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We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.

Large sea ice loss on the synoptic time scale is examined in various subregions in the Arctic as well as at the pan-Arctic scale. It is found that the frequency of large daily sea ice loss (LDSIL) days is significantly correlated with the September sea ice extent over the Beaufort–Chukchi–Siberian Seas, the Laptev–Kara Seas, the central Arctic, and the all-Arctic regions, indicating a link between the synoptic sea ice variability and the interannual variability of the annual minimum sea ice extent. A composite analysis reveals dipoles of anomalous cyclones and anticyclones associated with LDSIL days. Different from the well-known Arctic dipole pattern, the east–west dipoles are found over the corresponding regions of LDSIL in the Arctic marginal seas and are associated with the increasing occurrence of Rossby wave breaking and atmospheric rivers. The anticyclones of the dipoles are persistent and quasi-stationary, reminiscent of blocking. The anomalous poleward flow between the cyclone and the anticyclone enhances the poleward transport of heat and water vapor in the lower troposphere. Although enhanced downward shortwave radiation, associated with reduced cloud fraction, is found in some regions, it is not collocated with the regions of LDSIL. In contrast, enhanced downward longwave radiation owing to increasing column water vapor shows good spatial correspondence with LDSIL, indicating the importance of atmospheric rivers in LDSIL events. Lead/lag composites with respect to the onset of LDSIL episodes reveal precursor wave trains spanning the midlatitudes. The wave trains have predominantly zonal energy propagation in the midlatitudes and do not show a clear link to tropical or subtropical forcing.

Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this study we use observational data to evaluate the contribution of the trend to the skill of persistence-based statistical forecasts of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea for which the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the winter and summer trends during the 1990s. Persistence-based statistical forecasts of the Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. In only a few regions does September ice extent correlate significantly with antecedent ice anomalies in the same region more than 2 months earlier. The springtime “predictability barrier” in regional forecasts based on persistence of ice extent anomalies is not reduced by the inclusion of several decades of pre-satellite data. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea's ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.

Wind is a climate variable with major impacts on humans, ecosystems and infrastructure, especially in coastal regions with cold climates. Climate-related changes in high-wind events therefore have major implications for high-latitude residents, yet there has heretofore been no systematic evaluation of such changes in a framework spanning historical and future timeframes. In this study, hourly winds from surface station reports and from dynamical downscaling of winds simulated by two different global climate models have been synthesized into historical and future wind climatologies for Alaska. Quantile mapping procedures are used to calibrate wind simulations driven by an atmospheric reanalysis, and the calibrated winds are then used to bias-adjust the full distributions of historical and future winds downscaled from the global climate models. In the resulting climatologies, winds are generally stronger at coastal and offshore (island) locations than at interior sites, where calm conditions are frequent in winter. The season of peak wind speed varies from winter in the coastal and offshore locations to summer in interior areas. High-wind events determined from the hourly data are most frequent during winter at coastal locations. Projected changes for the late 21st century are statistically significant at many locations, and they show a qualitatively similar seasonality in the output from the two models: an increase of mean wind speeds in the cold season and a decrease of mean wind speeds in the warm season. High-wind events are projected by both models to become more frequent in the northern and western Alaska coastal regions, which are precisely the regions in which the protective sea ice cover has decreased (and is projected to decrease further), pointing to increased risks of coastal flooding and erosion.

This talk will contrast how U.S. decision makers’ impacts-focused perspective on compound extreme events differs from climate science-based perspectives. Examples from around the U.S. will be provided, with an emphasis on cascading impacts that have spanned multiple regions and sectors. The talk will also propose a path forward for synthesizing ‘top-down’ and ‘bottom-up’ approaches to compound extremes, to facilitate adaptation. Time-permitting, preliminary findings from an analysis of sequential humid heat and extreme precipitation over the U.S. may be shown, as a guiding example. The work described reflects a collaboration of scientists funded by NOAA’s Regional Integrated Sciences and Assessments (RISA) program, charged with co-generating ‘useable science’ by working closely with stakeholders.

