Loss of multiyear ice(MYI)is of great importance for Arctic climate and marine systems and can be monitored using active and passive microwave satellite data.In this paper,we describe an upgraded classification algori...Loss of multiyear ice(MYI)is of great importance for Arctic climate and marine systems and can be monitored using active and passive microwave satellite data.In this paper,we describe an upgraded classification algorithm using the data from the scatterometer and radiometer sensors onboard the Chinese Haiyang-2B(HY-2B)satellite to identify MYI and first-year ice(FYI).The proposed method was established based on K-means and fuzzy clustering(K-means+FC)and was used to focus on the transition zone where the ice condition is complex due to the highly commixing of MYI and FYI,leading to the high challenge for accurate classification of sea ice.The K-means algorithm was applied to preliminarily classify MYI using the combination of scatterometer and radiometer data,followed by applying fuzzy clustering to reclassify MYI in the transition zone.The HY-2B K-means+FC results were compared with the ice type products[including the Ocean and Sea Ice Satellite Application Facility(OSI SAF)sea ice type product and the Equal-Area Scalable Earth-Grid sea ice age dataset],and showed agreement in the time series of MYI extent.Intercomparisons in the transition zone indicated that the HY-2B K-means+FC results can identify more old ice than the OSI SAF product,but with an underestimation in identifying second-year ice.Comparisons between K-means and Kmeans+FC results were performed using regional ice charts and Sentinel-1 synthetic aperture radar(SAR)data.By adding fuzzy clustering,the MYI is more consistent with the ice charts,with the overall accuracy(OA)increasing by 0.9%–6.5%.Comparing against SAR images,it is suggested that more scattered MYI floes can be identified by fuzzy clustering,and the OA is increased by about 3%in middle freezing season and 7%–20%in early and late freezing season.展开更多
The North Water Polynya(NOW)is one of the largest and most productive polynyas in the Arctic.Compared to the surrounding sea ice,the combination of high winds and cold air,together with the thin ice or open water surf...The North Water Polynya(NOW)is one of the largest and most productive polynyas in the Arctic.Compared to the surrounding sea ice,the combination of high winds and cold air,together with the thin ice or open water surface of the NOW,produces large turbulent heat fluxes(THFs).The accurate estimation of these parameters requires high-resolution atmospheric data,which can be provided by the reanalysis products from different sources.In this study,we calculated the winter latent heat flux(LHF)and sensible heat flux(SHF)over the NOW and its surrounding sea ice area from 2005/2006 to 2015/2016 using high-resolution(15 km)Arctic System Reanalysis version 2(ASRv2)data and low-resolution(30 km)European Centre for Medium-Range Weather Forecasts ERA5 data.Results show that the LHF/SHF over the surrounding sea ice is about 82%/88%lower than over the NOW,as estimated using either dataset.Furthermore,within each area,the difference in the THFs estimated from the two datasets is small.The spatial distribution of the LHF/SHF estimated from both data sources is similar to that of sea ice concentration.The average LHF/SHF in the polynya obtained using ASRv2 data is only 5%/7%higher than that from the values obtained using ERA5 data.This is because the wind speed and air temperature from the ASRv2 data are higher than those of ERA5,and their effects on the THFs can cancel each other out.Furthermore,the estimated THFs do not necessarily improve with the refined resolution of ASRv2.展开更多
Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article ex...Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively.展开更多
