Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention ha...Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention has been paid to changes in the genesis locations of mesoscale eddies.Here,we provide evidence from three decades of satellite altimetry observations for the heterogeneity of the poleward shift of mesoscale activities,with the largest trend of~0.23°±0.05°(10 yr)^(-1) over the Atlantic sector and a moderate trend of~0.1°±0.03°(10 yr)^(-1) over the Indian sector,but no significant trend in the Pacific sector.The poleward shift of mesoscale eddies is associated with a southward shift of the local westerly winds while being constrained by the major topographies.As the poleward shift of westerly winds is projected to persist,the poleward oceanic heat flux from mesoscale eddies may influence future ice melt.展开更多
In November 1984,China launched its first expedition to the Southern Ocean and the Antarctic continent,culminating in the establishment of its first year-round research station—Great Wall Station—on the Antarctic Pe...In November 1984,China launched its first expedition to the Southern Ocean and the Antarctic continent,culminating in the establishment of its first year-round research station—Great Wall Station—on the Antarctic Peninsula in February 1985.Forty years later,in February 2024,China’s fifth research station,Qinling Station,commenced operations on Inexpress-ible Island near Terra Nova Bay.展开更多
Antarctic coastal polynyas play a vital role in atmosphere-ocean interactions and local ecosystems.This study investigates the interannual variability of springtime coastal polynyas over the Ross Sea based on satellit...Antarctic coastal polynyas play a vital role in atmosphere-ocean interactions and local ecosystems.This study investigates the interannual variability of springtime coastal polynyas over the Ross Sea based on satellite-retrieved sea-ice concentration(SIC)data from 1992 to 2021.Firstly,the springtime coastal polynya areas display large interannual variability as well as a positive trend of about 2000 km^(2)(10 yr)^(-1) over the 30 years.Secondly,based on composite analysis,in spring,we find that a deepened Amundsen Sea Low(ASL)induces stronger meridional winds over the eastern Ross Sea,leading to stronger sea-ice advection and expansion of coastal polynya areas.This is accompanied by more solar radiation absorption in early summer(about 16 W m^(2)),resulting in upper-ocean warming(~0.4℃)and significant sea-ice loss in late summer(~50%SIC).Additionally,the physical processes are validated by 500-year piControl simulations of a state-of-the-art Earth system model.Based on the same composite analysis,the results show that the sea-ice decline is consistent with the deepening of the ASL and the increase of the meridional sea-ice advection of the preceding spring,which is highly consistent with that of observations.This further confirms the circulations-polynyas-sea-ice physical linkages.Since the springtime ASL is strongly modulated by the tropical Pacific variability and the stratospheric polar vortex,changes in the polynya areas of the Ross Sea can be traced back to remote regions.展开更多
Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
Recent studies demonstrate that the Antarctic Ozone Hole has important influences on Antarctic sea ice.While most of these works have focused on effects associated with atmospheric and oceanic dynamic processes caused...Recent studies demonstrate that the Antarctic Ozone Hole has important influences on Antarctic sea ice.While most of these works have focused on effects associated with atmospheric and oceanic dynamic processes caused by stratospheric ozone changes,here we show that stratospheric ozone-induced cloud radiative effects also play important roles in causing changes in Antarctic sea ice.Our simulations demonstrate that the recovery of the Antarctic Ozone Hole causes decreases in clouds over Southern Hemisphere(SH)high latitudes and increases in clouds over the SH extratropics.The decrease in clouds leads to a reduction in downward infrared radiation,especially in austral autumn.This results in cooling of the Southern Ocean surface and increasing Antarctic sea ice.Surface cooling also involves ice-albedo feedback.Increasing sea ice reflects solar radiation and causes further cooling and more increases in Antarctic sea ice.展开更多
Seasonal minimum Antarctic sea ice extent(SIE)in 2022 hit a new record low since recordkeeping began in 1978 of 1.9 million km^(2) on 25 February,0.17 million km^(2) lower than the previous record low set in 2017.Sign...Seasonal minimum Antarctic sea ice extent(SIE)in 2022 hit a new record low since recordkeeping began in 1978 of 1.9 million km^(2) on 25 February,0.17 million km^(2) lower than the previous record low set in 2017.Significant negative anomalies in the Bellingshausen/Amundsen Seas,the Weddell Sea,and the western Indian Ocean sector led to the new record minimum.The sea ice budget analysis presented here shows that thermodynamic processes dominate sea ice loss in summer through enhanced poleward heat transport and albedo-temperature feedback.In spring,both dynamic and thermodynamic processes contribute to negative sea ice anomalies.Specifically,dynamic ice loss dominates in the Amundsen Sea as evidenced by sea ice thickness(SIT)change,while positive surface heat fluxes contribute most to sea ice melt in the Weddell Sea.展开更多
