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Atmospheric Precursors of and Response to Anomalous Arctic Sea Ice in CMIP5 Models


doi: 10.1007/s00376-017-7039-9

  • This study examines pre-industrial control simulations from CMIP5 climate models in an effort to better understand the complex relationships between Arctic sea ice and the stratosphere, and between Arctic sea ice and cold winter temperatures over Eurasia. We present normalized regressions of Arctic sea-ice area against several atmospheric variables at extended lead and lag times. Statistically significant regressions are found at leads and lags, suggesting both atmospheric precursors of, and responses to, low sea ice; but generally, the regressions are stronger when the atmosphere leads sea ice, including a weaker polar stratospheric vortex indicated by positive polar cap height anomalies. Significant positive midlatitude eddy heat flux anomalies are also found to precede low sea ice. We argue that low sea ice and raised polar cap height are both a response to this enhanced midlatitude eddy heat flux. The so-called "warm Arctic, cold continents" anomaly pattern is present one to two months before low sea ice, but is absent in the months following low sea ice, suggesting that the Eurasian cooling and low sea ice are driven by similar processes. Lastly, our results suggest a dependence on the geographic region of low sea ice, with low Barents-Kara Sea ice correlated with a weakened polar stratospheric vortex, whilst low Sea of Okhotsk ice is correlated with a strengthened polar vortex. Overall, the results support a notion that the sea ice, polar stratospheric vortex and Eurasian surface temperatures collectively respond to large-scale changes in tropospheric circulation.
    摘要: 本文利用第五次耦合模式比较计划(CMIP5)工业革命前对照实验的模式模拟结果, 考察了北极海冰与对流层大气、及其与欧亚冷冬的联系. 对北极海冰与大气环流进行超前滞后回归分析发现, 大气环流既是海冰异常的前兆因子同时也存在大气对海冰的滞后响应. 总体来说, 大气环流(如平流层极涡)异常超前于海冰异常的回归信号相对更强. 对海冰减退而言, 其前期中纬度涡动热通量出现显著正异常. 海冰减少和极盖位势高度是对前期中纬度强涡动热通量的响应. “极地热大陆冷”异常型也超前海冰减退异常1-2个月, 而在其之后消失, 表明欧亚冷异常和低海冰异常一样, 也是由中纬度强涡动热通量所控制. 本文结果还指出与大气环流异常相关的海冰异常的地理依赖性, 比如巴伦之海-喀拉海海冰减少之前往往出现平流层极涡减弱, 而鄂霍次克海海冰减少则对应着极涡增强. 总之, 从本文对大气超前一面的讨论结果而言, 海冰、平流层极涡和欧亚表面温度等的异常是对对流层大尺度大气环流的响应. (翻译:张鹏飞)
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  • Baldwin M. P., T. J. Dunkerton, 2001: Stratospheric harbingers of anomalous weather regimes.Science,294,581-584, https://doi.org/10.1126/science.1063315.10.1126/science.1063315eef35230b9a42dc2ec1960dde3dbee70http%3A%2F%2Fwww.bioone.org%2Fservlet%2Flinkout%3Fsuffix%3Di0276-4741-32-4-431-Baldwin1%26amp%3Bdbid%3D8%26amp%3Bdoi%3D10.1659%252FMRD-JOURNAL-D-12-00062.1%26amp%3Bkey%3D11641495http://www.sciencemag.org/cgi/doi/10.1126/science.1063315
    Baldwin M. P., D. B. Stephenson, D. W. J. Thompson, T. J. Dunkerton, A. J. Charlton, and A. O'Neill, 2003: Stratospheric memory and skill of extended-range weather forecasts.Science,301,636-640, https://doi.org/10.1126/science.1087143.10.1126/science.108714312893941393e58b950d97c5fdc013c6d497f4d8fhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FPMED%3Fid%3D12893941http://www.sciencemag.org/cgi/doi/10.1126/science.1087143We use an empirical statistical model to demonstrate significant skill in making extended-range forecasts of the monthly-mean Arctic Oscillation (AO). Forecast skill derives from persistent circulation anomalies in the lowermost stratosphere and is greatest during boreal winter. A comparison to the Southern Hemisphere provides evidence that both the time scale and predictability of the AO depend on the presence of persistent circulation anomalies just above the tropopause. These circulation anomalies most likely affect the troposphere through changes to waves in the upper troposphere, which induce surface pressure changes that correspond to the AO.
    Boland, E. J. D., T. J. Bracegirdle, E. F. Shuckburgh, 2017: Assessment of sea ice-atmosphere links in CMIP5 models.Climate Dyn.,49,683-702, https://doi.org/10.1007/s00382-016-3367-1.10.1007/s00382-016-3367-1ab3a251e32d7be734f9bdd52732c59b5http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00382-016-3367-1http://link.springer.com/10.1007/s00382-016-3367-1The Arctic is currently undergoing drastic changes in climate, largely thought to be due to so-called `Arctic amplification', whereby local feedbacks enhance global warming. Recently, a number of observational and modelling studies have questioned what the implications of this change in Arctic sea ice extent might be for weather in Northern Hemisphere midlatitudes, and in particular whether recent extremely cold winters such as 2009/10 might be consistent with an influence from observed Arctic sea ice decline. However, the proposed mechanisms for these links have not been consistently demonstrated. In a uniquely comprehensive cross-season and cross-model study, we show that the CMIP5 models provide no support for a relationship between declining Arctic sea ice and a negative NAM, or between declining Barents-Kara sea ice and cold European temperatures. The lack of evidence for the proposed links is consistent with studies that report a low signal-to-noise ratio in these relationships. These results imply that, whilst links may exist between declining sea ice and extreme cold weather events in the Northern Hemisphere, the CMIP5 model experiments do not show this to be a leading order effect in the long-term. We argue that this is likely due to a combination of the limitations of the CMIP5 models and an indication of other important long-term influences on Northern Hemisphere climate.
    Christiansen B., 2001: Downward propagation of zonal mean zonal wind anomalies from the stratosphere to the troposphere: Model and reanalysis.J. Geophys. Res.,106,27 307-27 322, https://doi.org/10.1029/2000JD000214.10.1029/2000JD000214c783b03c5a5d38dcc5b8b3f21c12683dhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2000JD000214%2Fcitedbyhttp://doi.wiley.com/10.1029/2000JD000214The connection between the Arctic Oscillation and the stratosphere is investigated on intra-annual timescales. Both the National Centers for Environmental Prediction reanalysis data and a general circulation model simulation are used. In the winter half year November-April the dominant variability in the stratosphere in middle and high latitudes has the form of downward propagation of zonal mean zonal wind anomalies. The strength of the anomalies decays below 10 hPa, but often the anomalies reach the surface. The time for the propagation from 10 hPa to the surface is 藴15 days. When positive anomalies reach the surface, the phase of the Arctic Oscillation tends to be positive. The stratospheric variability and the downward propagation is found to be driven by the vertical component of the Eliassen-Palm flux. This flux propagates from the lower troposphere to the tropopause on a timescale of 5 days. Model and reanalysis compare well in the structure of the stratospheric variability and the connection between the stratosphere and troposphere. However, the strength of the stratospheric variability is 藴25% weaker in the model.
    Cohen J., J. Jones, J. C. Furtado, and E. Tziperman, 2013: Warm arctic,cold continents: A common pattern related to arctic sea ice melt,snow advance,and extreme winter weather. Oceanography, 26, 150-160,2013. 70.https://doi.org/10.5670/oceanog.
    Cohen, J., Coauthors, 2014: Recent arctic amplification and extreme mid-latitude weather.Nature Geoscience,7,627-637, https://doi.org/10.1038/ngeo2234.10.1038/ngeo22344cd471caba2fba3502432bd1eab5ae32http%3A%2F%2Fwww.nature.com%2Fabstractpagefinder%2F10.1038%2Fngeo2234http://www.nature.com/doifinder/10.1038/ngeo2234The Arctic region has warmed more than twice as fast as the global average a phenomenon known as Arctic amplification. The rapid Arctic warming has contributed to dramatic melting of Arctic sea ice and spring snow cover, at a pace greater than that simulated by climate models. These profound changes to the Arctic system have coincided with a period of ostensibly more frequent extreme weather events across the Northern Hemisphere mid-latitudes, including severe winters. The possibility of a link between Arctic change and mid-latitude weather has spurred research activities that reveal three potential dynamical pathways linking Arctic amplification to mid-latitude weather: changes in storm tracks, the jet stream, and planetary waves and their associated energy propagation. Through changes in these key atmospheric features, it is possible, in principle, for sea ice and snow cover to jointly influence mid-latitude weather. However, because of incomplete knowledge of how high-latitude climate change influences these phenomena, combined with sparse and short data records, and imperfect models, large uncertainties regarding the magnitude of such an influence remain. We conclude that improved process understanding, sustained and additional Arctic observations, and better coordinated modelling studies will be needed to advance our understanding of the influences on mid-latitude weather and extreme events.
    Edmon H. J., B. J. Hoskins, and M. E. McIntyre, 1980: Eliassen-palm cross sections for the troposphere. J. Atmos. Sci., 37, 2600-2616, https://doi.org/10.1175/1520-0469(1980)037 <2600:EPCSFT>2.0,CO;2.10.1175/1520-0469(1980)0372.0.CO;263345326183008ef37da4949ba7e3a17http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1980jats...37.2600ehttp://journals.ametsoc.org/doi/abs/10.1175/1520-0469%281980%29037%3C2600%3AEPCSFT%3E2.0.CO%3B2`Eliassen-Palm (EP) cross sections' are meridional cross sections showing the Eliassen-Palm flux F by arrows and its divergence by contours. For large-scale, quasi-geostrophic motion F is defined to have and components rcos[, /] where is latitude, pressure, potential temperature, rthe radius of the earth, bars and primes denote zonal means and deviations and (u,v) is horizontal velocity. The theoretical reasons for using EP cross sections diagnostically are reviewed. The divergence of F reflects the magnitude of transient and irreversible eddy processes at each height and latitude, and is proportional to the northward flux of quasi-geostrophic (not Ertel's) potential vorticity. It is a direct measure of the total forcing of the zonal-mean state by the eddies. The direction of F indicates the relative importance of the principal eddy fluxes of heat and momentum. If the eddy dynamics is Rossby wavelike, then F is also a measure of net wave propagation from one height and latitude to another. Observational and theoretical EP cross sections are presented for the layer 1000-50 mb, and discussed in terms of the abovementioned properties. The observational cross sections for transient eddies are more reliably determined than for stationary eddies, and resemble to a significant degree the cross sections given by nonlinear baroclinic instability simulations. They do not resemble those given by linear instability theory for a realistic mean state (verifying the inappropriateness of linear theory as a basis for eddy parameterizations). They provide a direct view of the latitudinal planetary-wave propagation mechanism whereby midlatitudinal instabilities influence the high-tropospheric subtropics. A similar dynamical linkage appears to be depicted by the EP cross sections for stationary eddies in winter. The cross sections for stationary eddies in summer are strikingly different, but not very well determined by the data. Nevertheless, there are reasons why some of the differences might be real, with possible implications for theories of stationary planetary waves. The `residual meridional circulations' associated with the observed EP cross sections are presented and discussed.