Antarctic polynyas play an important role in regional atmosphere?ice?ocean interactions and are considered to help generate the global deep ocean conveyer belt.Polynyas therefore have a potential impact on the Earth’...Antarctic polynyas play an important role in regional atmosphere?ice?ocean interactions and are considered to help generate the global deep ocean conveyer belt.Polynyas therefore have a potential impact on the Earth’s climate in terms of the production of sea ice and high-salinity shelf water.In this study,we investigated the relationship between the area of the Terra Nova Bay polynya and the air temperature as well as the eastward and northward wind based on the ERA5 and ERAInterim reanalysis datasets and observations from automatic weather stations during the polar night.We examined the correlation between each factor and the polynya area under different temperature conditions.Previous studies have focused more on the effect of winds on the polynya,but the relationship between air temperature and the polynya area has not been fully investigated.Our study shows,eliminating the influence of winds,lower air temperature has a stronger positive correlation with the polynya area.The results show that the relationship between the polynya area and air temperature is more likely to be interactively influenced.As temperature drops,the relationship of the polynya area with air temperature becomes closer with increasing correlation coefficients.In the low temperature conditions,the correlation coefficients of the polynya area with air temperature are above 0.5,larger than that with the wind speed.展开更多
Arctic sea ice plays an essential role in regional and global climate by dynamic processes and feedbacks associated with its high reflectivity, thermal insulation especially in presence of snow cover, and brine reject...Arctic sea ice plays an essential role in regional and global climate by dynamic processes and feedbacks associated with its high reflectivity, thermal insulation especially in presence of snow cover, and brine rejection [1]. Both observations and model simulations show that Arctic sea ice extent has dramatically declined and thinned in the past few decades [2] in response to global warming and cumulative anthropogenic greenhouse gas(GHG)emissions [3,4].展开更多
In this study,sea ice thickness(SIT)and sea ice extent(SIE)in the Bohai Sea from 2000 to 2016 were investigated.A surface heat balance equation was applied to calculate SIT using ice surface temperatures estimated fro...In this study,sea ice thickness(SIT)and sea ice extent(SIE)in the Bohai Sea from 2000 to 2016 were investigated.A surface heat balance equation was applied to calculate SIT using ice surface temperatures estimated from the Moderate Resolution Imaging Spectroradiometer(MODIS)data with input from air temperature and wind speed from reanalyzing weather data.No trend was found in SIT during 2000–2016.The mean SIT and SIE during this period were 5.58±0.86 cm and 23×10^(3)±8×10^(3)km^(2),respectively.The largest SIT and SIE periods were observed during the second half of January and the first half of February,respectively.The Spearman correlation coefficient between mean ice thickness and average air temperature from 21 automatic weather stations around the Bohai Sea was–0.94(P<.005),and the coefficient between median ice extent and negative accumulated temperature was–0.503(P<.001).The rate of increase in air temperature around the Bohai Sea is 0.271℃per decade in winter for 1979–2016(P<.05),which is much lower than that in northern polar area(0.648℃per decade).This rate has not resulted in a decreasing trend in SIT and SIE for the past 16 years in the Bohai Sea.展开更多
The current climate change episode has impacted sea ice in the 2 polar regions differently.In the Arctic,remarkable sea ice extent and thickness declines have been observed with a stunning depletion rate of old ice.No...The current climate change episode has impacted sea ice in the 2 polar regions differently.In the Arctic,remarkable sea ice extent and thickness declines have been observed with a stunning depletion rate of old ice.No similar changes have been observed in the Antarctic.In this paper,the question posed in the title is addressed by reviewing findings retrieved from previous publications.The paper starts by identifying key geographic and climatic features and sea ice characteristics in the 2 polar regions and summarizing relevant recent records.It then proceeds by investigating interactions between sea ice and environmental factors,including atmospheric,oceanic,and dynamic aspects in each region,as well as the increasing number of icebergs in Antarctica.It is concluded that peculiarities of each polar region render the response to climate change differently.Researchers should not apply scenarios regarding the impacts of climate change on Arctic sea ice(i.e.,retreat)to Antarctic sea ice.Instead of asking why Antarctic sea ice has not responded to climate change in the same way as Arctic ice,a more reasonable question could be why Arctic ice changes are yielding an annual cycle that resembles that of Antarctic ice.Under current global warming conditions,old ice entrapment within the Arctic basin is relaxed.This could result in Arctic sea ice becoming predominantly seasonal during winter and almost completely melted during summer,which is the current state of Antarctic sea ice.展开更多