To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model(FIO-ESM)climate forecast system,satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic ...To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model(FIO-ESM)climate forecast system,satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic IceOcean Modeling and Assimilation System(PIOMAS)are assimilated into this system,using the method of localized error subspace transform ensemble Kalman filter(LESTKF).Five-year(2014–2018)Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation.Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent.All the biases of ice concentration,ice cover,ice volume,and ice thickness can be reduced dramatically through ice concentration and thickness assimilation.The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system.The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation.Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-toseasonal(S2 S)Prediction Project,FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast.Since sea ice thickness in the PIOMAS is updated in time,it is a good choice for data assimilation to improve sea ice prediction skills in the near-realtime Arctic sea ice seasonal prediction.展开更多
Accurate measurement of trace heavy metal mercury(Hg) in flue gas of coal-fired units is great significance for ecological and environmental protection.Mixed gas was used to simulate the actual flue gas of a power pla...Accurate measurement of trace heavy metal mercury(Hg) in flue gas of coal-fired units is great significance for ecological and environmental protection.Mixed gas was used to simulate the actual flue gas of a power plant in this study.A laser-induced breakdown spectroscopy(LIBS)system for Hg measurement in mixed gas was built to study the effect of mixed gas pressure,Hg concentration in mixed gas and delay time on Hg measurement.The experimental results show that the appropriate low mixed gas pressure can obtain high Hg signal intensity and signal to noise ratio.The Hg signal intensity and signal to noise ratio increased with the increase of Hg concentration in mixed gas.The Hg signal intensity and signal to noise ratio decreased with the increase in delay time.According to the above results,the optimized measurement conditions can be determined.Different Hg concentrations in mixed gas were quantitatively analyzed by the internal standard method and traditional calibration method respectively.The relative error of prediction of the test sample obtained by the internal standard method was within 11.11%.The relative error of prediction of the traditional calibration method was less than 14.54%.This proved that the internal standard method can improve the accuracy of quantitative analysis of Hg concentration in flue gas using LIBS.展开更多
The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica（off Zhongshan Station）during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was ...The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica（off Zhongshan Station）during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters（e.g., snow thickness, ice thickness, surface temperature, and air temperature） were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.展开更多
Tropical cyclone (TC) causes huge damage to lives and properties due to strong winds,storm surge,heavy rainfall and flooding(Peduzzi et al.,2012;Zhang et al.,2009).Climate model simulations suggested that the frequenc...Tropical cyclone (TC) causes huge damage to lives and properties due to strong winds,storm surge,heavy rainfall and flooding(Peduzzi et al.,2012;Zhang et al.,2009).Climate model simulations suggested that the frequency of TCs might increase during the 21st century,especially over the western North Pacific (Emanuel,2013).Climate changes tend to double the economic damages caused by natural disaster,i.e.,strong TCs.East Asia hit by TCs may suffer great damages in the future (Mendelsohn et al.,2012).展开更多
In recent decades,Arctic summer sea ice extent(SIE)has shown a rapid decline overlaid with large interannual variations,both of which are influenced by geopotential height anomalies over Greenland(GL-high)and the cent...In recent decades,Arctic summer sea ice extent(SIE)has shown a rapid decline overlaid with large interannual variations,both of which are influenced by geopotential height anomalies over Greenland(GL-high)and the central Arctic(CA-high).In this study,SIE along coastal Siberia(Sib-SIE)and Alaska(Ala-SIE)is found to account for about 65%and 21%of the Arctic SIE interannual variability,respectively.Variability in Ala-SIE is related to the GL-high,whereas variability in Sib-SIE is related to the CA-high.A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast,promoting ice-albedo feedback.A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation(DLR)along the Siberian coast.The years 2012 and 2020 with minimum recorded ASIE are used as examples.Compared to climatology,summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast,while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast.In 2012,the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation,amplifying ice-albedo feedback there;while in 2020,the opposite occurs with an increase in cloud cover along the Alaskan coast,resulting in a slight increase in sea ice there.Along the Siberian coast,increased DLR in 2020 plays a dominant role in sea ice loss,and increased cloud cover and water vapor both contribute to the increased DLR.展开更多
Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled ...Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.展开更多
The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the refo...The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory(Conv LSTM)Network. The reforecast experiments demonstrate that Conv LSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.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
Contents of fly ash are important factors for the operation of coal-fired plants. Real-time monitoring of coal and fly ash such as unburned carbon in fly ash can be an indicator of the combustion conditions. Because o...Contents of fly ash are important factors for the operation of coal-fired plants. Real-time monitoring of coal and fly ash such as unburned carbon in fly ash can be an indicator of the combustion conditions. Because of the strong signal intensity and the relative simplicity of the LIBS (Laser- Induced Breakdown Spectroscopy) technique, LIBS can be applicable for real-time composition measurement of coal and fly ash. This research presented here focused on the clarification of the effects of plasma temperature and coexisting materials on quantitative measurement of fly ash contents. Quantitative capability of LIBS was improved using the proposed plasma temperature correction method. The CO2 effect was also discussed to accurately evaluate unburned carbon in fly ash in exhausts. Using the results shown in this study, quantitative measurement of fly ash contents has been improved for wider applications of LIBS to practical fields.展开更多
Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated...Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.展开更多
The Antarctic,including the continent of Antarctica and the Southern Ocean,is a critically important part of the Earth system.Research in Antarctic meteorology and climate has always been a challenging endeavor.Studyi...The Antarctic,including the continent of Antarctica and the Southern Ocean,is a critically important part of the Earth system.Research in Antarctic meteorology and climate has always been a challenging endeavor.Studying and predicting weather patterns in the Antarctic are important for understanding their role in local-to-global processes and facilitating field studies and logistical operations in the Antarctic(e.g.,Walsh et al.,2018).Studies of climate change in the Antarctic are comparatively neglected compared to those of the Arctic.However,significant climate changes have occurred in the Antarctic in the past several decades,i.e.,a strong warming over the Antarctic Peninsula even with a recent minor cooling,a deepening of the Amundsen Sea low,a rapid warming of the upper ocean north of the circumpolar current,an increase of Antarctic sea ice since the late 1970s followed by a recent rapid decrease,and an accelerated ice loss from the Antarctic ice shelf/sheet since the late 1970s(e.g.,Turner et al.,2005;Raphael et al.,2016;Sallée,2018;Parkinson,2019;Rignot et al.,2019).Investigating recent climate change in the Antarctic and the underlying mechanisms are important for predicting future climate change and providing information to policymakers.展开更多
On 15 September 2020,the Arctic sea-ice extent(SIE)reached its annual minimum,which,based on data from the National Snow and Ice Data Center(NSIDC,2020a),was about 3.74 million km^(2)(1.44 million square miles).This v...On 15 September 2020,the Arctic sea-ice extent(SIE)reached its annual minimum,which,based on data from the National Snow and Ice Data Center(NSIDC,2020a),was about 3.74 million km^(2)(1.44 million square miles).This value was about 40%less than the climate average(~6.27 million km^(2))during 1980–2010.It was second only to the record low(3.34 million km^(2))set on 16 September 2012,but significantly smaller than the previous second-lowest(4.145 million km^(2),set on 7 September 2016)and third-lowest(4.147 million km^(2),set on 14 September 2007)values,making 2020 the second-lowest SIE year of the satellite era(42 years of data).展开更多
The first Southern Ocean Observing System （SOOS） Asian Workshop was successfully held in Shanghai, China in May 2013, attracting over 40 participants from six Asian nations and widening exposure to the objectives an...The first Southern Ocean Observing System （SOOS） Asian Workshop was successfully held in Shanghai, China in May 2013, attracting over 40 participants from six Asian nations and widening exposure to the objectives and plans of SOOS. The workshop was organized to clarify Asian research activities currently taking place in the Southern Ocean and to discuss, amongst other items, the potential for collaborative efforts with and between Asian countries in $OOS-related activities. The workshop was an important mechanism to initiate discussion, understanding and collaborative avenues in the Asian domain of SOOS beyond current established eflbrts. Here we present some of the major outcomes of the workshop covering the principle themes of SOOS and attempt to provide a way forward to achieve a more integrated research community, enhance data collection and quality, and guide scientific strategy in the Southern Ocean.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42230405,42006029)Science and Technology Plan of Liaoning Province(2024JH2/102400061)+1 种基金Dalian Science and Technology Innovation Fund(2024JJ11PT007)Dalian Science and Technology Pro-gram for Innovation Talents of Dalian(2022RJ06).
