Sea ice drift is a critical parameter for understanding the rapid changes in Arctic sea ice.Since the release of the Coupled Model Intercomparison Project Phase 6(CMIP6),there has been a lack of quantitative analysis ...Sea ice drift is a critical parameter for understanding the rapid changes in Arctic sea ice.Since the release of the Coupled Model Intercomparison Project Phase 6(CMIP6),there has been a lack of quantitative analysis regarding CMIP6's simulation of Arctic sea ice drift.This study aims to assess the simulated Arctic sea ice drift from 1979 to 2014 by fifteen CMIP6 models against recent satellite retrievals,utilizing various quantitative indices.Additionally,the influence of near-surface wind and surface ocean current on model performance is further analyzed.The CMIP6 models capture several aspects of the observed Arctic sea ice drift climatology and variability.The seasonal patterns of sea ice drift speed in all models exhibit similarities with the observed data,and the models agree with the evaluation datasets,indicating that the seasonal evolution of sea ice drift corresponds to near-surface wind patterns.However,notable discrepancies are identified.All models overestimate sea ice drift speed,exceeding the observational data by 36%e97%.Fourteen out of fifteen models display larger seasonal variability(ranging from 0.74 to 1.28 km d^(-1))compared to the observed data(0.54 km d^(-1)).Seven out of fifteen models exhibit a significant increasing trend in annual sea ice drift speed,similar to the observed trend of 0.58 km d^(-1) per decade,but with weaker trends(ranging from 0.11 to 0.33 km d^(-1) per decade).The remaining eight models reveal no statistically significant trend.The potential causes of such biases were further explored in this study.It suggests that the overestimation of sea ice drift speed in the models might be primarily attributed to the overestimation of near-surface wind speeds and their influence on sea ice drift speed.The models'overestimation of seasonal variability in near-surface wind speeds may account for the overestimation of seasonal variability in sea ice drift.The models'inability to represent the trend in sea ice drift speed may result from their failure to simulate an increasing trend in surface ocean current speed.展开更多
The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric...The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.展开更多
Sea ice hinders the navigability of the Arctic,especially in winter and spring.However,three Arc7 ice-class Liquefied Natural Gas carrying vessels safely transited the Northern Sea Route(NSR)without icebreaker assista...Sea ice hinders the navigability of the Arctic,especially in winter and spring.However,three Arc7 ice-class Liquefied Natural Gas carrying vessels safely transited the Northern Sea Route(NSR)without icebreaker assistance in January 2021.More and more Arc7 ice-class vessels are putting into the transit services in the NSR.Therefore,it is necessary to analyze sea-ice conditions and their impact on navigation during wintertime,and the future navigability of Arc7 ice-class vessels along the NSR during winter and spring.Based on sea ice datasets from satellite observations and a model using data assimilation,we explored the sea-ice conditions and their impact during the first three successful commercial voyages through the NSR in winter.In addition,we analyzed the sea ice variation and estimated navigability for Arc7 ice-class vessels in the NSR from January to June of the years 2021–2050 using future projections of the sea-ice cover by the Coupled Model Inter-comparison Project Phase 6(CMIP6)models under two emission scenarios(SSP2-4.5 and SSP5-8.5).The results reveal lower sea ice thickness and similar sea ice concentration during these three transits relative to the past 42 years(from 1979 to 2020).We found the thickness has a larger impact on the vessels’speeds than sea ice concentration.Very likely sea ice thickness played a larger role than the sea ice concentration for the successful transit of the NSR in winter 2021.Future projections suggest sea ice thickness will decrease further in most regions of the NSR from January to June under all scenarios enabling increased navigability of the NSR for Arc7 ice-class vessels.Such vessels could transit through the NSR from January to June under all scenarios by 2050,while some areas near the coast of East Siberian Sea remain inaccessible for Arc7 ice-class vessels in spring(April and May).These findings can support the strategic planning of shipping along the NSR in winter and spring.展开更多