    Francis J. A., W. H. Chan, D. J. Leathers, J. R. Miller, and D. E. Veron, 2009: Winter northern hemisphere weather patterns remember summer arctic sea-ice extent,Geophys. Res. Lett.,36,L07503, https://doi.org/10.1029/2009GL037274.10.1029/2009GL037274d3b87d349c019c3e05604f4fbcfb548chttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2009GL037274%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2009GL037274/fullThe dramatic decline in Arctic summer sea-ice cover is a compelling indicator of change in the global climate system and has been attributed to a combination of natural and anthropogenic effects. Through its role in regulating the exchange of energy between the ocean and atmosphere, ice loss is anticipated to influence atmospheric circulation and weather patterns. By combining satellite measurements of sea-ice extent and conventional atmospheric observations, we find that varying summer ice conditions are associated with large-scale atmospheric features during the following autumn and winter well beyond the Arctic's boundary. Mechanisms by which the atmosphere “remembers” a reduction in summer ice cover include warming and destabilization of the lower troposphere, increased cloudiness, and slackening of the poleward thickness gradient that weakens the polar jet stream. This ice-atmosphere relationship suggests a potential long-range outlook for weather patterns in the northern hemisphere.
    Garfinkel C. I., D. L. Hartmann, and F. Sassi, 2010: Tropospheric precursors of anomalous northern hemisphere stratospheric polar vortices.J. Climate,23,3282-3299, https://doi.org/10.1175/2010JCLI3010.1.10.1175/2010JCLI3010.1ef082c9382fca2eb375c19e810fe3fbehttp%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103246477.htmlhttp://journals.ametsoc.org/doi/abs/10.1175/2010JCLI3010.1Regional extratropical tropospheric variability in the North Pacific and eastern Europe is well correlated with variability in the Northern Hemisphere wintertime stratospheric polar vortex in both the ECMWF reanalysis record and in the Whole Atmosphere Community Climate Model. To explain this correlation, the link between stratospheric vertical Eliassen-Palm flux variability and tropospheric va...
    Honda M., J. Inoue, and S. Yamane, 2009: Influence of low arctic sea-ice minima on anomalously cold Eurasian winters. Geophys. Res. Lett. 36, https://doi.org/10.1029/2008GL037079.10.1029/2008GL03707911ff7459b32da24cee92554351efd9cbhttp%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103055291.htmlhttp://www.cabdirect.org/abstracts/20103055291.htmlInfluence of low Arctic sea-ice minima in early autumn on the wintertime climate over Eurasia is investigated. Observational evidence shows that significant cold anomalies over the Far East in early winter and zonally elongated cold anomalies from Europe to Far East in late winter are associated with the decrease of the Arctic sea-ice cover in the preceding summer-to-autumn seasons. Results fro...
    Hopsch S., J. Cohen, and K. Dethloff, 2012: Analysis of a link between fall arctic sea ice concentration and atmospheric patterns in the following winter,Tellus A,64,18624, v64i0. 18624.https://doi.org/10.3402/tellusa.10.3402/tellusa.v64i0.1862446fe623b20c72ca3fe205effb7547100http%3A%2F%2Fwww.tandfonline.com%2Fdoi%2Fabs%2F10.3402%2Ftellusa.v64i0.18624https://www.tandfonline.com/doi/full/10.3402/tellusa.v64i0.18624The impact of anomalous fall Arctic sea ice concentrations (SICs) on atmospheric patterns in the following winter is revisited by analysing results for two time periods: the most recent, satellite-era period (19792010) and a longer time-period (19502010). On the basis of September SICs for each time-period, an index was constructed which was used to identify anomalous high/low SIC years for both the original, as well as for the linearly detrended sea ice index. Identified years were then used to derive composites for the following winter's monthly atmospheric variables. Mid-troposphere geopotential height composites for winter months are in general reminiscent of the North Atlantic Oscillation pattern with high latitude maximum shifted towards the Barents Sea. Also, lower troposphere temperatures indicate the presence of cooler conditions over the continents during low SIC years. However, differences in the composite patterns are significant only for areas with limited spatial extent. While suggested pathways in previously published studies seem reasonable, our results show that these findings are not yet robust enough from a statistical significance perspective. More data (e.g. provided by longer, climate-quality reanalysis datasets) are needed before conclusions of impacts and feedbacks can be drawn with certainty.
    Jaiser R., K. Dethloff, D. Hand orf, A. Rinke, and J. Cohen, 2012: Impact of sea ice cover changes on the northern hemisphere atmospheric winter circulation,Tellus A,64,11595, v64i0. 11595.https://doi.org/10.3402/tellusa.10.3402/tellusa.v64i0.1159573cf21d64de757276aa85a42a608612chttp%3A%2F%2Fwww.tandfonline.com%2Fdoi%2Fabs%2F10.3402%2Ftellusa.v64i0.11595https://www.tandfonline.com/doi/full/10.3402/tellusa.v64i0.11595The response of the Arctic atmosphere to low and high sea ice concentration phases based on European Center for Medium-Range Weather Forecast (ECMWF) Re-Analysis Interim (ERA-Interim) atmospheric data and Hadley Centre's sea ice dataset (HadISST1) from 1989 until 2010 has been studied. Time slices of winter atmospheric circulation with high (1990-2000) and low (2001-2010) sea ice concentration in the preceding August/September have been analysed with respect to tropospheric interactions between planetary and baroclinic waves. It is shown that a changed sea ice concentration over the Arctic Ocean impacts differently the development of synoptic and planetary atmospheric circulation systems. During the low ice phase, stronger heat release to the atmosphere over the Arctic Ocean reduces the atmospheric vertical static stability. This leads to an earlier onset of baroclinic instability that further modulates the non-linear interactions between baroclinic wave energy fluxes on time scales of 2.56 d and planetary scales of 10-90 d. Our analysis suggests that Arctic sea ice concentration changes exert a remote impact on the large-scale atmospheric circulation during winter, exhibiting a barotropic structure with similar patterns of pressure anomalies at the surface and in the mid-troposphere. These are connected to pronounced planetary wave train changes notably over the North Pacific.
    Kim B.-M., S.-W. Son, S.-K. Min, J.-H. Jeong, S.-J. Kim, X. D. Zhang, T. Shim, and J.-H. Yoon, 2014: Weakening of the stratospheric polar vortex by arctic sea-ice loss,Nature Communications,5,4646, https://doi.org/10.1038/ncomms5646.10.1038/ncomms5646251813900c34446785d2f1fe02375ca8641143f2http%3A%2F%2Fwww.nature.com%2Fncomms%2F2014%2F140902%2Fncomms5646%2Fabs%2Fncomms5646.htmlhttp://www.nature.com/doifinder/10.1038/ncomms5646Successive cold winters of severely low temperatures in recent years have had critical social and economic impacts on the mid-latitude continents in the Northern Hemisphere. Although these cold winters are thought to be partly driven by dramatic losses of Arctic sea-ice, the mechanism that links sea-ice loss to cold winters remains a subject of debate. Here, by conducting observational analyses and model experiments, we show how Arctic sea-ice loss and cold winters in extra-polar regions are dynamically connected through the polar stratosphere. We find that decreased sea-ice cover during early winter months (November-December), especially over the Barents-Kara seas, enhances the upward propagation of planetary-scale waves with wavenumbers of 1 and 2, subsequently weakening the stratospheric polar vortex in mid-winter (January-February). The weakened polar vortex preferentially induces a negative phase of Arctic Oscillation at the surface, resulting in low temperatures in mid-latitudes.
    Knutti R., D. Masson, and A. Gettelman, 2013: Climate model genealogy: generation CMIP5 and how we got there.Geophys. Res. Lett.,40,1194-1199, https://doi.org/10.1002/grl.50256.10.1002/grl.502566041d4ddba374d30561fd92024b47421http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fgrl.50256%2Ffullhttp://doi.wiley.com/10.1002/grl.50256A new ensemble of climate models is becoming available and provides the basis for climate change projections. Here, we show a first analysis indicating that the models in the new ensemble agree better with observations than those in older ones and that the poorest models have been eliminated. Most models are strongly tied to their predecessors, and some also exchange ideas and code with other models, thus supporting an earlier hypothesis that the models in the new ensemble are neither independent of each other nor independent of the earlier generation. On the basis of one atmosphere model, we show how statistical methods can identify similarities between model versions and complement process understanding in characterizing how and why a model has changed. We argue that the interdependence of models complicates the interpretation of multimodel ensembles but largely goes unnoticed.
    Koenigk T., M. Caian, G. Nikulin, and S. Schimanke, 2016: Regional arctic sea ice variations as predictor for winter climate conditions.Climate Dyn.,46,317-337, https://doi.org/10.1007/s00382-015-2586-1.10.1007/s00382-015-2586-18ca179b60d5c665d89e9c04c6bb98392http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00382-015-2586-1http://link.springer.com/10.1007/s00382-015-2586-1Seasonal prediction skill of winter mid and high northern latitudes climate from sea ice variations in eight different Arctic regions is analyzed using detrended ERA-interim data and satellite sea ice data for the period 1980–2013. We find significant correlations between ice areas in both September and November and winter sea level pressure, air temperature and precipitation. The prediction skill is improved when using November sea ice conditions as predictor compared to September. This is particularly true for predicting winter NAO-like patterns and blocking situations in the Euro-Atlantic area. We find that sea ice variations in Barents Sea seem to be most important for the sign of the following winter NAO—negative after low ice—but amplitude and extension of the patterns are modulated by Greenland and Labrador Seas ice areas. November ice variability in the Greenland Sea provides the best prediction skill for central and western European temperature and ice variations in the Laptev/East Siberian Seas have the largest impact on the blocking number in the Euro-Atlantic region. Over North America, prediction skill is largest using September ice areas from the Pacific Arctic sector as predictor. Composite analyses of high and low regional autumn ice conditions reveal that the atmospheric response is not entirely linear suggesting changing predictive skill dependent on sign and amplitude of the anomaly. The results confirm the importance of realistic sea ice initial conditions for seasonal forecasts. However, correlations do seldom exceed 0.6 indicating that Arctic sea ice variations can only explain a part of winter climate variations in northern mid and high latitudes.
