundation of China(Grant No.41775089)+1 种基金the National Key R&D Program of China(Grant No.2017YFC1502304)the Partnership for Education and Cooperation in Operational Oceanography(PECO_(2))project awarded by the Research Council of Norway(111280).
文摘In this study,we perform a stand-alone sensitivity study using the Los Alamos Sea ice model version 6(CICE6)to investigate the model sensitivity to two Ice-Ocean(IO)boundary condition approaches.One is the two-equation approach that treats the freezing temperature as a function of the ocean mixed layer(ML)salinity,using two equations to parametrize the IO heat exchanges.Another approach uses the salinity of the IO interface to define the actual freezing temperature,so an equation describing the salt flux at the IO interface is added to the two-equation approach,forming the so-called three-equation approach.We focus on the impact of the three-equation boundary condition on the IO heat exchange and associated basal melt/growth of the sea ice in the Arctic Ocean.Compared with the two-equation simulation,our three-equation simulation shows a reduced oceanic turbulent heat flux,weakened basal melt,increased ice thickness,and reduced sea surface temperature(SST)in the Arctic.These impacts occur mainly at the ice edge regions and manifest themselves in summer.Furthermore,in August,we observed a downward turbulent heat flux from the ice to the ocean ML in two of our three-equation sensitivity runs with a constant heat transfer coefficient(0.006),which caused heat divergence and congelation at the ice bottom.Additionally,the influence of different combinations of heat/salt transfer coefficients and thermal conductivity in the three-equation approach on the model simulated results is assessed.The results presented in this study can provide insight into sea ice model sensitivity to the three-equation IO boundary condition for coupling the CICE6 to climate models.
基金supported by the National Key Research and Development Program of China(No.2016YFC0303401)the National Natural Science Foundation of China(No.51779236)the National Natural Science Foundation of China-Shandong Joint Fund(No.U1706226).
文摘Sea ice is the predominant natural threat to marine structures and oil-gas exploitation in the Arctic.However,for ice-resistant structural design,long-term successive level ice thickness measurements are still lacking.To fill this gap in the southern Kara Sea,the Los Alamos Sea Ice Model(CICE)is applied to achieve better simulation at the local and regional scales.Based on the validation against ice thickness observations in March and April in 1980-1986,the statistical root-mean-square error is determined to be less than 0.2 m.Then,based on the hindcast data,the spatiotemporal distributions of level ice thickness are analyzed annually,seasonally,and monthly,with thicker level ice of 1.2-1.5 m in spring and large ice-free zones in September and October.For floating platforms,a novel ice grade criterion with five classifications,namely,excellent,good,moderate,severe,and catastrophic,is pro-posed.The first two grades are most suitable for offshore activities,particularly from August to October,and the moderate grade is acceptable if with ice-resistant protections.Furthermore,hostile ice conditions are discussed in terms of the generalized extreme value distribution.The statistics reveal that at a return period of 100 yr,extreme level ice is primarily between 0.6 m and 1.0 m in December.The present investigation could be a useful reference for a feasibility study of the potential risk analysis and ice-resistant operation of oil-gas exploitation in the Arctic.