文摘Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention has been paid to changes in the genesis locations of mesoscale eddies.Here,we provide evidence from three decades of satellite altimetry observations for the heterogeneity of the poleward shift of mesoscale activities,with the largest trend of~0.23°±0.05°(10 yr)^(-1) over the Atlantic sector and a moderate trend of~0.1°±0.03°(10 yr)^(-1) over the Indian sector,but no significant trend in the Pacific sector.The poleward shift of mesoscale eddies is associated with a southward shift of the local westerly winds while being constrained by the major topographies.As the poleward shift of westerly winds is projected to persist,the poleward oceanic heat flux from mesoscale eddies may influence future ice melt.
文摘In November 1984,China launched its first expedition to the Southern Ocean and the Antarctic continent,culminating in the establishment of its first year-round research station—Great Wall Station—on the Antarctic Peninsula in February 1985.Forty years later,in February 2024,China’s fifth research station,Qinling Station,commenced operations on Inexpress-ible Island near Terra Nova Bay.
基金supported by the National Key R&D Program of China(Grant No.2021YFC2802504)the National Outstanding Youth Grant(Grant No.41925027)+1 种基金the National Natural Science Foundation of China(Grant No.42206251)the Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.311021008).
文摘Antarctic coastal polynyas play a vital role in atmosphere-ocean interactions and local ecosystems.This study investigates the interannual variability of springtime coastal polynyas over the Ross Sea based on satellite-retrieved sea-ice concentration(SIC)data from 1992 to 2021.Firstly,the springtime coastal polynya areas display large interannual variability as well as a positive trend of about 2000 km^(2)(10 yr)^(-1) over the 30 years.Secondly,based on composite analysis,in spring,we find that a deepened Amundsen Sea Low(ASL)induces stronger meridional winds over the eastern Ross Sea,leading to stronger sea-ice advection and expansion of coastal polynya areas.This is accompanied by more solar radiation absorption in early summer(about 16 W m^(2)),resulting in upper-ocean warming(~0.4℃)and significant sea-ice loss in late summer(~50%SIC).Additionally,the physical processes are validated by 500-year piControl simulations of a state-of-the-art Earth system model.Based on the same composite analysis,the results show that the sea-ice decline is consistent with the deepening of the ASL and the increase of the meridional sea-ice advection of the preceding spring,which is highly consistent with that of observations.This further confirms the circulations-polynyas-sea-ice physical linkages.Since the springtime ASL is strongly modulated by the tropical Pacific variability and the stratospheric polar vortex,changes in the polynya areas of the Ross Sea can be traced back to remote regions.