    Kost J. T., M. P. McDermott, 2002: Combining dependent P-values.Statistics & Probability Letters,60,183-190, .http://doi.org/10.1016/S0167-7152(02)00310-3
    Kug J.-S., J.-H. Jeong, Y.-S. Jang, B.-M. Kim, C. K. Folland , S.-K. Min, and S.-W. Son, 2015: Two distinct influences of arctic warming on cold winters over North America and East Asia.Nature Geosci,8,759-762, https://doi.org/10.1038/ngeo2517.10.1038/NGEO251776adf9a50b5913a10d5735fde3c115c3http%3A%2F%2Fwww.nature.com%2Fngeo%2Fjournal%2Fv8%2Fn10%2Fngeo2517%2Fmetricshttp://www.nature.com/doifinder/10.1038/ngeo2517Arctic warming has sparked a growing interest because of its possible impacts on mid-latitude climate. A number of unusually harsh cold winters have occurred in many parts of East Asia and North America in the past few years, and observational and modelling studies have suggested that atmospheric variability linked to Arctic warming might have played a central role. Here we identify two distinct influences of Arctic warming which may lead to cold winters over East Asia or North America, based on observational analyses and extensive climate model results. We find that severe winters across East Asia are associated with anomalous warmth in the Barents-Kara Sea region, whereas severe winters over North America are related to anomalous warmth in the East Siberian-Chukchi Sea region. Each regional warming over the Arctic Ocean is accompanied by the local development of an anomalous anticyclone and the downstream development of a mid-latitude trough. The resulting northerly flow of cold air provides favourable conditions for severe winters in East Asia or North America. These links between Arctic and mid-latitude weather are also robustly found in idealized climate model experiments and CMIP5 multi-model simulations. We suggest that our results may help improve seasonal prediction of winter weather and extreme events in these regions.
    Martius O., L. M. Polvani, and H. C. Davies, 2009: Blocking precursors to stratospheric sudden warming events. Geophys. Res. Lett. 36, https://doi.org/10.1029/2009GL038776.10.1029/2009GL0387768725b8aefe0512d59882521b541f153dhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2009GL038776%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2009GL038776/fullThe primary causes for the onset of major, midwinter, stratospheric sudden warming events remain unclear. In this paper, we report that 25 of the 27 events objectively identified in the ERA-40 dataset for the period 1957-2001 are preceded by blocking patterns in the troposphere. The spatial characteristics of tropospheric blocks prior to sudden warming events are strongly correlated with the type of sudden warming event that follows. Vortex displacement events are nearly always preceded by blocking over the Atlantic basin only, whereas vortex splitting events are preceded by blocking events occurring in the Pacific basin or in both basins contemporaneously. The differences in the geographical blocking distribution prior to sudden warming events are mirrored in the patterns of planetary waves that are responsible for producing events of either type. The evidence presented here, suggests that tropospheric blocking plays an important role in determining the onset and the type of warmings.
    McCusker K. E., J. C. Fyfe, and M. Sigmond, 2016: Twenty-five winters of unexpected Eurasian cooling unlikely due to arctic sea-ice loss.Nature Geoscience,9,838-842, https://doi.org/10.1038/ngeo2820.10.1038/ngeo282086ebb2cb4509993b8b6992484cd04e67http%3A%2F%2Fwww.nature.com%2Fngeo%2Fjournal%2Fv9%2Fn11%2Fngeo2820%2Fmetricshttp://www.nature.com/doifinder/10.1038/ngeo2820Winter cooling over Eurasia has been suggested to be linked to Arctic sea-ice loss. Climate model simulations reveal no evidence for such a link and instead suggest that a persistent atmospheric circulation pattern is responsible.
    Mori M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust arctic sea-ice influence on the frequent Eurasian cold winters in past decades.Nature Geoscience,7,869-873, https://doi.org/10.1038/ngeo2277.10.1038/ngeo2277cdef8a86f56c39f6052fde6e5d1dd7bbhttp%3A%2F%2Fwww.nature.com%2Fngeo%2Fjournal%2Fv7%2Fn12%2Fabs%2Fngeo2277.htmlhttp://www.nature.com/doifinder/10.1038/ngeo2277Over the past decade, severe winters occurred frequently in mid-latitude Eurasia, despite increasing global- and annual-mean surface air temperatures. Observations suggest that these cold Eurasian winters could have been instigated by Arctic sea-ice decline, through excitation of circulation anomalies similar to the Arctic Oscillation. In climate simulations, however, a robust atmospheric response to sea-ice decline has not been found, perhaps owing to energetic internal fluctuations in the atmospheric circulation. Here we use a 100-member ensemble of simulations with an atmospheric general circulation model driven by observation-based sea-ice concentration anomalies to show that as a result of sea-ice reduction in the Barents-Kara Sea, the probability of severe winters has more than doubled in central Eurasia. In our simulations, the atmospheric response to sea-ice decline is approximately independent of the Arctic Oscillation. Both reanalysis data and our simulations suggest that sea-ice decline leads to more frequent Eurasian blocking situations, which in turn favour cold-air advection to Eurasia and hence severe winters. Based on a further analysis of simulations from 22 climate models we conclude that the sea-ice-driven cold winters are unlikely to dominate in a warming future climate, although uncertainty remains, due in part to an insufficient ensemble size.
    Nakamura T., K. Yamazaki, K. Iwamoto, M. Honda, Y. Miyoshi, Y. Ogawa, Y. Tomikawa, and J. Ukita, 2016: The stratospheric pathway for arctic impacts on midlatitude climate.Geophys. Res. Lett.,43,3494-3501, https://doi.org/10.1002/2016GL068330.10.1002/2016GL068330b149e8559dbb4aaa964cec0873755ae5http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2016GL068330%2Ffullhttp://doi.wiley.com/10.1002/2016GL068330Recent evidence from both observations and model simulations suggests that an Arctic sea ice reduction tends to cause a negative Arctic Oscillation (AO) phase with severe winter weather in the Northern Hemisphere, which is often preceded by weakening of the stratospheric polar vortex. Although this evidence hints at a stratospheric involvement in the Arctic-midlatitude climate linkage, the exact role of the stratosphere remains elusive. Here we show that tropospheric AO response to the Arctic sea ice reduction largely disappears when suppressing the stratospheric wave mean flow interactions in numerical experiments. The results confirm a crucial role of the stratosphere in the sea ice impacts on the midlatitudes by coupling between the stratospheric polar vortex and planetary-scale waves. Those results and consistency with observation-based evidence suggest that a recent Arctic sea ice loss is linked to midlatitudes extreme weather events associated with the negative AO phase.
    Newman P. A., E. R. Nash, 2000: Quantifying the wave driving of the stratosphere.J. Geophys. Res.,105,12 485-12 497, https://doi.org/10.1029/1999JD901191.10.1029/1999JD9011912bdca7d63b8ba6404e46f86ce2cd5c04http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F1999JD901191%2Ffullhttp://doi.wiley.com/10.1029/1999JD901191Abstract Top of page Abstract References The zonal-mean eddy heat flux is directly proportional to the wave activity that propagates from the troposphere into the stratosphere. This quantity is a simple eddy diagnostic which is calculated from conventional meteorological analyses. Because this “wave driving” of the stratosphere has a strong impact on the stratospheric temperature, it is necessary to compare the impact of the flux with respect to stratospheric radiative changes caused by greenhouse gas changes. Hence we must understand the precision and accuracy of the heat flux derived from our global meteorological analyses. Herein we quantify the stratospheric heat flux using five different meteorological analyses and show that there are 15% differences, on average, between these analyses during the disturbed conditions of the Northern Hemisphere winter. Such large differences result from the planetary differences in the stationary temperature and meridional wind fields. In contrast, planetary transient waves show excellent agreement among these five analyses, and this transient heat flux appears to have a long-term downward trend.
    Overland, J. E., Coauthors, 2016: Nonlinear response of mid-latitude weather to the changing arctic.Nat. Clim. Change,6,992-999, https://doi.org/10.1038/nclimate3121.10.1038/nclimate3121042c9149fc49589ba72cc4cbab4b151dhttp%3A%2F%2Fwww.nature.com%2Fnclimate%2Fjournal%2Fv6%2Fn11%2Ffig_tab%2Fnclimate3121_F5.htmlhttp://www.nature.com/doifinder/10.1038/nclimate3121Are continuing changes in the Arctic influencing wind patterns and the occurrence of extreme weather events in northern mid-latitudes? The chaotic nature of atmospheric circulation precludes easy answers. The topic is a major science challenge, as continued Arctic temperature increases are an inevitable aspect of anthropogenic climate change. We propose a perspective that rejects simple cause-and-effect pathways and notes diagnostic challenges in interpreting atmospheric dynamics. We present a way forward based on understanding multiple processes that lead to uncertainties in Arctic and mid-latitude weather and climate linkages. We emphasize community coordination for both scientific progress and communication to a broader public.
    Pedersen R. A., I. Cvijanovic, P. L. Langen, and B. M. Vinther, 2016: The impact of regional arctic sea ice loss on atmospheric circulation and the NAO.J. Climate,29,889-902, https://doi.org/10.1175/JCLI-D-15-0315.1.10.1175/JCLI-D-15-0315.1d3da800db08f6a0c8116f9714124a0cchttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2016EGUGA..18.7437Ahttp://journals.ametsoc.org/doi/10.1175/JCLI-D-15-0315.1Rasmus A. Pedersen, Ivana Cvijanovic, Peter L. Langen, and Bo M. Vinther, 2016: The Impact of Regional Arctic Sea Ice Loss on Atmospheric Circulation and the NAO. J. Climate, 29, 889–902. doi: http://dx.doi.org/10.1175/JCLI-D-15-0315.1
