Sea ice is an important component in the Earth＇s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projecti...Sea ice is an important component in the Earth＇s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean- Atmosphere-Land System model Grid-point Version 2 （FGOALS-g2）, in the fifth phase of the Coupled Model Inter-comparison Project （CMIP5）, with a focus on historical experiments and late 20th century simu：ation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-gl.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future： （I） ocean model improvements to remove the artificial island at the North Pole; （2） higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and （3） ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.展开更多
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
Melt ponds significantly affect Arctic sea ice thermodynamic processes.The melt pond parameterization scheme in the Los Alamos sea ice model(CICE6.0) can predict the volume,area fraction(the ratio between melt pond ar...Melt ponds significantly affect Arctic sea ice thermodynamic processes.The melt pond parameterization scheme in the Los Alamos sea ice model(CICE6.0) can predict the volume,area fraction(the ratio between melt pond area to sea ice area in a model grid),and depth of melt ponds.However,this scheme has some uncertain parameters that affect melt pond simulations.These parameters could be determined through a conventional parameter estimation method,which requires a large number of sensitivity simulations.The adjoint model can calculate the parameter sensitivity efficiently.In the present research,an adjoint model was developed for the CESM(Community Earth System Model) melt pond scheme.A melt pond parameter estimation algorithm was then developed based on the CICE6.0 sea ice model,melt pond adjoint model,and L-BFGS(Limited-memory Broyden-Fletcher-Goldfard-Shanno) minimization algorithm.The parameter estimation algorithm was verified under idealized conditions.By using MODIS(Moderate Resolution Imaging Spectroradiometer)melt pond fraction observation as a constraint and the developed parameter estimation algorithm,the melt pond aspect ratio parameter in CESM scheme,which is defined as the ratio between pond depth and pond area fraction,was estimated every eight days during summertime for two different regions in the Arctic.One region was covered by multi-year ice(MYI) and the other by first-year ice(FYI).The estimated parameter was then used in simulations and the results show that:(1) the estimated parameter varies over time and is quite different for MYI and FYI;(2) the estimated parameter improved the simulation of the melt pond fraction.展开更多
Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological ele...Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological elements and turbulent flux, enabled this study to evaluate the sea ice surface energy budget process. Using in situ observations, three different reanalysis datasets from the European Centre for Medium-Range Weather Forecasts Interim Re-analysis(ERA-Interim), National Centers for Environmental Prediction Reanalysis2(NCEP R2), and Japanese 55-year Reanalysis(JRA55), and the Los Alamos sea ice model, CICE, output for surface fluxes were evaluated. The observed sensible heat flux(SH) and net longwave radiation showed seasonal variation with increasing temperature. Air temperature rose from the middle of October as the solar elevation angle increased.The ice surface lost more energy by outgoing longwave radiation as temperature increased, while the shortwave radiation showed obvious increases from the middle of October. The oceanic heat flux demonstrated seasonal variation and decreased with time, where the average values were 21 W/m^(2) and 11 W/m^(2), before and after August,respectively. The comparisons with in situ observations show that, SH and LE(latent heat flux) of JRA55 dataset had the smallest bias and mean absolute error(MAE), and those of NCEP R2 data show the largest differences.The ERA-Interim dataset had the highest spatial resolution, but performance was modest with bias and MAE between JRA55 and NCEP R2 compare with in situ observation. The CICE results(SH and LE) were consistent with the observed data but did not demonstrate the amplitude of inner seasonal variation. The comparison revealed better shortwave and longwave radiation stimulation based on the ERA-Interim forcing in CICE than the radiation of ERA-Interim. The average sea ice temperature decreased in June and July and increased after September,which was similar to the temperature measured by buoys, with a bias and MAE of 0.9℃ and 1.0℃, respectively.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
From October 28 to 30, 2006 Taishan International Congress of Culture & 1st Taishan Poetry Festival, co-organized by Center of International Cultural Exchange (CICE) and Tai’an Municipal Government, took place in...From October 28 to 30, 2006 Taishan International Congress of Culture & 1st Taishan Poetry Festival, co-organized by Center of International Cultural Exchange (CICE) and Tai’an Municipal Government, took place in Taishan Mountain, venerated as “the most superior among the five sacred mountains in China”. More than 100 poets, writers, artists and scholars from home and abroad gathered at the foot of Taishan Mountain to express their admiration for this holy mountain and discuss strategies for the development of Chinese culture.展开更多
基金supported by the National High-tech R&D Program(863)(Grant No.2010AA012304)the National Basic Research Program(973)(Grant No.2011CB309704)the National Natural Science Foundation of China(Grant No.51190101)
文摘Sea ice is an important component in the Earth＇s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean- Atmosphere-Land System model Grid-point Version 2 （FGOALS-g2）, in the fifth phase of the Coupled Model Inter-comparison Project （CMIP5）, with a focus on historical experiments and late 20th century simu：ation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-gl.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future： （I） ocean model improvements to remove the artificial island at the North Pole; （2） higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and （3） ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.