Global warming over the past half century has been amplified in the Arctic, especially in the cold season. Other Arctic indicators, especially those of the cryosphere, show signals consistent with the warming of the past half century. This Arctic amplification of the warming arises from a number of processes in the climate system, including the feedbacks associated with the loss of sea ice and snow, the increase of atmospheric moisture, and the vertical temperature structure of the Arctic atmosphere. Ocean heat fluxes into the Arctic from the North Atlantic and North Pacific also appear to have contributed to the Arctic warming through a reduction of sea ice. Internal variability, which played a major role in Arctic warming during the early twentieth century, appears to have been a minor contributor to the more recent warming, which has also been associated with unprecedented extremes of Arctic temperature and sea ice. There is evidence for increased moisture content of the Arctic atmosphere and corresponding impacts on episodes of extreme warmth. The recent variations of Arctic temperature and associated variables fit well with the simulations of Arctic climate by global and regional climate models. Projected changes include a continued warming of the Arctic even under moderate mitigation scenarios, and an increase of Arctic precipitation consistent with the higher temperatures and atmospheric humidities.

The greatest impacts of climate change on ecosystems, wildlife and humans often arise from extreme events rather than changes in climatic means. Northern high latitudes, including the Arctic, experience a variety of climate-related extreme events, yet there has been little attempt to synthesize information on extreme events in this region. This review surveys work on various types of extreme events in northern high latitudes, addressing (1) the evidence for variations and changes based on analyses of recent historical data and (2) projected changes based primarily on studies utilizing global climate models. The survey of extreme weather and climate events includes temperature, precipitation, snow, freezing rain, atmospheric blocking, cyclones, and wind. The survey also includes cryospheric and biophysical impacts: sea ice rapid loss events, Greenland Ice Sheet melt, floods, drought, wildfire, coastal erosion, terrestrial ecosystems, and marine ecosystems. Temperature and sea ice rank at the high end of the spectra of evidence for change and confidence in future change, while drought, flooding and cyclones rank at the lower end. Research priorities identified on the basis of this review include greater use of high-resolution models and observing system enhancements that target extreme events. There is also a need for further work on attribution, impacts on ecosystems and humans, and thresholds or tipping points that may be triggered by extreme events in high latitudes. Key words: climate, weather, extremes, storms, northern regions

Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. The indices include the number of false freeze-ups defined by transient exceedances of ice concentration prior to a corresponding exceedance that persists, false break-ups, timing of freeze-up and break-up, length of the open water duration, number of days when the winds preclude hunting via boat (wind speed threshold exceedances), the number of wind events conducive to geomorphological work or damage to infrastructure from ocean waves, and the number of these wind events with on- and along-shore components promoting water setup along the coastline. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices. The two primary large-scale datasets are the Historical Sea Ice Atlas for Alaska and the atmospheric output from a regional climate model used to downscale the ERA-Interim atmospheric reanalysis. We illustrate the variability and trends of these indices by application to the rural Alaska communities of Kotzebue, Shishmaref, and Utqiaġvik (previously Barrow), although the same procedure and metrics can be applied to other coastal communities. Over the 1979–2014 time period, there has been a marked increase in the number of combined false freeze-ups and false break-ups as well as the number of days too windy for hunting via boat for all three communities, especially Utqiaġvik. At Utqiaġvik, there has been an approximate tripling of the number of wind events conducive to coastline erosion from 1979 to 2014. We have also found a delay in freeze-up and earlier break-up, leading to a lengthened open water period for all of the communities examined.

High winds cause waves, storm surge, erosion and physical damage to infrastructure and ecosystems. However, there have been few evaluations of wind climatologies and future changes, especially change in high-wind events, on a regional basis. This study uses Alaska as a regional case study of climatological wind speed and direction. Eleven first-order stations across different subregions of Alaska provide historical data (1975-2005) for the observational climatology and for the calibration of Coupled Model Inter comparison Project (CMIP5) simulations, which in turn provide projections of changes in winds through 2100. Historically, winds exceeding 25 and 35 knots are most common in the Bering Sea coastal region of Alaska, followed by northern Alaska coastal areas. Autumn and winter are the seasons of most frequent high-wind occurrences in the coastal sites, while there is no distinct seasonal peak at the interior stations where high-wind events are less frequent. An examination of the sea level pressure pattern associated with the highest-wind event at each station reveals the presence of a strong pressure gradient associated with an extratropical cyclone in most cases. Northern coastal regions of Alaska are projected to experience increased frequencies of high-wind events during the cold season, especially late autumn and early winter, when reduced sea ice cover in the late century will leave coastal regions increasingly vulnerable to flooding and erosion.

This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.

