Assessments of the Arctic amplification and the changes in the Arctic sea surface

Although dramatic warming is occurring in the Arctic,it is incomplete to provide an estimate to the Arctic Amplification(AA)based only on the surface air temperature(SAT)obtained at a few land stations.In this study,a comprehensive evaluation has been made with sea surface temperature(SST)and SAT from the Arctic land and ocean.Additionally,the variations of sea surface parameters were analyzed for a better understanding of the updated Arctic changes in recent years.AA was underestimated by 4.3%when only considering the SAT.During 1982—2018,the Arctic and global SSTs increased dramatically after 2002 with a near-synchronous trend in 2011—2018.Sea ice extent exhibited negative anomalies in September and March after 2002,which were more significant in September.The warming was more remarkable in March than that in September,and the negative SST anomaly entirely disappeared in March in the last two years(2017—2018).However,sea ice thickness and snow depth in September increased with the positive anomaly in the southwestern Arctic Ocean.

Spatio-temporal variations of Arctic amplification and their linkage with the Arctic oscillation

The Arctic near-surface air temperatures are increasing more than twice as fast as the global average-a feature known as Arctic amplification （AA）. A modified AA index is constructed in this paper to emphasize the contrast of warming rate between polar and mid-latitude regions, as well as the spatial and temporal characteristics of AA and their influence on atmospheric circulation over the Northern Hemisphere. Results show that AA has a pronounced annual cycle. The positive or negative phase activities are the strongest in autumn and winter, the weakest in summer. After experiencing a remarkable decadal shift from negative to positive phase in the early global warming hiatus period, the AA has entered into a state of being enlarged continuously, and the decadal regime shift of AA in about 2002 is affected mainly by decadal shift in autumn. In terms of spatial distribution, AA has maximum warming near the surface in almost all seasons except in summer. Poleward of 20~N, AA in autumn has a significant influence on the atmospheric circulation in the following winter. The reason may be that the autumn AA increases the amplitude of planetary waves, slows the wave speeds and weakens upper-level zonal winds through the thermal wind relation, thus influencing surface air temperature in the following winter. The AA correlates to negative phase of the Arctic oscillation （AO） and leads AO by 0-3 months within the period 1979-2002. However, weaker relationship between them is indistinctive after the decadal shift of AA.

Influence of Surface Types on the Seasonality and Inter-Model Spread of Arctic Amplification in CMIP6

A robust phenomenon termed the Arctic Amplification(AA)refers to the stronger warming taking place over the Arctic compared to the global mean.The AA can be confirmed through observations and reproduced in climate model simulations and shows significant seasonality and inter-model spread.This study focuses on the influence of surface type on the seasonality of AA and its inter-model spread by dividing the Arctic region into four surface types:ice-covered,ice-retreat,ice-free,and land.The magnitude and inter-model spread of Arctic surface warming are calculated from the difference between the abrupt-4×CO_(2)and pre-industrial experiments of 17 CMIP6 models.The change of effective thermal inertia(ETI)in response to the quadrupling of CO_(2) forcing is the leading mechanism for the seasonal energy transfer mechanism,which acts to store heat temporarily in summer and then release it in winter.The ETI change is strongest over the ice-retreat region,which is also responsible for the strongest AA among the four surface types.The lack of ETI change explains the nearly uniform warming pattern across seasons over the ice-free(ocean)region.Compared to other regions,the ice-covered region shows the maximum inter-model spread in JFM,resulting from a stronger inter-model spread in the oceanic heat storage term.However,the weaker upward surface turbulent sensible and latent heat fluxes tend to suppress the inter-model spread.The relatively small inter-model spread during summer is caused by the cancellation of the inter-model spread in ice-albedo feedback with that in the oceanic heat storage term.