基金jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金the National Key R&D Program of China(2018YFA0605901)Y.XIA and Y.Y.HU are supported by the National Natural Science Foundation of China(NSFC)(Grant Nos.41530423 and 41761144072)+4 种基金Y.XIA is supported by the China Postdoctoral Science Foundation funded project(Grant No.2018M630027)Y.HUANG is supported by the Discovery Program of the Natural Sciences and Engineering Council of Canada(Grant No.RGPIN 418305-13)the Team Research Project Program of the Fonds de RechercheNature et Technologies of Quebec(Grant No.PR-190145)J.P.LIU is supported by the Climate Observation and Earth System Science Divisions,Climate Program Office,NOAA,U.S.Department of Commerce(Grant Nos.NA15OAR4310163 and NA14OAR4310216)J.T.LIN is supported by the NSFC(Grant No.41775115)and the 973 program(Grant No.2014CB441303).
文摘Recent studies demonstrate that the Antarctic Ozone Hole has important influences on Antarctic sea ice.While most of these works have focused on effects associated with atmospheric and oceanic dynamic processes caused by stratospheric ozone changes,here we show that stratospheric ozone-induced cloud radiative effects also play important roles in causing changes in Antarctic sea ice.Our simulations demonstrate that the recovery of the Antarctic Ozone Hole causes decreases in clouds over Southern Hemisphere(SH)high latitudes and increases in clouds over the SH extratropics.The decrease in clouds leads to a reduction in downward infrared radiation,especially in austral autumn.This results in cooling of the Southern Ocean surface and increasing Antarctic sea ice.Surface cooling also involves ice-albedo feedback.Increasing sea ice reflects solar radiation and causes further cooling and more increases in Antarctic sea ice.
基金supported by the National Natural Science Foundation of China(Grant Nos.41941009,41922044,and 42006191)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2020B1515020025)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.19lgzd07)the Norges Forskningsråd(Grant no.328886).
文摘Seasonal minimum Antarctic sea ice extent(SIE)in 2022 hit a new record low since recordkeeping began in 1978 of 1.9 million km^(2) on 25 February,0.17 million km^(2) lower than the previous record low set in 2017.Significant negative anomalies in the Bellingshausen/Amundsen Seas,the Weddell Sea,and the western Indian Ocean sector led to the new record minimum.The sea ice budget analysis presented here shows that thermodynamic processes dominate sea ice loss in summer through enhanced poleward heat transport and albedo-temperature feedback.In spring,both dynamic and thermodynamic processes contribute to negative sea ice anomalies.Specifically,dynamic ice loss dominates in the Amundsen Sea as evidenced by sea ice thickness(SIT)change,while positive surface heat fluxes contribute most to sea ice melt in the Weddell Sea.
基金The National Key Research and Development Program of China under contract Nos 2018YFC1407205 and2018YFA0605901the Basic Scientific Fund for National Public Research Institute of China(ShuXingbei Young Talent Program)under contract No.2019S06+1 种基金the National Natural Science Foundation of China under contract Nos 41821004,42022042 and 41941012the China-Korea Cooperation Project on Northwestern Pacific Climate Change and its Prediction。
文摘To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model(FIO-ESM)climate forecast system,satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic IceOcean Modeling and Assimilation System(PIOMAS)are assimilated into this system,using the method of localized error subspace transform ensemble Kalman filter(LESTKF).Five-year(2014–2018)Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation.Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent.All the biases of ice concentration,ice cover,ice volume,and ice thickness can be reduced dramatically through ice concentration and thickness assimilation.The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system.The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation.Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-toseasonal(S2 S)Prediction Project,FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast.Since sea ice thickness in the PIOMAS is updated in time,it is a good choice for data assimilation to improve sea ice prediction skills in the near-realtime Arctic sea ice seasonal prediction.
基金supported by National Natural Science Foundation of China (No. 51506171)。
文摘Accurate measurement of trace heavy metal mercury(Hg) in flue gas of coal-fired units is great significance for ecological and environmental protection.Mixed gas was used to simulate the actual flue gas of a power plant in this study.A laser-induced breakdown spectroscopy(LIBS)system for Hg measurement in mixed gas was built to study the effect of mixed gas pressure,Hg concentration in mixed gas and delay time on Hg measurement.The experimental results show that the appropriate low mixed gas pressure can obtain high Hg signal intensity and signal to noise ratio.The Hg signal intensity and signal to noise ratio increased with the increase of Hg concentration in mixed gas.The Hg signal intensity and signal to noise ratio decreased with the increase in delay time.According to the above results,the optimized measurement conditions can be determined.Different Hg concentrations in mixed gas were quantitatively analyzed by the internal standard method and traditional calibration method respectively.The relative error of prediction of the test sample obtained by the internal standard method was within 11.11%.The relative error of prediction of the traditional calibration method was less than 14.54%.This proved that the internal standard method can improve the accuracy of quantitative analysis of Hg concentration in flue gas using LIBS.