Alaska experienced record-setting warmth during the 2015/16 cold season (October–April). Statewide average temperatures exceeded the period-of-record mean by more than 4°C over the 7-month cold season and by more than 6°C over the 4-month late-winter period, January–April. The record warmth raises two questions: 1) Why was Alaska so warm during the 2015/16 cold season? 2) At what point in the future might this warmth become typical if greenhouse warming continues? On the basis of circulation analogs computed from sea level pressure and 850-hPa geopotential height fields, the atmospheric circulation explains less than half of the anomalous warmth. The warming signal forced by greenhouse gases in climate models accounts for about 1°C of the anomalous warmth. A factor that is consistent with the seasonal and spatial patterns of the warmth is the anomalous surface state. The surface anomalies include 1) above-normal ocean surface temperatures and below-normal sea ice coverage in the surrounding seas from which air advects into Alaska and 2) the deficient snowpack over Alaska itself. The location of the maximum of anomalous warmth over Alaska and the late-winter–early-spring increase of the anomalous warmth unexplained by the atmospheric circulation implicates snow cover and its albedo effect, which is supported by observational measurements in the boreal forest and tundra biomes. Climate model simulations indicate that warmth of this magnitude will become the norm by the 2050s if greenhouse gas emissions follow their present scenario.

Arctic sea ice data from a variety of historical sources have been synthesized into a database extending back to 1850 with monthly time‐resolution. The synthesis procedure includes interpolation to...

Key observational indicators of climate change in the Arctic, most spanning a 47 year period (1971–2017) demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion that increasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near‐coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO2 uptake, with counterbalancing increases in shoulder season and winter CO2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no. Key indicators of Arctic climate change: 1971–2017

Alaska is experiencing effects of global climate change that are due, in large part, to the positive feedback mechanisms associated with polar amplification. The major risk factors include loss of sea ice and glaciers, thawing permafrost, increased wildfires, and ocean acidification. Reanalyses, integral to understanding mechanisms of Alaska’s past climate and to helping to calibrate modeling efforts, are based on the output of weather forecast models that assimilate observations. This study evaluates temperature and precipitation from five reanalyses at monthly and daily time scales for the period 1979–2009. Monthly data are evaluated spatially at grid points and for six climate zones in Alaska. In addition, daily maximum temperature, minimum temperature, and precipitation from reanalyses are compared with meteorological-station data at six locations. The reanalyses evaluated in this study include the NCEP–NCAR reanalysis (R1), North American Regional Reanalysis (NARR), Climate Forecast System Reanalysis (CFSR), ERA-Interim, and the Modern-Era Retrospective Analysis for Research and Applications (MERRA). Maps of seasonal bias and standard deviation, constructed from monthly data, show how the reanalyses agree with observations spatially. Cross correlations between the monthly gridded and daily station time series are computed to provide a measure of confidence that data users can assume when selecting reanalysis data in a region without many surface observations. A review of natural hazards in Alaska indicates that MERRA is the top reanalysis for wildfire and interior-flooding applications. CFSR is the recommended reanalysis for North Slope coastal erosion issues and, along with ERA-Interim, for heavy precipitation in southeastern Alaska.

Metrics of storm activity in Northern Hemisphere high and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December) – the period when the ongoing and projected Arctic sea ice retreat is the greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks show indications of shifting polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high latitudes, especially the Baffin Bay/Davis Strait region in September. Autumn precipitation is projected to increase significantly across the entire high latitudes. Together with the projected loss of sea ice and increases in storm intensity and sea level, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.

Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. However, the strong negative trend of sea ice coverage in recent decades complicates the evaluation of statistical skill by inflating the correlation of interannual variations of pan-Arctic and regional ice extent. In this study we provide a quantitative evaluation of the contribution of the trend to the predictive skill of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea where the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the trend during the 1990s in most of the Arctic subregions. The Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical predictability out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea’s ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.

This manuscript presents an evaluation of global climate models to guide future projections of Arctic sea ice extent (SIE). Thirty-five model simulations from Coupled Model Intercomparison Project, Phase 5 were examined to select model subsets using comparison to observational data (1979–2013). The study extends previous work by highlighting the seasonality of sea ice trends, utilizing a multi-step selection process to demonstrate how the timing of an ice-free Arctic varies with the hindcast performance of the models, and extending the analysis to include sudden ice loss events (SILE). Although the models' trends for the historical period are generally smaller than observed, the models' projected trends show a similar seasonality, largest in September and smallest in March to April. A multi-step evaluation process is applied to obtain progressively smaller subsets of the best-performing models. As the number of models retained becomes smaller, the simulated historical trend becomes larger and the median d...