Landfast ice plays an important role in atmosphere‒ocean interactions and ecosystems in the near coast area of Antarctica.Understanding the characteristics and variations of landfast ice is crucial to the study of cli...Landfast ice plays an important role in atmosphere‒ocean interactions and ecosystems in the near coast area of Antarctica.Understanding the characteristics and variations of landfast ice is crucial to the study of climates and field activities in Antarctic.In this study,a high-resolution thermodynamic snow-ice(HIGHTSI)model was applied to simulate the seasonal changes of landfast ice along the Mawson Coast,East Antarctica,through ERA-Interim reanalysis data.Four ocean heat-flux(Fw)values(10,15,20 and 25 W m−2)were used in sensitivity experiments.The results showed that it is reasonable to simulate landfast ice using the HIGHTSI model,and the simulation of landfast ice thickness matched best well with field measurements when Fw was 20 W m^(−2).Then,2-D distributions of landfast ice from 2006 to 2018 were modeled by HIGHTSI with 2-D ERA-Interim reanalysis data in a 0.125°×0.125°cell grid as external forcing.The results showed that fast ice was thicker along the coast and thinner near open water,and usually reaches its maximal thickness in October,varying from 1.2 to 2.0 m through the study area.There was no statistical trend for the thickness during the study period.展开更多
The presence or absence of sea ice introduces a substantial perturbation to surface-atmosphere energy exchanges.Comprehending the effect of varying sea ice cover on surface-atmosphere interactions is an important cons...The presence or absence of sea ice introduces a substantial perturbation to surface-atmosphere energy exchanges.Comprehending the effect of varying sea ice cover on surface-atmosphere interactions is an important consideration for understanding the Arctic climate system.The recurring North Water Polynya(NOW)serves as a natural laboratory for isolating cloud responses to a rapid,near-step perturbation in sea ice.In this study,we employed high-resolution Arctic System Reanalysis version 2(ASRv2)data to estimate turbulent heat fluxes over the NOW and nearby sea ice(NSI)area between 2005/2006 and 2015/2016.The results indicate that the average turbulent heat fluxes in the polynya are about 87%and 86%higher than in the NSI area over the 10 years during the entire duration of the polynya and during polar night,respectively.Enhanced turbulent heat fluxes from the polynya tend to produce more low-level clouds.The relationship between the polynya and low cloud in winter was examined based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO).The low-cloud fraction(0-2 km)was about 7%-34%larger over the polynya than the NSI area,and the ice water content below 200 m was about 250%-413%higher over the former than the latter.The correlation between cloud fraction and turbulent heat fluxes in the polynya peaks around the altitude of 200-300 m.These results suggest that the NOW affects the Arctic boundary layer cloudiness and structure in wintertime.Furthermore,higher horizontal resolution reanalysis data can advance our understanding of the cloud-polynya response.展开更多
In 2023,Antarctica experienced its lowest sea ice extent in the satellite era,with extreme polar events gaining widespread attention.Prydz Bay,where the Chinese Zhongshan Station is located,is the third largest embaym...In 2023,Antarctica experienced its lowest sea ice extent in the satellite era,with extreme polar events gaining widespread attention.Prydz Bay,where the Chinese Zhongshan Station is located,is the third largest embayment in Antarctica.Changes in sea ice,fast ice and polynyas directly affect local heat and mass exchanges between the ocean and atmosphere,as well as ecosystems and research activities.In 2023,substantial fast ice anomalies were observed in Prydz Bay:the extent of fast ice off Zhongshan Station(ZSFI)was anomalously low,while that within Barrier Bay(BaFI)was anomalously high.This study analysed the seasonal evolution and underlying main causes for the extreme conditions using ice charts,satellites and reanalysis data.From 2014 to 2022,the extent of zSFI typically increased during the cold season,reaching a maximum of(9.41±2.47)×10^(3) km^(2),whilst the Barrier Bay Polynya(BaP)persisted throughout this period.However,in 2023,ZSFI did not increase from June onwards,peaking at a maximum extent of only 5.49×10^(3) km^(2),and the BaP closed in mid-winter,leading to the formation of extensive BaFI.Air temperature and wind speed continuously dropped in July,and these conditions persisted for approximately 1 month,leading to the closure of BaP.However,zSFI did not expand further under these extreme meteorological conditions,indicating its independence from these factors.The limited expansion of ZSFI could be attributed to high ocean temperatures.Overall,this study provides valuable insights into the mechanisms driving extreme fast ice conditions.展开更多
基金funded by the National Key Research and Development Program of China(2021YFC2800705)the National Natural Science Foundation of China(42206247)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2021A1515110779)Fengyun Application Pioneering Project(FY-APP-2022.0201).