    Peings Y., G. Magnusdottir, 2014: Response of the wintertime northern hemisphere atmospheric circulation to current and projected arctic sea ice decline: A numerical study with CAM5.J. Climate,27,244-264, https://doi.org/10.1175/JCLI-D-13-00272.1.10.1175/JCLI-D-13-00272.1e9732dd6358dbd0d3b6b5b82193b2c9chttp%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FXREF%3Fid%3D10.1175%2FJCLI-D-13-00272.1http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00272.1The wintertime Northern Hemisphere (NH) atmospheric circulation response to current (2007-12) and projected (2080-99) Arctic sea ice decline is examined with the latest version of the Community Atmospheric Model (CAM5). The numerical experiments suggest that the current sea ice conditions force a remote atmospheric response in late winter that favors cold land surface temperatures over midlatitudes, as has been observed in recent years. Anomalous Rossby waves forced by the sea ice anomalies penetrate into the stratosphere in February and weaken the stratospheric polar vortex, resulting in negative anomalies of the northern annular mode (NAM) that propagate downward during the following weeks, especially over the North Pacific. The seasonality of the response is attributed to timing of the phasing between the forced and climatological waves. When sea ice concentration taken from projections of conditions at the end of the twenty-first century is prescribed to the model, negative anomalies of theNAMare visible in the troposphere, both in early and late winter. This response is mainly driven by the large warming of the lower troposphere over the Arctic, as little impact is found in the stratosphere in this experiment. As a result of the thermal expansion of the polar troposphere, the westerly flow is decelerated and a weak but statistically significant increase of the midlatitude meanders is identified. However, the thermodynamical response extends beyond the Arctic and offsets the dynamical effect, such that the stronger sea ice forcing has limited impact on the intensity of cold extremes over midlatitudes. 2014 American Meteorological Society.
    Perlwitz J., M. Hoerling, and R. Dole, 2015: Arctic tropospheric warming: Causes and linkages to lower latitudes.J. Climate,28,2154-2167, https://doi.org/10.1175/JCLI-D-14-00095.1.10.1175/JCLI-D-14-00095.1e1f15b352e80b6968f6ca4e5cee932b6http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JCli...28.2154Phttp://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00095.1Arctic temperatures have risen dramatically relative to those of lower latitudes in recent decades, with a common supposition being that sea ice declines are primarily responsible for amplified Arctic tropospheric warming. This conjecture is central to a hypothesis in which Arctic sea ice loss forms the beginning link of a causal chain that includes weaker westerlies in midlatitudes, more persistent and amplified midlatitude waves, and more extreme weather. Through model experimentation, the first step in this chain is examined by quantifying contributions of various physical factors to October揇ecember (OND) mean Arctic tropospheric warming since 1979. The results indicate that the main factors responsible for Arctic tropospheric warming are recent decadal fluctuations and long-term changes in sea surface temperatures (SSTs), both located outside the Arctic. Arctic sea ice decline is the largest contributor to near-surface Arctic temperature increases, but it accounts for only about 20% of the magnitude of 1000500-hPa warming. These findings thus disconfirm the hypothesis that deep tropospheric warming in the Arctic during OND has resulted substantially from sea ice loss. Contributions of the same factors to recent midlatitude climate trends are then examined. It is found that pronounced circulation changes over the North Atlantic and North Pacific result mainly from recent decadal ocean fluctuations and internal atmospheric variability, while the effects of sea ice declines are very small. Therefore, a hypothesized causal chain of hemisphere-wide connections originating from Arctic sea ice loss is not supported.
    Petoukhov V., V. A. Semenov, 2010: A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J. Geophys. Res. 115, https://doi.org/10.1029/2009JD013568.10.1029/2009JD013568dc1ac9e62c94b87f316ae99122829c96http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2009JD013568%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1029/2009JD013568/pdfThe recent overall Northern Hemisphere warming was accompanied by several severe northern continental winters, as for example, extremely cold winter 2005-2006 in Europe and northern Asia. Here we show that anomalous decrease of wintertime sea ice concentration in the Barents-Kara (B-K) seas could bring about extreme cold events like winter 2005-2006. Our simulations with the ECHAM5 general circulation model demonstrate that lower-troposphere heating over the B-K seas in the Eastern Arctic caused by the sea ice reduction may result in strong anticyclonic anomaly over the Polar Ocean and anomalous easterly advection over northern continents. This causes a continental-scale winter cooling reaching -1.5ºC, with more than 3 times increased probability of cold winter extremes over large areas including Europe. Our results imply that several recent severe winters do not conflict the global warming picture but rather supplement it, being in qualitative agreement with the simulated large-scale atmospheric circulation realignment. Furthermore, our results suggest that high-latitude atmospheric circulation response to the B-K sea ice decrease is highly nonlinear and characterized by transition from anomalous cyclonic circulation to anticyclonic one and then back again to cyclonic type of circulation as the B-K sea ice concentration gradually reduces from 100% to ice free conditions. We present a conceptual model that may explain the nonlinear local atmospheric response in the B-K seas region by counter play between convection over the surface heat source and baroclinic effect due to modified temperature gradients in the vicinity of the heating area.
    Sato K., J. Inoue, and M. Watanabe, 2014: Influence of the gulf stream on the Barents Sea ice retreat and Eurasian coldness during early winter,Environmental Research Letters,9,084009, https://doi.org/10.1088/1748-9326/9/8/084009.10.1088/1748-9326/9/8/0840099c5d56ad9ccb94480ed2f47502d57e80http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014AGUFM.A33D3218Shttp://stacks.iop.org/1748-9326/9/i=8/a=084009?key=crossref.6f28bcabaff7bcbdba0494c16983ca82Abnormal sea-ice retreat over the Barents Sea during early winter has been considered a leading driver of recent midlatitude severe winters over Eurasia. However, causal relationships between such retreat and the atmospheric circulation anomalies remains uncertain. Using a reanalysis dataset, we found that poleward shift of a sea surface temperature front over the Gulf Stream likely induces warm southerly advection and consequent sea-ice decline over the Barents Sea sector, and a cold anomaly over Eurasia via planetary waves triggered over the Gulf Stream region. The above mechanism is supported by the steady atmospheric response to the diabatic heating anomalies over the Gulf Stream region obtained with a linear baroclinic model. The remote atmospheric response from the Gulf Stream would be amplified over the Barents Sea region via interacting with sea-ice anomaly, promoting the warm Arctic and cold Eurasian pattern. (letter)
    Screen J. A., 2017a: Climate science: Far-flung effects of arctic warming.Nature Geoscience,10,253-254, https://doi.org/10.1038/ngeo2924.10.1038/ngeo2924aea36c4b3f00dd6d18be43477a8eb5d6http%3A%2F%2Fwww.nature.com%2Fngeo%2Fjournal%2Fv10%2Fn4%2Ffull%2Fngeo2924.htmlhttp://www.nature.com/doifinder/10.1038/ngeo2924Abstract Arctic warming affects weather and climate thousands of miles to the south. Scientists are split on how large this effect is.
    Screen J. A., 2017b: Simulated atmospheric response to regional and pan-arctic sea ice loss.J. Climate,30,3945-3962, https://doi.org/10.1175/JCLI-D-16-0197.1.10.1175/JCLI-D-16-0197.15a55386fa74a2b1cde0e04944b938f1bhttp%3A%2F%2Fwww.researchgate.net%2Fpublication%2F312642732_Simulated_Atmospheric_Response_to_Regional_and_Pan-Arctic_Sea-Ice_Losshttp://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0197.1Theloss ofArctic sea-iceis already having profound environmental, societal and ecologicalimpactslocally.A highlyuncertainareaofscientificresearch,however,iswhethersuchArcticchange has a tangible effect on weather and climate at lower latitudes. There is emergingevidencethat thegeographicallocation of sea-icelossis criticallyimportantin determiningthe large-scale atmospheric circulation response and associated mid-latitude impacts.However,such regionaldependencieshavenotbeenexploredinathorough andsystematicmanner.Tomake progress on thisissue, this study analyses ensemble simulations with anatmosphericgeneralcirculationmodel prescribedwithsea-icelossseparatelyinnine regionsof theArctic, toelucidate thedistinctresponses toregionalsea-iceloss. Theresultssuggestthatin some regions sea-iceloss triggerslarge-scale dynamical responseswhereasin otherregionssea-icelossinducesonlylocalthermodynamicalchanges.Sea-icelossintheBarents-KaraSeaisuniqueindrivingaweakeningofthestratosphericpolarvortex,followedintimeby a tropospheric circulation response that resembles the North Atlantic Oscillation. ForOctober-to-March, the largest spatial-scale responses are driven by sea-ice loss in theBarents-KaraSeaandSeaofOkhotsk;however,differentregionsassumegreaterimportanceinotherseasons.Theatmosphererespondsverydifferentlytoregionalsea-icelossesthantopan-Arcticsea-iceloss,andthelattercannotbeobtainedbylinearadditionoftheresponsesto regional sea-ice losses. The results imply that diversity in past studies of the simulatedresponse toArcticsea-icelosscanbepartlyexplainedbythedifferentspatialpatternsofsea-iceloss imposed.
    Screen J. A., C. Deser, and I. Simmonds, 2012: Local and remote controls on observed Arctic warming. Geophys. Res. Lett. 39, https://doi.org/10.1029/2012GL051598.10.1029/2012GL0515980d2bcba75b9feef142830ce668ae7653http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2012GL051598%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1029/2012GL051598/pdfThe Arctic is warming two to four times faster than the global average. Debate continues on the relative roles of local factors, such as sea ice reductions, versus remote factors in driving, or amplifying, Arctic warming. This study examines the vertical profile and seasonality of observed tropospheric warming, and addresses its causes using atmospheric general circulation model simulations. The simulations enable the isolation and quantification of the role of three controlling factors of Arctic warming: 1) observed Arctic sea ice concentration (SIC) and sea surface temperature (SST) changes; 2) observed remote SST changes; and 3) direct radiative forcing (DRF) due to observed changes in greenhouse gases, ozone, aerosols, and solar output. Local SIC and SST changes explain a large portion of the observed Arctic near-surface warming, whereas remote SST changes explain the majority of observed warming aloft. DRF has primarily contributed to Arctic tropospheric warming in summer.