It is often remarked that Arctic coastal communities are on the frontlines of the impacts related to the rapidly diminishing ice pack. These impacts can have direct effects on communities, such as reduced access to subsistence hunting species, or increased wave height and coastal erosion. There are also indirect effects driven by external socioeconomic systems, such as increased maritime activity, which may provide local economic benefits while increasing potential for disruption to subsistence activities. Here, we use the Historical Sea Ice Atlas (HSIA) dataset to assess the potential direct and indirect impacts from sea ice change for selected Alaska communities. The HSIA provides sea ice concentration for the Bering, Chukchi and Beaufort Seas on a 0.25-degree grid for the period 1953–2013. We estimate the timing of freeze-up and break-up, which is reported by local residents to be of critical importance for subsistence hunting activities and food security. We calculate the open water season length and extend the existing timeseries of the Barnett Severity Index (BSI), which assesses the impact of ice conditions on maritime traffic destined for the Beaufort Sea. We find consistent trends toward later freeze-up and earlier break-up, leading to a lengthened open water period. In Utqiavik (formerly Barrow), there is evidence of a navigational regime change in the 1990s when the pack ice edge started to routinely retreat beyond this most northern community.

Arctic sea ice decline has led to an amplification of surface warming and is projected to continue to decline from anthropogenic forcing, although the exact timing of ice-free summers is uncertain owing to large natural variability. Sea ice reductions affect surface heating patterns and the atmospheric pressure distribution, which may alter midlatitude extreme weather patterns. Increased light penetration and nutrient availability during spring from earlier ice breakup enhances primary production in the Arctic Ocean and its adjacent shelf seas. Ice-obligate marine mammals may be losers, whereas seasonally migrant species may be winners from rapid sea ice decline. Tundra greening is occurring across most of the Arctic, driven primarily by warming temperatures, and is displaying complex spatial patterns that are likely tied to other factors. Sea ice changes are affecting greenhouse gas exchanges as well as halogen chemistry in the Arctic. This review highlights the heterogeneous nature of Arctic change, which is vital for researchers to better understand.

Over 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.

The climate in the Arctic is changing faster than in midlatitudes. This is shown by increased temperatures, loss of summer sea ice, earlier snow melt, impacts on ecosystems, and increased economic access. Arctic sea ice volume has decreased by 75% since the 1980s. Long-lasting global anthropogenic forcing from carbon dioxide has increased over the previous decades and is anticipated to increase over the next decades. Temperature increases in response to greenhouse gases are amplified in the Arctic through feedback processes associated with shifts in albedo, ocean and land heat storage, and near-surface longwave radiation fluxes. Thus, for the next few decades out to 2040, continuing environmental changes in the Arctic are very likely, and the appropriate response is to plan for adaptation to these changes. For example, it is very likely that the Arctic Ocean will become seasonally nearly sea ice free before 2050 and possibly within a decade or two, which in turn will further increase Arctic temperatures, economic access, and ecological shifts. Mitigation becomes an important option to reduce potential Arctic impacts in the second half of the 21st century. Using the most recent set of climate model projections (CMIP5), multimodel mean temperature projections show an Arctic-wide end of century increase of +13°C in late fall and +5°C in late spring for a business-as-usual emission scenario (RCP8.5) in contrast to +7°C in late fall and +3°C in late spring if civilization follows a mitigation scenario (RCP4.5). Such temperature increases demonstrate the heightened sensitivity of the Arctic to greenhouse gas forcing.

Although much remains to be learned about the Arctic and its component processes, many of the most urgent scientific, engineering, and social questions can only be approached through a broader system perspective. Here, we address interactions between components of the Arctic system and assess feedbacks and the extent to which feedbacks (1) are now underway in the Arctic and (2) will shape the future trajectory of the Arctic system. We examine interdependent connections among atmospheric processes, oceanic processes, sea-ice dynamics, marine and terrestrial ecosystems, land surface stocks of carbon and water, glaciers and ice caps, and the Greenland ice sheet. Our emphasis on the interactions between components, both historical and anticipated, is targeted on the feedbacks, pathways, and processes that link these different components of the Arctic system. We present evidence that the physical components of the Arctic climate system are currently in extreme states, and that there is no indication that the system will deviate from this anomalous trajectory in the foreseeable future. The feedback for which the evidence of ongoing changes is most compelling is the surface albedo-temperature feedback, which is amplifying temperature changes over land (primarily in spring) and ocean (primarily in autumn-winter). Other feedbacks likely to emerge are those in which key processes include surface fluxes of trace gases, changes in the distribution of vegetation, changes in surface soil moisture, changes in atmospheric water vapor arising from higher temperatures and greater areas of open ocean, impacts of Arctic freshwater fluxes on the meridional overturning circulation of the ocean, and changes in Arctic clouds resulting from changes in water vapor content.