Antarctic tabular icebergs are important active components in the ice sheet-ice shelf-ocean system.Seafloor topography is the key factor that affects the drifting and grounding of icebergs,but it has not been fully in...Antarctic tabular icebergs are important active components in the ice sheet-ice shelf-ocean system.Seafloor topography is the key factor that affects the drifting and grounding of icebergs,but it has not been fully investigated.This study analyzes the impact of seafloor topography on the drifting and grounding of Antarctic tabular icebergs using Bedmap-2 datasets and iceberg route tracking data from Brigham Young University.The results highlight the following points.(1) The quantitative distributions of iceberg grounding events and the tracking points of grounded icebergs are mainly affected by iceberg draft and reach their peak values in sea water with depths between 200 m and 300 m.The peak tracking point number and linear velocity of free-drifting icebergs are found in the Antarctic Slope Front(water depth of approximately 500 m).(2) The area of possible grounding regions of small-scale icebergs calved from ice shelf fronts accounts for 28%of the sea area at water depths less than 2000 m outside the Antarctic coastline periphery(3.62 million km2).Their spatial distribution is mainly around East Antarctica and the Antarctic Peninsula.The area of possible grounding regions of large tabular icebergs with long axes larger than 18.5 km(in water depths of less than 800 m) accounts for 74%of the sea area.(3) The iceberg drifting velocity is positively correlated with ocean depth in areas where the depth is less than 2000 m(R=0.85,P<0.01).This result confirms the effect of water depth variations induced by seafloor topography fluctuations on iceberg drifting velocity.展开更多
基金the National Key Research and Development Program of China under contract No.2021YFC2803301the Fundamental Research Funds for the Central Universities,China under contract Nos 2042024kf0037 and 2042022dx0001the Natural Science Foundation of Wuhan under cocntract No.2024040701010030.
文摘Loss of multiyear ice(MYI)is of great importance for Arctic climate and marine systems and can be monitored using active and passive microwave satellite data.In this paper,we describe an upgraded classification algorithm using the data from the scatterometer and radiometer sensors onboard the Chinese Haiyang-2B(HY-2B)satellite to identify MYI and first-year ice(FYI).The proposed method was established based on K-means and fuzzy clustering(K-means+FC)and was used to focus on the transition zone where the ice condition is complex due to the highly commixing of MYI and FYI,leading to the high challenge for accurate classification of sea ice.The K-means algorithm was applied to preliminarily classify MYI using the combination of scatterometer and radiometer data,followed by applying fuzzy clustering to reclassify MYI in the transition zone.The HY-2B K-means+FC results were compared with the ice type products[including the Ocean and Sea Ice Satellite Application Facility(OSI SAF)sea ice type product and the Equal-Area Scalable Earth-Grid sea ice age dataset],and showed agreement in the time series of MYI extent.Intercomparisons in the transition zone indicated that the HY-2B K-means+FC results can identify more old ice than the OSI SAF product,but with an underestimation in identifying second-year ice.Comparisons between K-means and Kmeans+FC results were performed using regional ice charts and Sentinel-1 synthetic aperture radar(SAR)data.By adding fuzzy clustering,the MYI is more consistent with the ice charts,with the overall accuracy(OA)increasing by 0.9%–6.5%.Comparing against SAR images,it is suggested that more scattered MYI floes can be identified by fuzzy clustering,and the OA is increased by about 3%in middle freezing season and 7%–20%in early and late freezing season.
基金supported by the National Key Research and Development Program of China(Grant no.2024YFB3908004).