Role of Ocean Dynamics in the Seasonal Hadley Cell:A Response to Idealized Arctic Amplification

How atmospheric and oceanic circulations respond to Arctic warming at different timescales are revealed with idealized numerical simulations.Induced by local forcing and feedback,Arctic warming appears and leads to sea-ice melting.Deep-water formation is inhibited,which weakens the Atlantic Meridional Overturning Circulation(AMOC).The flow and temperature in the upper layer does not respond to the AMOC decrease immediately,especially at mid-low latitudes.Thus,nearly uniform surface warming in mid-low latitudes enhances(decreases)the strength(width)of the Hadley cell(HC).With the smaller northward heat carried by the weaker AMOC,the Norwegian Sea cools significantly.With strong warming in Northern Hemisphere high latitudes,the long-term response triggers the“temperature-wind-gyre-temperature”cycle,leading to colder midlatitudes,resulting in strong subsidence and Ferrel cell enhancement,which drives the HC southward.With weaker warming in the tropics and stronger warming at high latitudes,there is a stronger HC with decreased width.A much warmer Southern Hemisphere appears due to a weaker AMOC that also pushes the HC southward.Our idealized model results suggest that the HC strengthens under both warming conditions,as tropical warming determines the strength of the HC convection.Second,extreme Arctic warming led by artificially reduced surface albedo decreases the meridional temperature gradient between high and low latitudes,which contracts the HC.Third,a warmer mid-high latitude in the Northern(Southern)Hemisphere due to surface albedo feedback(weakened AMOC)in our experiments pushes the HC northward(southward).In most seasons,the HC exhibits the same trend as that described above.

Impact of Arctic amplification on East Asian winter climate

1.IntroductionThe Arctic region warms about twice as much as the global average,and this so-called Arctic amplification（AA）might increase the moisture flux towards Siberia（Cohen et al.2014）.Furthermore,because of strong radiative cooling over Siberia in winter,AA might enhance the snowfall in that region and reinforce cold spells in East Asia（Wu,Su,and Zhang 2011）.

The historical to future linkage of Arctic amplification on extreme precipitation over the Northern Hemisphere using CMIP5 and CMIP6 models

Arctic warming played a dominant role in recent occurrences of extreme events over the Northern Hemisphere,but climate models cannot accurately simulate the relationship.Here a significant positive correlation(0.33-0.95)between extreme precipitation and Arctic amplification(AA)is found using observations and CMIP5/6 multi-model ensembles.However,CMIP6 models are superior to CMIP5 models in simulating the temporal evolution of extreme precipitation and AA.According to 14 optimal CMIP6 models,the maximum latitude of planetary waves and the strength of Northern Hemisphere annular mode(NAM)will increase with increasing AA,contributing to increased extreme precipitation over the Northern Hemisphere.Under the Shared Socioeconomic Pathway SSP5-8.5,AA is expected to increase by 0.85℃ per decade while the maximum latitude of planetary waves will increase by 2.82°per decade.Additionally,the amplitude of the NAM will increase by 0.21 hPa per decade,contributing to a rise in extreme precipitation of 1.17% per decade for R95pTOT and 0.86% per decade for R99pTOT by 2100.

Changes in polar amplification in response to increasing warming in CMIP6

The climate in polar regions has experienced an obvious warming amplification due to global warming.In this study,the changes in polar amplification are analyzed in response to feedback mechanisms(including Planck,lapse rate,cloud,water vapor,albedo feedback,CO_(2) radiative forcing,ocean heat uptake,and atmospheric heat transport)under three warming scenarios in CMIP6—namely,SSP1-2.6,SSP2-4.5,and SSP5-8.5.The results show that,by quantifying the warming contribution of different feedback mechanisms to surface air temperature with the“radiative kernel”method,Arctic amplification(AA)is stronger than Antarctic amplification(ANA),mostly resulting from the lapse rate feedback,followed by the albedo and Planck feedbacks.Furthermore,ocean heat uptake causes stronger polar warming in winter than in summer.During winter,the lapse rate feedback causes a larger AA than ANA.The intermodel spread for both AA and ANA decrease with increasing strength of global warming from SSP1-2.6 to SSP5-8.5,and the dominant mechanisms are the Planck,lapse rate,albedo,and ocean heat uptake feedbacks.These findings help to enhance our understanding of polar regions’responses to different strengths of global warming.