This study is a broad-scale synthesis of information on climate changes in two Arctic terrestrial regions, eastern Siberia and the Alaska–Yukon area of North America. Over the past 60 years (1951–2010), the trends of temperature and precipitation in the two regions are broadly similar in their seasonality. However, atmospheric advection influences the two regions differently during winter. The differential advective effects are much weaker in the other seasons. The Pacific Decadal Oscillation is the strongest correlator with interannual variability in the two regions, followed by the Arctic Oscillation and the El Nino/Southern Oscillation. Projected changes by the late 21st Century are qualitatively similar to the changes that have been ongoing over the past 60 years, although the rate of change increases modestly under mid-range forcing scenarios (e.g., the A1B scenario). The greatest warming is projected to occur farther north over the Arctic Ocean in response to sea ice loss. Precipitation is projected to increase by all models, although increases in evapotranspiration preclude conclusions about trends toward wetter or drier land surface conditions. A notable feature of the future climate simulations is a strong maximum of pressure decreases in the Bering Sea region, implying further advective changes.

Sea ice has emerged as the canary in the coal mine of climate change. Its summer extent in the Arctic has decreased by about 50% over the past decade, and the Arctic Ocean has undergone a regime shift from a cover of thick multiyear ice to a largely seasonal and much thinner ice cover. The recent loss is unprecedented in the periods of satellite and historical records of sea ice, and it also appears to be unique in paleo reconstructions spanning more than a thousand years. A "perfect storm" of warmer atmospheric and oceanic forcing, together with a boost from natural variability of wind forcing in some years, drove the change. However, the reduction of ice coverage is not apparent in some sub-Arctic regions during the winter, nor has it occurred in the Antarctic region.Signals of a response to the loss of sea ice are emerging in the ocean and the atmosphere. Ocean heat storage during the ice-free season not only contributes to a later freeze-up than in the past, but it also reduces the thickness to which first-year ice can grow. The vulnerability of this thinner ice to rapid spring melt is a manifestation of the ice-albedo-temperature feedback that has long been postulated as a contributor to polar amplification of climate change. More notably for middle latitudes, the loss of sea ice appears to be triggering a reduction of the large-scale westerlies that characterize atmospheric circulation in middle and subpolar latitudes. This response is consistent with increased persistence of departures from normal temperature, precipitation, and extreme weather during autumn and winter in heavily populated areas of the Northern Hemisphere.

There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

Alaska encompasses several climate types because of its vast size, high-latitude location, proximity to oceans, and complex topography. There is a great need to understand how climate varies regionally for climatic research and forecasting applications. Although climate-type zones have been established for Alaska on the basis of seasonal climatological mean behavior, there has been little attempt to construct climate divisions that identify regions with consistently homogeneous climatic variability. In this study, cluster analysis was applied to monthly-average temperature data from 1977 to 2010 at a robust set of weather stations to develop climate divisions for the state. Mean-adjusted Advanced Very High Resolution Radiometer surface temperature estimates were employed to fill in missing temperature data when possible. Thirteen climate divisions were identified on the basis of the cluster analysis and were subsequently refined using local expert knowledge. Divisional boundary lines were drawn that encompass the grouped stations by following major surrounding topographic boundaries. Correlation analysis between station and gridded downscaled temperature and precipitation data supported the division placement and boundaries. The new divisions north of the Alaska Range were the North Slope, West Coast, Central Interior, Northeast Interior, and Northwest Interior. Divisions south of the Alaska Range were Cook Inlet, Bristol Bay, Aleutians, Northeast Gulf, Northwest Gulf, North Panhandle, Central Panhandle, and South Panhandle. Correlations with various Pacific Ocean and Arctic climatic teleconnection indices showed numerous significant relationships between seasonal division average temperature and the Arctic Oscillation, Pacific–North American pattern, North Pacific index, and Pacific decadal oscillation.