基金supported by the National Natural Science Foundation of China(Grant Nos.41006115 and 41376005)the Chinese Polar Environmental Comprehensive Investigation and Assessment Programthe Chinese National Key Basic Research Project(2011CB309704)
文摘The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica（off Zhongshan Station）during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters（e.g., snow thickness, ice thickness, surface temperature, and air temperature） were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.
基金The National Key R&D Program of China under contract No.2018YFA0605901the National Natural Science Foundation of China under contract No.41676185the Joint PhD Program of China Scholarship Council(CSC)。
文摘Tropical cyclone (TC) causes huge damage to lives and properties due to strong winds,storm surge,heavy rainfall and flooding(Peduzzi et al.,2012;Zhang et al.,2009).Climate model simulations suggested that the frequency of TCs might increase during the 21st century,especially over the western North Pacific (Emanuel,2013).Climate changes tend to double the economic damages caused by natural disaster,i.e.,strong TCs.East Asia hit by TCs may suffer great damages in the future (Mendelsohn et al.,2012).
基金the National Key Research and Development Program of China(Grant Nos.2021YFC2802504 and 2019YFC1509104)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.311021008).
文摘In recent decades,Arctic summer sea ice extent(SIE)has shown a rapid decline overlaid with large interannual variations,both of which are influenced by geopotential height anomalies over Greenland(GL-high)and the central Arctic(CA-high).In this study,SIE along coastal Siberia(Sib-SIE)and Alaska(Ala-SIE)is found to account for about 65%and 21%of the Arctic SIE interannual variability,respectively.Variability in Ala-SIE is related to the GL-high,whereas variability in Sib-SIE is related to the CA-high.A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast,promoting ice-albedo feedback.A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation(DLR)along the Siberian coast.The years 2012 and 2020 with minimum recorded ASIE are used as examples.Compared to climatology,summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast,while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast.In 2012,the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation,amplifying ice-albedo feedback there;while in 2020,the opposite occurs with an increase in cloud cover along the Alaskan coast,resulting in a slight increase in sea ice there.Along the Siberian coast,increased DLR in 2020 plays a dominant role in sea ice loss,and increased cloud cover and water vapor both contribute to the increased DLR.
基金supported by the NOAA Climate Program Office(Grant No.NA15OAR4310163)the National Key R&D Program of China(Grant Nos.2018YFA0605904 and 2018YFA0605901)the National Natural Science Foundation of China(Grant No.41676185)。
文摘Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.
基金supported by the National Key R&D Program of China (Grant No.2022YFE0106300)the National Natural Science Foundation of China (Grant Nos.41941009 and 42006191)+2 种基金the China Postdoctoral Science Foundation (Grant No.2023M741526)the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant Nos.SML2022SP401 and SML2023SP207)the Program of Marine Economy Development Special Fund under Department of Natural Resources of Guangdong Province (Grant No.GDNRC [2022]18)。
文摘The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory(Conv LSTM)Network. The reforecast experiments demonstrate that Conv LSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.
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.
文摘Contents of fly ash are important factors for the operation of coal-fired plants. Real-time monitoring of coal and fly ash such as unburned carbon in fly ash can be an indicator of the combustion conditions. Because of the strong signal intensity and the relative simplicity of the LIBS (Laser- Induced Breakdown Spectroscopy) technique, LIBS can be applicable for real-time composition measurement of coal and fly ash. This research presented here focused on the clarification of the effects of plasma temperature and coexisting materials on quantitative measurement of fly ash contents. Quantitative capability of LIBS was improved using the proposed plasma temperature correction method. The CO2 effect was also discussed to accurately evaluate unburned carbon in fly ash in exhausts. Using the results shown in this study, quantitative measurement of fly ash contents has been improved for wider applications of LIBS to practical fields.