文摘The North Water Polynya(NOW)is one of the largest and most productive polynyas in the Arctic.Compared to the surrounding sea ice,the combination of high winds and cold air,together with the thin ice or open water surface of the NOW,produces large turbulent heat fluxes(THFs).The accurate estimation of these parameters requires high-resolution atmospheric data,which can be provided by the reanalysis products from different sources.In this study,we calculated the winter latent heat flux(LHF)and sensible heat flux(SHF)over the NOW and its surrounding sea ice area from 2005/2006 to 2015/2016 using high-resolution(15 km)Arctic System Reanalysis version 2(ASRv2)data and low-resolution(30 km)European Centre for Medium-Range Weather Forecasts ERA5 data.Results show that the LHF/SHF over the surrounding sea ice is about 82%/88%lower than over the NOW,as estimated using either dataset.Furthermore,within each area,the difference in the THFs estimated from the two datasets is small.The spatial distribution of the LHF/SHF estimated from both data sources is similar to that of sea ice concentration.The average LHF/SHF in the polynya obtained using ASRv2 data is only 5%/7%higher than that from the values obtained using ERA5 data.This is because the wind speed and air temperature from the ASRv2 data are higher than those of ERA5,and their effects on the THFs can cancel each other out.Furthermore,the estimated THFs do not necessarily improve with the refined resolution of ASRv2.
文摘Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively.
基金the National Natural Science Foundation of China(Grant No.41830536,Grant No.41676190,and Grant No.41941009)the Fundamental Research Funds for the Central Universities(Grant No.12500-312231103)The authors thank the University of Bremen for providing the AMSR-E,AMSR-2 and SSMIS SIC data,as well as the University of Wisconsin-Madison Automatic Weather Station Program(NSF Grant No.ANT-1543305)。
文摘Antarctic polynyas play an important role in regional atmosphere?ice?ocean interactions and are considered to help generate the global deep ocean conveyer belt.Polynyas therefore have a potential impact on the Earth’s climate in terms of the production of sea ice and high-salinity shelf water.In this study,we investigated the relationship between the area of the Terra Nova Bay polynya and the air temperature as well as the eastward and northward wind based on the ERA5 and ERAInterim reanalysis datasets and observations from automatic weather stations during the polar night.We examined the correlation between each factor and the polynya area under different temperature conditions.Previous studies have focused more on the effect of winds on the polynya,but the relationship between air temperature and the polynya area has not been fully investigated.Our study shows,eliminating the influence of winds,lower air temperature has a stronger positive correlation with the polynya area.The results show that the relationship between the polynya area and air temperature is more likely to be interactively influenced.As temperature drops,the relationship of the polynya area with air temperature becomes closer with increasing correlation coefficients.In the low temperature conditions,the correlation coefficients of the polynya area with air temperature are above 0.5,larger than that with the wind speed.
基金supported by the National Key Research and Development Program of China(2019YFC1509104)the National Natural Science Fundation of China for Distinguished Young Scholars(41925027)。
文摘Arctic sea ice plays an essential role in regional and global climate by dynamic processes and feedbacks associated with its high reflectivity, thermal insulation especially in presence of snow cover, and brine rejection [1]. Both observations and model simulations show that Arctic sea ice extent has dramatically declined and thinned in the past few decades [2] in response to global warming and cumulative anthropogenic greenhouse gas(GHG)emissions [3,4].
基金the Chinese Arctic and Antarctic Administration,National Natural Science Foundation of China(Grant Nos.41676176,41676182 and 41428603)Chinese Polar Environment Comprehensive Investigation and Assessment Program.