The Arctic and the surrounding region of the sub-Arctic represent a key area for the study of global change because the anthropogenic impact, particularly the rate of warming, is projected to be the greatest in any part of the world due to the complicated feedback processes which occur. This Arctic region has undergone very large changes in recent years due to global warming, and accelerated change is predicted. The rapid changes that are occurring in the Arctic, and that have been the topic of the ISAR-1 and ISAR-2 conferences, manifest themselves at a number of scales. The large scales are Arctic-wide changes in key environmental parameters, which are described in a series of papers in this issue. On a more subtle scale we see changes to species and to biological processes in the Arctic. We hope that readers will enjoy the range of papers published in this issue, and will appreciate that phenomena ranging in scale from global radiation balance to clutch size of birds' eggs are actually all related via the central fact of the present-day Arctic, its high rate of warming.

aMerICaN MeTeOrOLOGICaL SOCIeTy | 145 AffiliAtions: Polyakov and Walsh—International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, Alaska; kWok—Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California CoRREsPonDinG AUtHoR: Igor V. Polyakov, International Arctic Research Center, University of Alaska Fairbanks, P.O. Box 757335, Fairbanks, AK 99775 E-mail: igor@iarc.uaf.edu

During the past decade, the Arctic has experienced its highest temperatures of the instrumental record, even exceeding the warmth of the 1930s and 1940s. Recent paleo-reconstructions also show that recent Arctic summer temperatures are higher than at any time in the past 2000 years. The geographical distribution of the recent warming points strongly to an influence of sea ice reduction. The spatial pattern of the near-surface warming also shows the signature of the Pacific Decadal Oscillation in the Pacific sector as well as the influence of a dipole-like circulation pattern in the Atlantic sector. Areally averaged Arctic precipitation over the land areas north of 55°N shows large year-to-year variability, superimposed on an increase of about 5% since 1950. The years since 2000 have been wetter than average according to both precipitation and river discharge data. There are indications of increased cloudiness over the Arctic, especially low clouds during the warm season, consistent with a longer summer and a reduction of summer sea ice. Storm events and extreme high temperature show signs of increases. The Arctic Ocean has experienced enhanced oceanic heat inflows from both the North Atlantic and the North Pacific. The Pacific inflows evidently played a role in the retreat of sea ice in the Pacific sector of the Arctic Ocean, while the Atlantic water heat influx has been characterized by increasingly warm pulses. Recent shipboard observations show increased ocean heat storage in newly sea-ice-free ocean areas, with increased influence on autumn atmospheric temperature and wind fields.

The Arctic cryosphere is a critically important component of the earth system, affecting the energy balance, atmospheric and ocean circulation, freshwater storage, sea level, the storage, and release of large quantities of greenhouse gases, economy, infrastructure, health, and indigenous and non-indigenous livelihoods, culture and identity. Currently, components of the Arctic cryosphere are subjected to dramatic change due to global warming. The need to document, understand, project, and respond to changes in the cryosphere and their consequences stimulated a comprehensive international assessment called “SWIPA”: Snow, Water, Ice, Permafrost in the Arctic. Some of the extensive key SWIPA chapters have been summarized and made more widely available to a global audience with multi-disciplinary interests in this Special Report of Ambio. In this article, an overview is provided of this Special Report in the context of the more detailed and wider scope of the SWIPA Report. Accelerated changes in major components of the Arctic cryosphere are documented. Evidence of feedback mechanisms between the cryosphere and other parts of the climate system are identified as contributing factors to enhanced Arctic warming while the growing importance of Arctic land-based ice as a contributor to global sea-level rise is quantified. Cryospheric changes will result in multifaceted and cascading effects for people within and beyond the Arctic presenting both challenges and opportunities.

Over the period of modern satellite observations, Arctic sea-ice extent at the end of the melt season (September) has declined at a rate of >11% per decade, and there is evidence that the rate of decline has accelerated during the last decade. While climate models project further decreases in sea- ice mass and extent through the 21st century, the model ensemble mean trend over the period of instrumental records is smaller than observed. Possible reasons for the apparent discrepancy between observations and model simulations include observational uncertainties, vigorous unforced climate variability in the high latitudes, and limitations and shortcomings of the models stemming in particular from gaps in understanding physical process. The economic significance of a seasonally sea-ice-free future Arctic, the increased connectivity of a warmer Arctic with changes in global climate, and large uncertainties in magnitude and timing of these impacts make the problem of rapid sea-ice loss in the Arctic a grand challenge of climate science. Meaningful prediction/projection of the Arctic sea-ice conditions for the coming decades and beyond requires determining priorities for observations and model development, evaluation of the ability of climate models to reproduce the observed sea-ice behavior as a part of the broader climate system, improved attribution of the causes of Arctic sea-ice change, and improved understanding of the predictability of sea-ice conditions on seasonal through centennial timescales in the wider context of the polar climate predictability.