    Sjoberg J. P., T. Birner, 2012: Transient tropospheric forcing of sudden stratospheric warmings.J. Atmos. Sci.,69,3420-3432, https://doi.org/10.1175/JAS-D-11-0195.1.10.1175/JAS-D-11-0195.17f1bcf10e6d9a72df676addb849fd891http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2012JAtS...69.3420Shttp://journals.ametsoc.org/doi/abs/10.1175/JAS-D-11-0195.1The amplitude of upward-propagating tropospherically forced planetary waves is known to be of first-order importance in producing sudden stratospheric warmings (SSWs). This forcing amplitude is observed to undergo strong temporal fluctuations. Characteristics of the resulting transient forcing leading to SSWs are studied in reanalysis data and in highly truncated simple models of stratospheric wave搈ean flow interaction. It is found in both the reanalysis data and the simple models that SSWs are preferentially generated by transient forcing of sufficiently long time scales (on the order of 1 week or longer). The time scale of the transient forcing is found to play a stronger role in producing SSWs than the strength of the forcing. In the simple models it is possible to fix the amplitude of the tropospheric forcing but to vary the time scale of the forcing. The resulting frequency of occurrence of SSWs shows dramatic reductions for decreasing forcing time scales.
    Smith K. L., P. J. Kushner, and J. Cohen, 2011: The role of linear interference in northern annular mode variability associated with Eurasian snow cover extent.J. Climate,24,6185-6202, https://doi.org/10.1175/JCLI-D-11-00055.1.10.1175/JCLI-D-11-00055.13d829219cb8c882ab29fd95a1067fd4ehttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2011JCli...24.6185Shttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-11-00055.1ABSTRACT One of the outstanding questions regarding the observed relationship between October Eurasian snow cover anomalies and the boreal winter northern annular mode (NAM) is what causes the multiple-week lag between positive Eurasian snow cover anomalies in October and the associated peak in Rossby wave activity flux from the troposphere to the stratosphere inDecember. This study explores the following hypothesis about this lag: in order to achieve amplification of the wave activity, the vertically propagating Rossby wave train associated with the snow cover anomaly must reinforce the climatological stationary wave, which corresponds to constructive linear interference between the anomalous wave and the climatological wave. It is shown that the lag in peak wave activity flux arises because the Rossby wave train associated with the snow cover is in quadrature or out of phasewith the climatological stationary wave fromOctober tomid-November. Beginning inmid-November the associated wave anomaly migrates into a position that is in phase with the climatological wave, leading to constructive interference and anomalously positive upward wave activity fluxes until mid-January. Climate models from the Coupled Model Intercomparison Project 3 (CMIP3) do not capture this behavior. This linear interference effect is not only associated with stratospheric variability related to Eurasian snow cover anomalies but is a general feature of Northern Hemisphere troposphere-stratosphere interactions and, in particular, dominated the negative NAM events of the fall-winter of 2009/10.
    Sorokina S. A., C. Li, J. J. Wettstein, and N. G. Kvamst, 2016: Observed atmospheric coupling between Barents Sea ice and the warm-arctic cold-Siberian anomaly pattern.J. Climate,29,495-511, https://doi.org/10.1175/JCLI-D-15-0046.1.10.1175/JCLI-D-15-0046.1b29ffa8838c909be8dfad5ed9ad398ffhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2016JCli...29..495Shttp://journals.ametsoc.org/doi/10.1175/JCLI-D-15-0046.1The decline in Barents Sea ice has been implicated in forcing the “warm-Arctic cold-Siberian” (WACS) anomaly pattern via enhanced turbulent heat flux (THF). This study investigates interannual variability in winter [December–February (DJF)] Barents Sea THF and its relationship to Barents Sea ice and the large-scale atmospheric flow. ERA-Interim and observational data from 1979/80 to 2011/12 are used. The leading pattern (EOF1: 33%) of winter Barents Sea THF variability is relatively weakly correlated (r = 0.30) with Barents Sea ice and appears to be driven primarily by atmospheric variability. The sea ice–related THF variability manifests itself as EOF2 (20%, r = 0.60). THF EOF2 is robust over the entire winter season, but its link to the WACS pattern is not. However, the WACS pattern emerges consistently as the second EOF (20%) of Eurasian surface air temperature (SAT) variability in all winter months. When Eurasia is cold, there are indeed weak reductions in Barents Sea ice, but the associated THF anomalies are on average negative, which is inconsistent with the proposed direct atmospheric response to sea ice variability. Lead–lag correlation analyses on shorter time scales support this conclusion and indicate that atmospheric variability plays an important role in driving observed variability in Barents Sea THF and ice cover, as well as the WACS pattern.
    Sun L. T., C. Deser, and R. A. Tomas, 2015: Mechanisms of stratospheric and tropospheric circulation response to projected arctic sea ice loss.J. Climate,28,7824-7845, org/10.1175/JCLI-D-15-0169.1.https://doi.10.1175/JCLI-D-15-0169.1ba274dff919f751130d49ac33e13a325http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JCli...28.7824Shttp://journals.ametsoc.org/doi/10.1175/JCLI-D-15-0169.1The impact of projected Arctic sea ice loss on the atmospheric circulation is investigated using the Whole Atmosphere Community Climate Model (WACCM), a model with a well-resolved stratosphere. Two 160-year simulations are conducted: one with surface boundary conditions fixed at late 20th century values, and the other with identical conditions except for Arctic sea ice which is prescribed at late 21st century values. Their difference isolates the impact of future Arctic sea ice loss upon the atmosphere. The tropospheric circulation response to the imposed ice loss resembles the negative phase of the Northern Annular Mode, with largest amplitude in winter, while the less well-known stratospheric response transitions from a slight weakening of the polar vortex in winter to a strengthening of the vortex in spring. The lack of a significant winter stratospheric circulation response is shown to be a consequence of largely cancelling effects from sea ice loss in the Atlantic and Pacific sectors, which drive opposite-signed changes in upward wave propagation from the troposphere to the stratosphere. Identical experiments conducted with Community Atmosphere Model Version 4, WACCM's low-top counterpart, show a weaker tropospheric response and a different stratospheric response compared to WACCM. An additional WACCM experiment in which the imposed ice loss is limited to August through November reveals that autumn ice loss weakens the stratospheric polar vortex in January, followed by a small but significant tropospheric response in late winter and early spring that resembles the negative phase of the North Atlantic Oscillation, with attendant surface climate impacts.
    Sun L., J. Perlwitz, and M. Hoerling, 2016: What caused the recent "warm arctic,cold continents" trend pattern in winter temperatures? Geophys. Res. Lett.,43,5345-5352,org/10.1002/2016GL069024.https://doi.
    Vihma T., 2014: Effects of arctic sea ice decline on weather and climate: A review.Surveys in Geophysics,35,1175-1214, https://doi.org/10.1007/s10712-014-9284-0.10.1007/s10712-014-9284-077da958a10209d7918a429ac5f8df01chttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs10712-014-9284-0http://link.springer.com/10.1007/s10712-014-9284-0The areal extent, concentration and thickness of sea ice in the Arctic Ocean and adjacent seas have strongly decreased during the recent decades, but cold, snow-rich winters have been common over mid-latitude land areas since 2005. A review is presented on studies addressing the local and remote effects of the sea ice decline on weather and climate. It is evident that the reduction in sea ice cover has increased the heat flux from the ocean to atmosphere in autumn and early winter. This has locally increased air temperature, moisture, and cloud cover and reduced the static stability in the lower troposphere. Several studies based on observations, atmospheric reanalyses, and model experiments suggest that the sea ice decline, together with increased snow cover in Eurasia, favours circulation patterns resembling the negative phase of the North Atlantic Oscillation and Arctic Oscillation. The suggested large-scale pressure patterns include a high over Eurasia, which favours cold winters in Europe and northeastern Eurasia. A high over the western and a low over the eastern North America have also been suggested, favouring advection of Arctic air masses to North America. Mid-latitude winter weather is, however, affected by several other factors, which generate a large inter-annual variability and often mask the effects of sea ice decline. In addition, the small sample of years with a large sea ice loss makes it difficult to distinguish the effects directly attributable to sea ice conditions. Several studies suggest that, with advancing global warming, cold winters in mid-latitude continents will no longer be common during the second half of the twenty-first century. Recent studies have also suggested causal links between the sea ice decline and summer precipitation in Europe, the Mediterranean, and East Asia.
    Walsh J. E., 2014: Intensified warming of the arctic: Causes and impacts on middle latitudes.Global and Planetary Change,117,52-63, 2014. 03. 003.https://doi.org/10.1016/j.gloplacha.10.1016/j.gloplacha.2014.03.0030492af2361aef1eb6ba44877938ed087http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0921818114000575http://linkinghub.elsevier.com/retrieve/pii/S0921818114000575Over the past half century, the Arctic has warmed at about twice the global rate. The reduction of sea ice and snow cover has contributed to the high-latitude warming, as the maximum of the amplification during autumn is a fingerprint of the ice-albedo feedback. There is evidence that atmospheric water vapor, a greenhouse gas, has increased in the Arctic over the past several decades. Ocean heat fluxes into the Arctic from the North Atlantic and North Pacific have also contributed to the Arctic warming through a reduction of sea ice. Observational and modeling studies suggest that reduced sea ice cover and a warmer Arctic in autumn may affect the middle latitudes by weakening the west-to-east wind speeds in the upper atmosphere, by increasing the frequency of wintertime blocking events that in turn lead to persistence or slower propagation of anomalous temperatures in middle latitudes, and by increasing continental snow cover that can in turn influence the atmospheric circulation. While these effects on middle latitudes have been suggested by some analyses, natural variability has thus far precluded a conclusive demonstration of an impact of the Arctic on mid-latitude weather and climate.
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Manuscript received: 20 February 2017
Manuscript accepted: 14 August 2017
通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Atmospheric Precursors of and Response to Anomalous Arctic Sea Ice in CMIP5 Models