Advances in understanding the mechanisms of Arctic amplification

The near-surface temperatures in the Arctic are increasing at more than twice the global average rate,a phenomenon known as Arctic amplification(AA).In recent years,numerous studies using ground-based and satellite observations,along with model simulations,have explored the potential mechanisms behind AA,offering a variety of observational evidence and theoretical explanations.Although the understanding of AA drivers has improved,significant uncertainties remain in quantifying the contributions of different influential factors.On the basis of the latest research,this article thoroughly examines the factors driving rapid warming in the Arctic,including local feedbacks,atmospheric circulation,ocean currents,and aerosols,and compares quantitative results across studies.The analysis highlights the complex interplay of multiple factors contributing to AA,with no clear consensus on the relative contributions of each driver.Finally,the article underscores key challenges in current research,emphasizing the need for more reliable observational data,a deeper understanding of AA mechanisms,improved model parameterizations,and the disentanglement of interactions among driving factors,all of which are essential for future investigations.

The Warm Arctic-Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern Hemisphere.However,divergent results between model and observational studies of the WACE still remain.This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the models.The results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single models.Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern well.This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)region.Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central Eurasia.Therefore,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

Characteristics and spatial distribution of strong warming events in the central Arctic(2000-2019)

Arctic amplification in the context of global warming has received considerable attention,and mechanisms such as ice-albedo feedback and extratropical cyclone activity have been proposed to explain such abnormal warming.Since 2000,several short-term episodes of significant temperature rise have been observed in the Arctic;however,long-duration warming events in the central Arctic are less common and lack comprehensive research.Previous studies identified that amplified Rossbywaves could connect Arctic warming with extreme weather events in mid-latitude regions,and thus the recent increase in the frequency of mid-latitude extreme weather is also a subject of intensive research.With consideration of temperature anomalies,this study defined a continuous warming process as a warming event and selected strong warming events based on duration.Analysis of National Centers for Environmental Prediction Reanalysis-2 surface air temperature data found that nine strong warming events occurred during 2000-2019,which could be categorized into three types based on the area of warming.This study also investigated the relation between strong warming events and sea ice concentration reduction,sudden stratospheric warming,and extratropical cyclone activities.After full consideration and comparison,we believe that strong warming events in the central Arctic are induced primarily by continuous transport of warm air from mid-latitude ocean areas.

Extreme Cold Events from East Asia to North America in Winter 2020/21:Comparisons,Causes,and Future Implications

Three striking and impactful extreme cold weather events successively occurred across East Asia and North America during the mid-winter of 2020/21.These events open a new window to detect possible underlying physical processes.The analysis here indicates that the occurrences of the three events resulted from integrated effects of a concurrence of anomalous thermal conditions in three oceans and interactive Arctic-lower latitude atmospheric circulation processes,which were linked and influenced by one major sudden stratospheric warming(SSW).The North Atlantic warm blob initiated an increased poleward transient eddy heat flux,reducing the Barents-Kara seas sea ice over a warmed ocean and disrupting the stratospheric polar vortex(SPV)to induce the major SSW.The Rossby wave trains excited by the North Atlantic warm blob and the tropical Pacific La Nina interacted with the Arctic tropospheric circulation anomalies or the tropospheric polar vortex to provide dynamic settings,steering cold polar air outbreaks.The long memory of the retreated sea ice with the underlying warm ocean and the amplified tropospheric blocking highs from the midlatitudes to the Arctic intermittently fueled the increased transient eddy heat flux to sustain the SSW over a long time period.The displaced or split SPV centers associated with the SSW played crucial roles in substantially intensifying the tropospheric circulation anomalies and moving the jet stream to the far south to cause cold air outbreaks to a rarely observed extreme state.The results have significant implications for increasing prediction skill and improving policy decision making to enhance resilience in“One Health,One Future”.