文摘In this study,sea ice thickness(SIT)and sea ice extent(SIE)in the Bohai Sea from 2000 to 2016 were investigated.A surface heat balance equation was applied to calculate SIT using ice surface temperatures estimated from the Moderate Resolution Imaging Spectroradiometer(MODIS)data with input from air temperature and wind speed from reanalyzing weather data.No trend was found in SIT during 2000–2016.The mean SIT and SIE during this period were 5.58±0.86 cm and 23×10^(3)±8×10^(3)km^(2),respectively.The largest SIT and SIE periods were observed during the second half of January and the first half of February,respectively.The Spearman correlation coefficient between mean ice thickness and average air temperature from 21 automatic weather stations around the Bohai Sea was–0.94(P<.005),and the coefficient between median ice extent and negative accumulated temperature was–0.503(P<.001).The rate of increase in air temperature around the Bohai Sea is 0.271℃per decade in winter for 1979–2016(P<.05),which is much lower than that in northern polar area(0.648℃per decade).This rate has not resulted in a decreasing trend in SIT and SIE for the past 16 years in the Bohai Sea.
基金supported by the National Natural Science Foundation of China(Grant No.42106225)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.311021008)the Natural Science Foundation of Guangdong Province,China(Grant No.2022A1515011545).
文摘The current climate change episode has impacted sea ice in the 2 polar regions differently.In the Arctic,remarkable sea ice extent and thickness declines have been observed with a stunning depletion rate of old ice.No similar changes have been observed in the Antarctic.In this paper,the question posed in the title is addressed by reviewing findings retrieved from previous publications.The paper starts by identifying key geographic and climatic features and sea ice characteristics in the 2 polar regions and summarizing relevant recent records.It then proceeds by investigating interactions between sea ice and environmental factors,including atmospheric,oceanic,and dynamic aspects in each region,as well as the increasing number of icebergs in Antarctica.It is concluded that peculiarities of each polar region render the response to climate change differently.Researchers should not apply scenarios regarding the impacts of climate change on Arctic sea ice(i.e.,retreat)to Antarctic sea ice.Instead of asking why Antarctic sea ice has not responded to climate change in the same way as Arctic ice,a more reasonable question could be why Arctic ice changes are yielding an annual cycle that resembles that of Antarctic ice.Under current global warming conditions,old ice entrapment within the Arctic basin is relaxed.This could result in Arctic sea ice becoming predominantly seasonal during winter and almost completely melted during summer,which is the current state of Antarctic sea ice.
基金supported by the National Key Research and Development Program of China(Grant No. 2016YFA0600103)the National Natural Science Foundation of China (Grant Nos.41406211,41476161,41676182 & 41676176)+3 种基金the National Basic Research Program of China(Grant No.2012CB957704)the KeyLaboratory Research Fund of the National Administration of Surveying, Mapping and Geoinformation of China(Grant No.201416)the Specialized Research Fund for the Doctoral Program of Higher Education(Grant No.20120003110030)the Project of International Cooperation and Exchanges CHINARE(Grant No.201611)
文摘Antarctic tabular icebergs are important active components in the ice sheet-ice shelf-ocean system.Seafloor topography is the key factor that affects the drifting and grounding of icebergs,but it has not been fully investigated.This study analyzes the impact of seafloor topography on the drifting and grounding of Antarctic tabular icebergs using Bedmap-2 datasets and iceberg route tracking data from Brigham Young University.The results highlight the following points.(1) The quantitative distributions of iceberg grounding events and the tracking points of grounded icebergs are mainly affected by iceberg draft and reach their peak values in sea water with depths between 200 m and 300 m.The peak tracking point number and linear velocity of free-drifting icebergs are found in the Antarctic Slope Front(water depth of approximately 500 m).(2) The area of possible grounding regions of small-scale icebergs calved from ice shelf fronts accounts for 28%of the sea area at water depths less than 2000 m outside the Antarctic coastline periphery(3.62 million km2).Their spatial distribution is mainly around East Antarctica and the Antarctic Peninsula.The area of possible grounding regions of large tabular icebergs with long axes larger than 18.5 km(in water depths of less than 800 m) accounts for 74%of the sea area.(3) The iceberg drifting velocity is positively correlated with ocean depth in areas where the depth is less than 2000 m(R=0.85,P<0.01).This result confirms the effect of water depth variations induced by seafloor topography fluctuations on iceberg drifting velocity.