  • 1. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QE, UK

Abstract: This study examines pre-industrial control simulations from CMIP5 climate models in an effort to better understand the complex relationships between Arctic sea ice and the stratosphere, and between Arctic sea ice and cold winter temperatures over Eurasia. We present normalized regressions of Arctic sea-ice area against several atmospheric variables at extended lead and lag times. Statistically significant regressions are found at leads and lags, suggesting both atmospheric precursors of, and responses to, low sea ice; but generally, the regressions are stronger when the atmosphere leads sea ice, including a weaker polar stratospheric vortex indicated by positive polar cap height anomalies. Significant positive midlatitude eddy heat flux anomalies are also found to precede low sea ice. We argue that low sea ice and raised polar cap height are both a response to this enhanced midlatitude eddy heat flux. The so-called "warm Arctic, cold continents" anomaly pattern is present one to two months before low sea ice, but is absent in the months following low sea ice, suggesting that the Eurasian cooling and low sea ice are driven by similar processes. Lastly, our results suggest a dependence on the geographic region of low sea ice, with low Barents-Kara Sea ice correlated with a weakened polar stratospheric vortex, whilst low Sea of Okhotsk ice is correlated with a strengthened polar vortex. Overall, the results support a notion that the sea ice, polar stratospheric vortex and Eurasian surface temperatures collectively respond to large-scale changes in tropospheric circulation.

摘要: 本文利用第五次耦合模式比较计划(CMIP5)工业革命前对照实验的模式模拟结果, 考察了北极海冰与对流层大气、及其与欧亚冷冬的联系. 对北极海冰与大气环流进行超前滞后回归分析发现, 大气环流既是海冰异常的前兆因子同时也存在大气对海冰的滞后响应. 总体来说, 大气环流(如平流层极涡)异常超前于海冰异常的回归信号相对更强. 对海冰减退而言, 其前期中纬度涡动热通量出现显著正异常. 海冰减少和极盖位势高度是对前期中纬度强涡动热通量的响应. “极地热大陆冷”异常型也超前海冰减退异常1-2个月, 而在其之后消失, 表明欧亚冷异常和低海冰异常一样, 也是由中纬度强涡动热通量所控制. 本文结果还指出与大气环流异常相关的海冰异常的地理依赖性, 比如巴伦之海-喀拉海海冰减少之前往往出现平流层极涡减弱, 而鄂霍次克海海冰减少则对应着极涡增强. 总之, 从本文对大气超前一面的讨论结果而言, 海冰、平流层极涡和欧亚表面温度等的异常是对对流层大尺度大气环流的响应. (翻译:张鹏飞)

1. Introduction
  • Changes in Arctic sea ice have a direct impact on the local atmosphere and ocean in the region of ice loss; however, the remote impacts of changing sea ice are less well understood. As ice is lost, open ocean with lower albedo is exposed, giving rise to increased surface heat and moisture fluxes from the ocean into the atmosphere. This is hypothesized to weaken the equator-to-pole temperature gradient, thereby having an impact on midlatitude circulation. Multiple review papers, including (Cohen et al., 2014), (Vihma, 2014), (Walsh, 2014) and (Overland et al., 2016), have assembled the current status of our understanding of the interactions between Arctic sea ice and the atmosphere, both locally and remotely. (Overland et al., 2016) suggested a nonlinear dependence on the state of the atmosphere-ocean-sea-ice system that means not all changes in sea ice lead to the same atmospheric response. It should also be noted that while connections between Arctic and midlatitude weather have been demonstrated, the interannual variability is affected by many other factors, including sea surface temperatures and tropical teleconnections.

    The atmospheric geopotential height over the polar cap can be used to identify changes in circulation, and is strongly related to the mean temperature below a particular level. Changes in temperatures at lower levels can impact the atmosphere above through this relationship. The work by (Sun et al., 2015) showed that changes in sea ice can impact the mid-to-upper tropospheric and lower stratospheric circulation in an idealized model. This is supported by the results of (Peings and Magnusdottir, 2014), (Kim et al., 2014) and (Nakamura et al., 2016), among others, who identified a connection with the stratosphere. However, such studies were largely concerned with the response to low sea ice and did not explicitly consider the causes of low sea ice in the first instance. In the present study, we suggest that the atmospheric conditions that precede low sea ice can also weaken the polar stratospheric vortex directly.