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funded by the National Key R&D Program of China (Grant No.2018YFA0605904)。
文摘Melt ponds significantly affect Arctic sea ice thermodynamic processes.The melt pond parameterization scheme in the Los Alamos sea ice model(CICE6.0) can predict the volume,area fraction(the ratio between melt pond area to sea ice area in a model grid),and depth of melt ponds.However,this scheme has some uncertain parameters that affect melt pond simulations.These parameters could be determined through a conventional parameter estimation method,which requires a large number of sensitivity simulations.The adjoint model can calculate the parameter sensitivity efficiently.In the present research,an adjoint model was developed for the CESM(Community Earth System Model) melt pond scheme.A melt pond parameter estimation algorithm was then developed based on the CICE6.0 sea ice model,melt pond adjoint model,and L-BFGS(Limited-memory Broyden-Fletcher-Goldfard-Shanno) minimization algorithm.The parameter estimation algorithm was verified under idealized conditions.By using MODIS(Moderate Resolution Imaging Spectroradiometer)melt pond fraction observation as a constraint and the developed parameter estimation algorithm,the melt pond aspect ratio parameter in CESM scheme,which is defined as the ratio between pond depth and pond area fraction,was estimated every eight days during summertime for two different regions in the Arctic.One region was covered by multi-year ice(MYI) and the other by first-year ice(FYI).The estimated parameter was then used in simulations and the results show that:(1) the estimated parameter varies over time and is quite different for MYI and FYI;(2) the estimated parameter improved the simulation of the melt pond fraction.
基金The National Key R&D Program of China under contract No. 2018YFA0605903the National Natural Science Foundation of China under contract Nos 41941009, 41922044 and 41876212the Guangdong Basic and Applied Basic Research Foundation under contract No. 2020B1515020025。
文摘Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological elements and turbulent flux, enabled this study to evaluate the sea ice surface energy budget process. Using in situ observations, three different reanalysis datasets from the European Centre for Medium-Range Weather Forecasts Interim Re-analysis(ERA-Interim), National Centers for Environmental Prediction Reanalysis2(NCEP R2), and Japanese 55-year Reanalysis(JRA55), and the Los Alamos sea ice model, CICE, output for surface fluxes were evaluated. The observed sensible heat flux(SH) and net longwave radiation showed seasonal variation with increasing temperature. Air temperature rose from the middle of October as the solar elevation angle increased.The ice surface lost more energy by outgoing longwave radiation as temperature increased, while the shortwave radiation showed obvious increases from the middle of October. The oceanic heat flux demonstrated seasonal variation and decreased with time, where the average values were 21 W/m^(2) and 11 W/m^(2), before and after August,respectively. The comparisons with in situ observations show that, SH and LE(latent heat flux) of JRA55 dataset had the smallest bias and mean absolute error(MAE), and those of NCEP R2 data show the largest differences.The ERA-Interim dataset had the highest spatial resolution, but performance was modest with bias and MAE between JRA55 and NCEP R2 compare with in situ observation. The CICE results(SH and LE) were consistent with the observed data but did not demonstrate the amplitude of inner seasonal variation. The comparison revealed better shortwave and longwave radiation stimulation based on the ERA-Interim forcing in CICE than the radiation of ERA-Interim. The average sea ice temperature decreased in June and July and increased after September,which was similar to the temperature measured by buoys, with a bias and MAE of 0.9℃ and 1.0℃, respectively.
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.
文摘From October 28 to 30, 2006 Taishan International Congress of Culture & 1st Taishan Poetry Festival, co-organized by Center of International Cultural Exchange (CICE) and Tai’an Municipal Government, took place in Taishan Mountain, venerated as “the most superior among the five sacred mountains in China”. More than 100 poets, writers, artists and scholars from home and abroad gathered at the foot of Taishan Mountain to express their admiration for this holy mountain and discuss strategies for the development of Chinese culture.