文摘Sea ice drift is a critical parameter for understanding the rapid changes in Arctic sea ice.Since the release of the Coupled Model Intercomparison Project Phase 6(CMIP6),there has been a lack of quantitative analysis regarding CMIP6's simulation of Arctic sea ice drift.This study aims to assess the simulated Arctic sea ice drift from 1979 to 2014 by fifteen CMIP6 models against recent satellite retrievals,utilizing various quantitative indices.Additionally,the influence of near-surface wind and surface ocean current on model performance is further analyzed.The CMIP6 models capture several aspects of the observed Arctic sea ice drift climatology and variability.The seasonal patterns of sea ice drift speed in all models exhibit similarities with the observed data,and the models agree with the evaluation datasets,indicating that the seasonal evolution of sea ice drift corresponds to near-surface wind patterns.However,notable discrepancies are identified.All models overestimate sea ice drift speed,exceeding the observational data by 36%e97%.Fourteen out of fifteen models display larger seasonal variability(ranging from 0.74 to 1.28 km d^(-1))compared to the observed data(0.54 km d^(-1)).Seven out of fifteen models exhibit a significant increasing trend in annual sea ice drift speed,similar to the observed trend of 0.58 km d^(-1) per decade,but with weaker trends(ranging from 0.11 to 0.33 km d^(-1) per decade).The remaining eight models reveal no statistically significant trend.The potential causes of such biases were further explored in this study.It suggests that the overestimation of sea ice drift speed in the models might be primarily attributed to the overestimation of near-surface wind speeds and their influence on sea ice drift speed.The models'overestimation of seasonal variability in near-surface wind speeds may account for the overestimation of seasonal variability in sea ice drift.The models'inability to represent the trend in sea ice drift speed may result from their failure to simulate an increasing trend in surface ocean current speed.
基金This work was supported by the National Natural Science Foundation of China(41976214)The European Union's Horizon 2020 research and innovation programme provided support to BC and TV through the Polar Regions in the Earth System project(PolarRES,101003590)to MAG through the Climate Relevant interactions and feedbacks:the key role of sea ice and Snow in the polar and global climate system project(CRiceS,101003826).
文摘The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.
基金supported by the National Natural Science Foundation of China(41976214)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021008).
文摘Sea ice hinders the navigability of the Arctic,especially in winter and spring.However,three Arc7 ice-class Liquefied Natural Gas carrying vessels safely transited the Northern Sea Route(NSR)without icebreaker assistance in January 2021.More and more Arc7 ice-class vessels are putting into the transit services in the NSR.Therefore,it is necessary to analyze sea-ice conditions and their impact on navigation during wintertime,and the future navigability of Arc7 ice-class vessels along the NSR during winter and spring.Based on sea ice datasets from satellite observations and a model using data assimilation,we explored the sea-ice conditions and their impact during the first three successful commercial voyages through the NSR in winter.In addition,we analyzed the sea ice variation and estimated navigability for Arc7 ice-class vessels in the NSR from January to June of the years 2021–2050 using future projections of the sea-ice cover by the Coupled Model Inter-comparison Project Phase 6(CMIP6)models under two emission scenarios(SSP2-4.5 and SSP5-8.5).The results reveal lower sea ice thickness and similar sea ice concentration during these three transits relative to the past 42 years(from 1979 to 2020).We found the thickness has a larger impact on the vessels’speeds than sea ice concentration.Very likely sea ice thickness played a larger role than the sea ice concentration for the successful transit of the NSR in winter 2021.Future projections suggest sea ice thickness will decrease further in most regions of the NSR from January to June under all scenarios enabling increased navigability of the NSR for Arc7 ice-class vessels.Such vessels could transit through the NSR from January to June under all scenarios by 2050,while some areas near the coast of East Siberian Sea remain inaccessible for Arc7 ice-class vessels in spring(April and May).These findings can support the strategic planning of shipping along the NSR in winter and spring.