    There is an established relationship between mid-tropospheric eddy meridional heat flux, which is the vertical component of Eliassen-Palm wave activity flux (Edmon et al., 1980), and stratospheric circulation (e.g., Newman and Nash, 2000; Sjoberg and Birner, 2012). Enhanced heat flux, or upward wave activity relative to climatology, over a period of a few months has been shown to be related to a weakened stratospheric polar vortex. Thereafter, changes in polar stratospheric circulation have been shown to enhance long time scale predictability in the troposphere (Baldwin and Dunkerton, 2001; Christiansen, 2001; Baldwin et al., 2003). As enhanced tropospheric meridional heat flux affects the stratosphere, and is also associated with midlatitude circulation anomalies that may affect sea ice, we speculate that midlatitude circulation anomalies associated with positive eddy heat flux anomalies can affect both Arctic sea ice and the stratospheric circulation directly, and then provide evidence for this speculation. This complicates the assessment of causality of sea-ice-stratosphere linkages, as both may be responding to eddy heat flux anomalies rather than the sea ice driving the stratosphere directly.

    A hypothesized impact of Arctic sea ice loss is the "warm Arctic, cold continent" pattern in surface temperatures. Work by (Mori et al., 2014) suggested that more frequent Eurasian blocking due to sea ice loss forces cold-air advection into the region and thus cooler Eurasian winters. In (Petoukhov and Semenov, 2010) a similar process was discussed, though the resulting pattern was found to be nonlinearly dependent on the degree of sea ice loss. The work of (McCusker et al., 2016) and (Sun et al., 2016), however, provided modelling evidence that while a warm Arctic is driven by sea ice loss, the cold continental temperature pattern may not be. (Sorokina et al., 2016) found a robust relationship between turbulent heat flux and Barents-Kara Sea ice using reanalysis data, though the link to cold continental temperatures was not apparent. As the "warm Arctic, cold continent" is a pattern that can be driven purely by internal variability, we attempt, by means of lead-lag regressions, to elucidate its temporal evolution and infer the directionality of the relationship between this pattern and Arctic sea ice.

    The atmospheric response to sea ice loss is likely to be sensitive to the geographical location of the ice anomalies. The results of (Petoukhov and Semenov, 2010), (Sun et al., 2015), (Koenigk et al., 2016), (Pedersen et al., 2016), (Screen, 2017b) and others suggest that different regions of ice loss have different response patterns. This is possibly related to the interference with the climatological mean planetary wave (Martius et al., 2009; Garfinkel et al., 2010; Smith et al., 2011), whereby constructive (destructive) interference between the forced and climatological planetary waves acts to enhance (suppress) vertical wave propagation. For this reason, the present study examines relationships with pan-Arctic anomalies as well as with regional sea ice anomalies.

    This paper seeks to further our understanding of the precursors of, and response to, Arctic sea ice loss, presenting evidence from CMIP5 climate models. The CMIP5 models have been a relatively underused resource in this regard, with the notable exception of (Boland et al., 2017). In contrast to (Boland et al., 2017), who examined historical and future scenarios, we focus on pre-industrial control simulations to examine the internal variability in the absence of forced trends. We are especially motivated to better understand the nature of the coupled two-way relationship between Arctic sea ice and the stratospheric polar vortex, and additionally between Arctic sea ice and cold winter temperatures over Eurasia, as present within the selected CMIP5 models.

2. Data and methods
  • The data used in this study are from the CMIP5 archive. Monthly means from the pre-industrial control simulations are used, as the purpose of the investigation is to examine relationships between sea ice and the atmosphere that occur as part of the natural climate variability. There are 34 models (Table 1) that have the required data available. We first examine this group as a whole, before then using a subset of models with different model genealogy (Knutti et al., 2013), which can be considered to be roughly independent of one another. The model subset is denoted with bold text in Table 1, and is selected such that one model per family is chosen and, where possible, similar horizontal resolutions are used. The results from this subset of models are qualitatively similar to those using the full set of models; however, there are quantitative differences in the magnitude of the regressions and their statistical significance. We argue that the non-independence of the models in the full set leads to overconfidence and, therefore, opt to use the smaller set of independent models here. Selected results from a similarly constructed set of high-top models are also presented. These demonstrate that the specific selection of models does not impact the results qualitatively.

    Time series of isobaric geopotential height and sea ice area (sea ice concentration multiplied by grid cell area) over the polar cap (66°-90°N), and zonal-mean meridional eddy heat flux (\(\overline{v'T'}\)) over 45°-65°N are calculated. This latitudinal band for the averaging of heat flux is different to that used in previous studies (e.g., Newman and Nash, 2000; Sjoberg and Birner, 2012) in order to separate the Arctic and midlatitudes, but this choice does not affect the results qualitatively. The time series of each variable is then used to calculate standardized climatological anomalies, \(x'=(\bar{x}-x)/s_x\), where \(\bar{x}\) and sx are the long-term monthly mean and standard deviation for the nearest 30 years to the modelled monthly variable x.

    The standardized sea ice area anomalies are regressed against the diagnostic variable anomalies at leads and lags of up to 14 months. To generate seasonal regressions, sea ice is masked such that only anomalies from each individual season are regressed against the atmospheric variables of all seasons. This means a lag of -3 in the December-January-February (DJF) mean is a mean of the regression of all December sea ice with September diagnostic variables, January sea ice with October diagnostic variables, and February sea ice with November diagnostic variables. In all plots, we show the negative regression slope, as this enables the association between the atmosphere and low sea ice conditions to be demonstrated. Statistical significance is calculated using Fisher's method (Kost and McDermott, 2002).

3. Results
  • We begin by looking at the linear regression between sea ice area and polar cap height at extended lead and lag times (Fig. 1) for the set of all CMIP5 models with data available. There are statistically significant regressions at both positive and negative lags, implying both atmospheric precursors of, and responses to, low sea ice. Positive (anticyclonic) anomalies are the dominant signal through most of the atmosphere, with significant anomalies at both positive and negative lag times. This indicates that low sea ice is preceded by, and followed by, tropospheric high geopotential height anomalies in the Arctic region. In general, the regressions are stronger when the atmosphere leads sea ice, which suggests that sea ice, at least initially, is not forcing the changes in the polar mid-to-upper troposphere and lower stratosphere. This is especially the case for low summer and low autumn sea ice, suggesting sea ice in these seasons is particularly sensitive to the atmospheric conditions in preceding months. However, there are statistically significant positive anomalies in polar cap height following low sea ice in all seasons, but especially in winter and spring, which suggests a weakening of the polar stratospheric vortex following low sea ice.

    Figure 2 is constructed in a similar manner to Fig. 1, but for the subset of independent models described in Table 1. There are some small but notable differences in the magnitude of the regressions (between the subset and full set), but the largest differences are in the areas of model agreement and statistical significance. Figure 3, showing the results from a subset of high-top (greater than 0.01 hPa) models, is similar to the previous two figures, with some key exceptions. The magnitudes of the regression slopes are higher, and all seasons show a statistically significant but weak negative anomaly in the early spring stratosphere. The latter may indicate a more persistent polar stratospheric vortex in spring, relative to the climatological mean transition to anticyclonic summer circulation. This could be a delay in the final stratospheric warming, the transition between winter (cyclonic) and summer (anticyclonic) stratospheric circulations, typically occurring in April. In general, the qualitative differences in the regressions are small (comparing the high-top subset and the full set), but the high-top subset has a smaller area of statistical significance and robustness compared to the full set. In the following figures, we show results only from the models of the first subset of independent models, as the differences between the two subsets and the full set are small. It should also be noted that the maximum regression slopes, as well as correlation coefficients, are small (maximums of 0.3), despite the relationship being robust across models and statistically significant. This is to be expected, as multiple factors influence atmospheric circulation in addition to sea ice.

    Figure 1.  Linear regression of standardized polar cap sea ice area anomalies against standardized polar cap geopotential height anomalies for each season for the full set of models. The regressions have been multiplied by minus one to show the patterns associated with low sea ice. Hatching covers areas not statistically significant at the 99% confidence level, while dots cover areas where fewer than 75% of models agree with the sign of the regression slope. Negative lags indicate atmosphere leading sea ice. The shading is unitless (standardized regression coefficient).

    Figure 2.  As in Fig. 1, but for the subset of eight selected models shown in Table 1.

    Figure 3.  As in Fig. 1, but for the subset of six selected high-top models shown in Table 1.

  • We now turn our attention to the midlatitude tropospheric meridional eddy heat flux (hereafter, "heat flux"), which is known to drive stratospheric variability and is the vertical component of the Eliassen-Palm flux. In all seasons, a statistically significant heat flux is found to precede anomalously low polar cap sea ice (Fig. 4). Enhanced heat flux is apparent in the lower troposphere for up to 6 months prior to low sea ice in winter and spring, and 12 months prior to low sea ice in summer and autumn. This strongly suggests that enhanced poleward heat flux contributes to the low sea ice anomalies. There is little evidence for the opposite——sea ice causing a change in the heat flux——with mostly insignificant regressions at positive lag times (i.e., following anomalously low ice). A positive heat flux is known to contribute to stratospheric polar vortex weakening. The heat flux anomalies preceding low sea ice are one likely cause of the enhanced polar cap height that also precedes low sea ice. Therefore, it is probable that the sea ice and polar cap height are both responding to this enhanced midlatitude heat flux——similar to the results of (Perlwitz et al., 2015) and (Screen et al., 2012) with respect to Arctic warming being driven by heat transport into the Arctic from lower latitudes.

    Figure 4.  As in Fig. 2 but for midlatitude meridional eddy heat flux standardized anomalies. The shading is unitless (standardized regression coefficient).