基金supported by the National Key R&D Program of China(Grant No.2022YFE0106300)the National Natural Science Foundation of China(Grant Nos.42105052 and 42106220)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2020B1515020025)the fundamental research funds for the Norges Forskningsråd(Grant No.328886).
文摘Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.
基金the National Key R&D Program of China(Grant No.2018YFA0605901).
文摘The Antarctic,including the continent of Antarctica and the Southern Ocean,is a critically important part of the Earth system.Research in Antarctic meteorology and climate has always been a challenging endeavor.Studying and predicting weather patterns in the Antarctic are important for understanding their role in local-to-global processes and facilitating field studies and logistical operations in the Antarctic(e.g.,Walsh et al.,2018).Studies of climate change in the Antarctic are comparatively neglected compared to those of the Arctic.However,significant climate changes have occurred in the Antarctic in the past several decades,i.e.,a strong warming over the Antarctic Peninsula even with a recent minor cooling,a deepening of the Amundsen Sea low,a rapid warming of the upper ocean north of the circumpolar current,an increase of Antarctic sea ice since the late 1970s followed by a recent rapid decrease,and an accelerated ice loss from the Antarctic ice shelf/sheet since the late 1970s(e.g.,Turner et al.,2005;Raphael et al.,2016;Sallée,2018;Parkinson,2019;Rignot et al.,2019).Investigating recent climate change in the Antarctic and the underlying mechanisms are important for predicting future climate change and providing information to policymakers.
基金This work was supported by the National Key R&D Program of China[grant number 2018YFA0605901]the National Natural Science Foundation of China[grant numbers 41861144016 and 42011530082].
文摘On 15 September 2020,the Arctic sea-ice extent(SIE)reached its annual minimum,which,based on data from the National Snow and Ice Data Center(NSIDC,2020a),was about 3.74 million km^(2)(1.44 million square miles).This value was about 40%less than the climate average(~6.27 million km^(2))during 1980–2010.It was second only to the record low(3.34 million km^(2))set on 16 September 2012,but significantly smaller than the previous second-lowest(4.145 million km^(2),set on 7 September 2016)and third-lowest(4.147 million km^(2),set on 14 September 2007)values,making 2020 the second-lowest SIE year of the satellite era(42 years of data).
基金hosted and sponsored by the Polar Research Institute of China (PRIC), with additional sponsorship by the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), the World Climate Research Programme (WCRP) "Climate and the Cryosphere" project (CliC), SCAR and the Scientific Committee on Oceanic Research (SCOR). We thank Alexander Klepikov, Hyoung Chul Shin, Katsuro Katsumata for providing the information on ship tracks. The conveners would like to thank the efforts by all participants, in particular the presenters, in making the first SOOS Asia Workshop a successful forum by which to highlight the extensive Asian research activities in the Southern Ocean and discuss a way forward in driving collaboration and integration with SOOS, as well as the greater international community. SOOS would like to recognize the support of the Institute for Marine and Antarctic Studies (IMAS, University of Tasmania) in hosting the SOOS International Project Office, and the sponsorship of the office by numerous international organizations (see www.soos.aq/index.php/ about-us/sponsors)
文摘The first Southern Ocean Observing System （SOOS） Asian Workshop was successfully held in Shanghai, China in May 2013, attracting over 40 participants from six Asian nations and widening exposure to the objectives and plans of SOOS. The workshop was organized to clarify Asian research activities currently taking place in the Southern Ocean and to discuss, amongst other items, the potential for collaborative efforts with and between Asian countries in $OOS-related activities. The workshop was an important mechanism to initiate discussion, understanding and collaborative avenues in the Asian domain of SOOS beyond current established eflbrts. Here we present some of the major outcomes of the workshop covering the principle themes of SOOS and attempt to provide a way forward to achieve a more integrated research community, enhance data collection and quality, and guide scientific strategy in the Southern Ocean.