About 75% of 46 glaciers measured using repeat airborne altimetry in Alaska and northwestern Canada have been losing mass at an increasing rate from the mid-1990s to the middle of the first decade of the twenty-first century, relative to an earlier period beginning in the 1950s–70s. The remaining glaciers have been either gaining mass during the more recent period or continuing to lose mass, but at a decreasing rate. Temperature and precipitation data at 67 climate stations were examined to explain these changes. Nearly all significant changes in winter (October–April) and summer (May–September) air temperatures were positive (2.0° ± 0.8° and 1.0° ± 0.4°C) between 1950 and 2002, and all seasonally averaged values of freezing level heights (FLH) increased during the same time period. A small increase in precipitation was observed, but these changes were significant at only 17% of the stations. Regional glacier changes, modeled using mass balance sensitivities and climate station temperature and precipitation changes, agreed with observations to within the limits of reported errors. Seasonal variations in accumulation resulted in large uncertainties in the recent period mass variations. In nearly all regions, increasing summer temperatures accounted for most of the glacier mass losses. FLH variations show that the maritime glacier systems are more sensitive to variations in the mean position of the winter FLH than interior regions, suggesting that strong winter warming has affected these regions in addition to the summer changes. These measurements augment the increasingly strong evidence of late twentieth-century climate change in northwestern North America.

Ongoing climate variations in the Arctic and Antarctic pose an apparent paradox. In contrast to the large warming and loss of sea ice in the Arctic in recent decades, Antarctic temperatures and sea ice show little change except for the Antarctic Peninsula. However, model simulations indicate that the Arctic changes have been shaped largely by low-frequency variations of the atmospheric circulation, superimposed on a greenhouse warming that is apparent in model simulations when ensemble averages smooth out the circulation-driven variability of the late 20th century. By contrast, the Antarctic changes of recent decades appear to be shaped by ozone depletion and an associated strengthening of the southern annular mode of the atmospheric circulation. While the signature of greenhouse-driven change is projected to emerge from the natural variability during the present century, the emergence of a statistically significant greenhouse signal may be slower than in other regions. Models suggest that feedbacks from retreating sea ice will make autumn and winter the seasons of the earliest emergence of the greenhouse signal in both Polar Regions. Priorities for enhanced robustness of the Antarctic climate simulations are the inclusion of ozone chemistry and the realistic simulation of water vapour over the Antarctic Ice Sheet.

Monthly surface air temperatures from land surface stations, automatic weather stations, and ship/buoy observations from the high-latitude Southern Hemisphere are synthesized into gridded analyses at a resolution appropriate for applications ranging from spatial trend analyses to climate change impact assessments. Correlation length scales are used to enhance information content while limiting the spatial extent of influence of the sparse data in the Antarctic region. The correlation length scales are generally largest in summer and over the Antarctic continent, while they are shortest over the winter sea ice. Gridded analyses of temperature anomalies, limited to regions within a correlation length scale of at least one observation, are constructed and validated against observed temperature anomalies in single-station-out experiments. Trends calculated for the 1958–2002 period suggest modest warming over much of the 60°–90°S domain. All seasons show warming, with winter trends being the largest at +0.172°C decade−1 while summer warming rates are only +0.045°C decade−1. The 45-yr temperature trend for the annual means is +0.082°C decade−1 corresponding to a +0.371°C temperature change over the 1958–2002 period of record. Trends computed using these analyses show considerable sensitivity to start and end dates, with trends calculated using start dates prior to 1965 showing overall warming, while those using start dates from 1966 to 1982 show net cooling over the region. Because of the large interannual variability of temperatures over the continental Antarctic, most of the continental trends are not statistically significant. However, the statistically significant warming over the Antarctic Peninsula is the strongest and most seasonally robust in the spatial patterns of temperature change. Composite (11-model) global climate model (GCM) simulations for 1958–2002 with forcing from historic aerosol and greenhouse gas concentrations show warming patterns and magnitudes similar to the corresponding observed trends for the 45-yr period. GCM projections for the rest of the twenty-first century, however, discontinue the pattern of strongest warming over the Antarctic Peninsula, but instead show the strongest warming over the Antarctic continent.