  • In previous work, low sea ice (and in some cases a weakened stratospheric polar vortex) has been proposed to cause the "warm Arctic, cold continent" winter temperature anomaly pattern. It has been argued that low Arctic sea ice causes warmer Arctic surface temperatures but cooler conditions over Eurasia and North America (Honda et al., 2009; Petoukhov and Semenov, 2010; Cohen et al., 2013; Mori et al., 2014; Kug et al., 2015). Figure 5 shows the lead-lag relationship between winter sea ice and Northern Hemisphere surface temperature. The CMIP5 models reproduce the "warm Arctic, cold continent" anomaly pattern at zero lag, with significant cold winter temperature anomalies over Eurasia correlated with low winter sea ice. This temperature anomaly pattern is also seen at a lag of -1 month and, to a lesser extent, at a lag of -2 months. This implies that both the Arctic warming and Eurasian cooling precede low winter sea ice.

    Figure 5.  Linear regression of winter (DJF) polar cap sea ice area standardized anomalies against standardized surface temperature anomalies between lag -1 months to lead +4 months. The regressions have been multiplied by minus one to show the patterns associated with low sea ice. Blue, dashed contours are cold anomalies; red, solid contours are warm anomalies. The shading is unitless (standardized regression coefficient).

    The warm anomaly in the Arctic is maximized over the Barents-Kara Sea and is present for at least two months before low winter sea ice. The progression of anomalously warm Arctic temperatures supports the results presented in the previous section, where warmer midlatitude air is transported to the Arctic, thereby reducing sea ice. The warm anomaly persists over the Barents-Kara Sea at lags of up to 3 months, likely in response to the low sea ice. The cool continental anomaly, however, is only present in the months before low sea ice, and not after. This implies the Eurasian cooling is not a response to low sea ice, but instead is driven by atmospheric circulation changes that precede and contribute to low sea ice. Of note is that we also find no evidence for Eurasian winter cooling following low sea ice in other seasons. More specifically, we find no evidence for Eurasian winter cooling following low autumn sea ice, as suggested by others (e.g., Francis et al., 2009; Hopsch et al., 2012; Jaiser et al., 2012).

  • To further examine the atmospheric circulation changes linked to the Eurasian cooling, we carry out the same analysis again but with sea level pressure. In the CMIP5 models, the Eurasian cooling is dynamically related to a strengthened Siberian high, consistent with previous studies (Mori et al., 2014; Sun et al., 2016). A high sea level pressure anomaly is found simultaneously with, and for two months prior to, low winter sea ice, which can be seen in Fig. 6. The strengthened Siberian high appears part of a larger-scale pattern of circulation anomalies, including a positive North Atlantic Oscillation (NAO)-type pattern in the North Atlantic and raised pressure in the North Pacific. The surface circulation anomalies are much weaker at positive lags, with the most notable feature being a negative NAO pattern at lags of 1 and 2 months. There is no evidence of a strengthened Siberian high following low sea ice, which helps explain the lack of Eurasian cooling following low winter sea ice.

    Figure 6.  As in Fig. 5 but for standardized mean sea level pressure anomalies. Red, solid contours are high pressure anomalies; blue, dashed contours are low pressure anomalies. The shading is unitless (standardized regression coefficient).

    Several studies have examined the Siberian winter cooling trend, some of which have found that sea ice loss is a precursor to cold continental temperatures (Petoukhov and Semenov, 2010; Mori et al., 2014). Others, meanwhile, have found that sea ice does not drive the cold continental temperatures, but does force a warming Arctic (McCusker et al., 2016; Sorokina et al., 2016; Sun et al., 2016). Our study falls into the latter category insofar as that, while there is evidence for sea ice loss as a precursor to warmer Arctic surface temperatures, the same cannot be said for cold continental temperatures. Thus far, the causes of the "warm Arctic, cold continent" pattern remain uncertain, as discussed in (Screen, 2017a).

    Figure 7.  Geographic regions used for spatial averaging of atmospheric and sea ice variables. Grey is the polar cap; Barents-Kara Sea in blue; Bering Sea in orange; Sea of Okhotsk in red; Greenland Sea in green.

  • As mentioned earlier, low ice in specific regions of the Arctic can impact the atmosphere in different ways. To examine these relationships, Arctic sea ice is partitioned into the marginal seas shown in Fig. 7, based on those previously used in (Screen, 2017b). Figures 8 and 9 show regressions of sea ice, averaged over the four selected polar seas, against the polar cap geopotential height and eddy heat flux, respectively. The regressions of Barents-Kara Sea winter sea ice with polar cap height (Fig. 8a) are similar to those previously shown for the pan-Arctic ice area, with positive polar cap height (Fig. 8a) and eddy heat flux (Fig. 9a) anomalies preceding low ice by 2-3 months, and positive polar cap height anomalies following low sea ice. However, in comparison to the regressions with the pan-Arctic sea ice area, the regressions against Barents-Kara Sea ice are weaker at negative lags and strong at positive lags. Broadly similar lead and lag regressions are found for low winter Greenland Sea ice (Figs. 8b and 9b). There are significant (mainly tropospheric) positive polar cap height and eddy heat flux anomalies preceding, and coincident with, low winter Bering Sea ice (Figs. 8c and 9c). The Sea of Okhotsk has a noticeably distinct pattern from the other seas, with a large negative polar cap height anomaly (Fig. 8d) and negative heat flux (Fig. 9d) in the 2-5 months prior to low ice. This indicates reduced vertical wave activity propagation into the stratosphere and a stronger polar vortex.

    Figure 8.  As in Fig. 2 but for winter (DJF) sea ice standardized anomalies in the (a) Barents-Kara Sea, (b) Bering Sea, (c) Greenland Sea and (d) Sea of Okhotsk.

    Figure 9.  As in Fig. 8 but for midlatitude meridional eddy heat flux standardized anomalies. The shading is unitless (standardized regression coefficient).

4. Conclusions
  • In this paper, we present a series of regressions of atmospheric variables against Arctic sea ice area at extended leads and lags using output from CMIP5 pre-industrial control simulations. We find statistically significant regressions at both positive and negative lags, suggesting both atmospheric precursors of, and responses to, low sea ice. Despite being robust across models and statistically significant, we note the regressions are fairly modest, suggesting Arctic sea is not the dominant driver of polar-cap-average circulation variability, or vice-versa. Nevertheless, midlatitude circulation anomalies in the form of enhanced meridional eddy heat flux do significantly influence Arctic sea ice area. We find that positive polar cap anomalies, reflecting a weaker polar stratospheric vortex, both precede low sea ice and, in some seasons, also follow low sea ice. Zonal mean meridional eddy heat flux anomalies are shown to be statistically significant prior to low sea ice, but weaker and not statistically significant following low sea ice. This suggests that midlatitude atmospheric circulation changes, which manifest as an increase in eddy heat flux, lead to changes in Arctic sea ice as well as a weakening of the polar stratospheric vortex. In this regard, our results provide support for previous studies that have suggested a sizeable component of Arctic mid-tropospheric thickness changes is driven by lower-latitude processes (Screen et al., 2012; Perlwitz et al., 2015). We argue that whilst low sea ice may enhance Arctic warming and further weaken the polar vortex, it appears that in the first instance both the low sea ice and weakened polar vortex are driven by the enhanced eddy heat flux. This is somewhat different to the conclusions of many studies reviewed by (Cohen et al., 2014), which hypothesized that reduced sea ice leads to enhanced wave propagation from the troposphere to the stratosphere and a weakened polar vortex.

    Figure 10.  As in Fig. 2, but for RCP8.5 simulations.

    As year-on-year variations in sea ice during the pre-industrial control simulations may be of different magnitude and spatial pattern to those projected in the future, a similar analysis is performed using detrended RCP8.5 projections from the primary subset of models in Table 1. As shown in Fig. 10, the results are qualitatively similar to those of the pre-industrial control simulations, which further emphasizes the robustness of the results.

    We find that low sea ice in winter is associated with warm winter surface temperatures over the Arctic and cold surface temperatures over Eurasia, consistent with previous studies using observations or reanalyses (Cohen et al., 2013; Mori et al., 2014; Kug et al., 2015). The Eurasian cooling is dynamically related to a strengthened Siberian high, again consistent with past work (Mori et al., 2014). Crucially however, we show that both the strengthened Siberian high and the Eurasian cooling are present several months before the low sea ice. In contrast, we find no evidence of a strengthened Siberian high or Eurasian cooling in the months following low winter sea ice. This suggests that the Eurasian cooling is driven by atmospheric circulation anomalies that precede and may contribute to low sea ice, but is not directly driven by low sea ice. This supports the conclusions of (Sato et al., 2014), (Sorokina et al., 2016), (Sun et al., 2016) and (McCusker et al., 2016), but is contrary to other studies that proposed a causal relationship between low sea ice and Eurasian cooling (Honda et al., 2009; Petoukhov and Semenov, 2010; Mori et al., 2014; Kug et al., 2015).

    Finally, we examine relationships between regional sea ice anomalies and polar cap height. Similar to (Sun et al., 2015), we find that low Atlantic sector sea ice, specifically in the Barents-Kara Sea, is correlated with a weakened stratospheric polar vortex; and low Pacific sector sea ice, specifically in the Sea of Okhotsk, is correlated with a strengthened polar vortex. In both cases, the polar cap height anomalies precede low sea ice by several months and are associated with meridional heat flux anomalies that also precede the low sea ice. Thus, our analyses suggest that modified meridional eddy heat flux could contribute simultaneously to both a perturbed polar vortex and low sea ice.

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