基金funded by the National Natural Science Foundation of China(41925027,41676176)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021008).
文摘Landfast ice plays an important role in atmosphere‒ocean interactions and ecosystems in the near coast area of Antarctica.Understanding the characteristics and variations of landfast ice is crucial to the study of climates and field activities in Antarctic.In this study,a high-resolution thermodynamic snow-ice(HIGHTSI)model was applied to simulate the seasonal changes of landfast ice along the Mawson Coast,East Antarctica,through ERA-Interim reanalysis data.Four ocean heat-flux(Fw)values(10,15,20 and 25 W m−2)were used in sensitivity experiments.The results showed that it is reasonable to simulate landfast ice using the HIGHTSI model,and the simulation of landfast ice thickness matched best well with field measurements when Fw was 20 W m^(−2).Then,2-D distributions of landfast ice from 2006 to 2018 were modeled by HIGHTSI with 2-D ERA-Interim reanalysis data in a 0.125°×0.125°cell grid as external forcing.The results showed that fast ice was thicker along the coast and thinner near open water,and usually reaches its maximal thickness in October,varying from 1.2 to 2.0 m through the study area.There was no statistical trend for the thickness during the study period.
基金supported by the National Natural Science Foundation of China(41976214 and 41925027)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021008).
文摘The presence or absence of sea ice introduces a substantial perturbation to surface-atmosphere energy exchanges.Comprehending the effect of varying sea ice cover on surface-atmosphere interactions is an important consideration for understanding the Arctic climate system.The recurring North Water Polynya(NOW)serves as a natural laboratory for isolating cloud responses to a rapid,near-step perturbation in sea ice.In this study,we employed high-resolution Arctic System Reanalysis version 2(ASRv2)data to estimate turbulent heat fluxes over the NOW and nearby sea ice(NSI)area between 2005/2006 and 2015/2016.The results indicate that the average turbulent heat fluxes in the polynya are about 87%and 86%higher than in the NSI area over the 10 years during the entire duration of the polynya and during polar night,respectively.Enhanced turbulent heat fluxes from the polynya tend to produce more low-level clouds.The relationship between the polynya and low cloud in winter was examined based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO).The low-cloud fraction(0-2 km)was about 7%-34%larger over the polynya than the NSI area,and the ice water content below 200 m was about 250%-413%higher over the former than the latter.The correlation between cloud fraction and turbulent heat fluxes in the polynya peaks around the altitude of 200-300 m.These results suggest that the NOW affects the Arctic boundary layer cloudiness and structure in wintertime.Furthermore,higher horizontal resolution reanalysis data can advance our understanding of the cloud-polynya response.
基金supported by the National Natural Science Foundation of China(41925027,42206248).
文摘In 2023,Antarctica experienced its lowest sea ice extent in the satellite era,with extreme polar events gaining widespread attention.Prydz Bay,where the Chinese Zhongshan Station is located,is the third largest embayment in Antarctica.Changes in sea ice,fast ice and polynyas directly affect local heat and mass exchanges between the ocean and atmosphere,as well as ecosystems and research activities.In 2023,substantial fast ice anomalies were observed in Prydz Bay:the extent of fast ice off Zhongshan Station(ZSFI)was anomalously low,while that within Barrier Bay(BaFI)was anomalously high.This study analysed the seasonal evolution and underlying main causes for the extreme conditions using ice charts,satellites and reanalysis data.From 2014 to 2022,the extent of zSFI typically increased during the cold season,reaching a maximum of(9.41±2.47)×10^(3) km^(2),whilst the Barrier Bay Polynya(BaP)persisted throughout this period.However,in 2023,ZSFI did not increase from June onwards,peaking at a maximum extent of only 5.49×10^(3) km^(2),and the BaP closed in mid-winter,leading to the formation of extensive BaFI.Air temperature and wind speed continuously dropped in July,and these conditions persisted for approximately 1 month,leading to the closure of BaP.However,zSFI did not expand further under these extreme meteorological conditions,indicating its independence from these factors.The limited expansion of ZSFI could be attributed to high ocean temperatures.Overall,this study provides valuable insights into the mechanisms driving extreme fast ice conditions.