Surface Temperature Changes Projected by FGOALS Models under Low Warming Scenarios in CMIP5 and CMIP6

To meet the low warming targets proposed in the 2015 Paris Agreement,substantial reduction in carbon emissions is needed in the future.It is important to know how surface climates respond under low warming targets.The present study investigates the surface temperature changes under the low-forcing scenario of Representative Concentration Pathways(RCP2.6)and its updated version(Shared Socioeconomic Pathways,SSP1-2.6)by the Flexible Global Ocean-Atmosphere-Land System(FGOALS)models participating in phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6,respectively).In both scenarios,radiative forcing(RF)first increases to a peak of 3 W m^−2 around 2045 and then decreases to 2.6 W m^−2 by 2100.Global mean surface air temperature rises in all FGOALS models when RF increases(RF increasing stage)and declines or holds nearly constant when RF decreases(RF decreasing stage).The surface temperature change is distinct in its sign and magnitude between the RF increasing and decreasing stages over the land,Arctic,North Atlantic subpolar region,and Southern Ocean.Besides,the regional surface temperature change pattern displays pronounced model-to-model spread during both the RF increasing and decreasing stages,mainly due to large intermodel differences in climatological surface temperature,ice-albedo feedback,natural variability,and Atlantic Meridional Overturning Circulation change.The pattern of tropical precipitation change is generally anchored by the spatial variations of relative surface temperature change(deviations from the tropical mean value)in the FGOALS models.Moreover,the projected changes in the updated FGOALS models are closer to the multi-model ensemble mean results than their predecessors,suggesting that there are noticeable improvements in the future projections of FGOALS models from CMIP5 to CMIP6.

China’s Recent Progresses in Polar Climate Change and Its Interactions with the Global Climate System

During the recent four decades since 1980,a series of modern climate satellites were launched,allowing for the measurement and record-keeping of multiple climate parameters,especially over the polar regions where traditional observations are difficult to obtain.China has been actively engaging in polar expeditions.Many observations were conducted during this period,accompanied by improved Earth climate models,leading to a series of insightful understandings concerning Arctic and Antarctic climate changes.Here,we review the recent progress China has made concerning Arctic and Antarctic climate change research over the past decade.The Arctic temperature increase is much higher than the global-mean warming rate,associated with a rapid decline in sea ice,a phenomenon called the Arctic Amplification.The Antarctic climate changes showed a zonally asymmetric pattern over the past four decades,with most of the fastest changes occurring over West Antarctica and the Antarctic Peninsula.The Arctic and Antarctic climate changes were driven by anthropogenic greenhouse gas emissions and ozone loss,while tropical-polar teleconnections play important roles in driving the regional climate changes and extreme events over the polar regions.Polar climate changes may also feedback to the entire Earth climate system.The adjustment of the circulation in both the troposphere and the stratosphere contributed to the interactions between the polar climate changes and lower latitudes.Climate change has also driven rapid Arctic and Southern ocean acidification.Chinese researchers have made a series of advances in understanding these processes,as reviewed in this paper.

Spatial and temporal variability of sea ice deformation rates in the Arctic Ocean observed by RADARSAT-1

Sea ice deformation parameters are important for elucidation of the properties and characteristics of ice-ocean models.Observations of sea ice motion over 11.5 year period(November 1996–April 2008) are used to calculate ice motion divergence and shear rates, and thus, to construct total deformation rate(TDR) estimates with respect to spatial and temporal variability in the Arctic Ocean. Strong sea ice deformation signal(SDS) rates are identified when TDR>0.01 day^(-1), and very strong SDS events,when TDR>0.05 day^(-1). These calculations are based on measurements made by the RADARSAT-1 Geophysical Processer System(RGPS). Statistical analysis of the SDS data suggest the following features:(1) Mean SDS and the SDS probability distributions are larger in "low latitudes" of the Arctic Ocean(less than 80°N) than in "high latitudes"(above 80°N), in both summer and winter;(2) very high SDS probabilities distributions and mean SDS values occur in coastal areas, e.g. the East Siberian Sea, Chukchi Sea and Beaufort Sea;(3) areas with relatively low TDR values, in the range from 0.01 day^(-1) to 0.05 day^(-1), cover much of the Arctic Ocean, in summer and winter;(4) of the entire TDR dataset, 45.89% belong to SDS, with summer the SDS percentage, 59.06%,and the winter SDS percentage, 40.50%. Statistically, the summer mean SDS, SDS percentage and very strong SDS are larger than corresponding values in the winter for each year, and show slight increasing tendencies during the years from 1997 to 2007.These results suggest important constraints for accurate simulations of very strong SDS in ice-ocean models.