Ensembles of simulations of the twentieth- and twentyfirst-century climate, performed with 20 coupled models for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment, provide the basis for an evaluation of the Arctic (70°–90°N) surface energy budget. While the various observational sources used for validation contain differences among themselves, some model biases and across-model differences emerge. For all energy budget components in the twentieth-century simulations (the 20C3M simulation), the across-model variance and the differences from observational estimates are largest in the marginal ice zone (Barents, Kara, Chukchi Seas). Both downward and upward longwave radiation at the surface are underestimated in winter by many models, and the ensenmble mean annual net surface energy loss by longwave radiation is 35 W/m2, which is less than for the NCEP and ERA40 reanalyses but in line with some of the satellite estimates. Incoming solar radiation is overestimated by the models in spring and underestimated in summer and autumn. The ensemble mean annual net surface energy gain by shortwave radiation is 39 W/m2, which is slightly less than for the observational based estimates, In the twentyfirst-century simulations driven by the SRES A2 scenario, increased concentrations of greenhouse gasses increase (average for 2080–2100 minus average for 1980–2000 averages) the annual average ensemble mean downward longwave radiation by 30.1 W/m2. This was partly counteracted by a 10.7 W/m2 reduction in downward shortwave radiation. Enhanced sea ice melt and increased surface temperatures increase the annual surface upward longwave radiation by 27.1 W/m2 and reduce the upward shortwave radiation by 13.2 W/m2, giving an annual net (shortwave plus longwave) surface radiation increase of 5.8 W/m2 , with the maximum changes in summer. The increase in net surface radiation is largely offset by an increased energy loss of 4.4 W/m2 by the turbulent fluxes.

Simulations of Arctic surface air temperature and sea level pressure by 14 global climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are synthesized in an analysis of biases and trends. Simulated composite GCM surface air temperatures for 1981–2000 are generally 1°–2°C colder than corresponding observations with the exception of a cold bias maximum of 6°–8°C in the Barents Sea. The Barents Sea bias, most prominent in winter and spring, occurs in 12 of the 14 GCMs and corresponds to a region of oversimulated sea ice. All models project a twenty-first-century warming that is largest in the autumn and winter, although the rates of the projected warming vary considerably among the models. The across-model and across-scenario uncertainties in the projected temperatures are comparable through the first half of the twenty-first century, but increases in variability associated with the choice of scenario begin to outpace increases in across-model variability by about the year 2070. By the end of the twenty-first century, the cross-scenario variability is about 50% greater than the across-model variability. The biases of sea level pressure are smaller than in the previous generation of global climate models, although the models still show a positive bias of sea level pressure in the Eurasian sector of the Arctic Ocean, surrounded by an area of negative pressure biases. This bias is consistent with an inability of the North Atlantic storm track to penetrate the Eurasian portion of the Arctic Ocean. The changes of sea level pressure projected for the twenty-first century are negative over essentially the entire Arctic. The most significant decreases of pressure are projected for the Bering Strait region, primarily in autumn and winter.

We contrast recent climatic and environmental changes and their causes in the Arctic and the Antarctic. There are continuing increases in surface temperatures, losses of sea ice and tundra, and warming of permafrost over broad areas of the Arctic, while most of the major increase in Antarctic temperatures is on the Antarctic Peninsula associated with sea ice loss in the Bellingshausen-Amundsen Seas sector. While both natural atmospheric and oceanic variability, and changes in external forcing including increased greenhouse gas concentrations, must be considered in the quest for understanding such changes, the interactions and feedbacks between system components are particularly strong at high latitudes. For the 1950s to date in the Arctic and for 1957 to date in the Antarctic, positive trends in large-scale atmospheric circulation represented by the Arctic oscillation (AO) and Antarctic oscillations (AAO) and the Pacific North American (PNA) pattern contribute to the long-term temperature trends. However, continuing Arctic trends during the last decade of near neutral AO will require alternate explanations. The trend in the AAO since 1950 is larger than expected from natural variability and may be associated with the decrease in stratospheric ozone over Antarctic. The persistence shown in many Arctic and Antarctic Peninsula components of climate and their influence through possible feedback supports continuation of current trends over the next decade. One can expect large spatial and temporal differences, however, from the relative contributions of intrinsic variability, external forcing, and internal feedback/amplifications. It is particularly important to resolve regional feedback processes in future projections based on modeling scenarios.

Manifold changes in the freshwater cycle of high-latitude lands and oceans have been reported in the past few years. A synthesis of these changes in freshwater sources and in ocean freshwater storage illustrates the complementary and synoptic temporal pattern and magnitude of these changes over the past 50 years. Increasing river discharge anomalies and excess net precipitation on the ocean contributed approximately 20,000 cubic kilometers of fresh water to the Arctic and high-latitude North Atlantic oceans from lows in the 1960s to highs in the 1990s. Sea ice attrition provided another approximately 15,000 cubic kilometers, and glacial melt added approximately 2000 cubic kilometers. The sum of anomalous inputs from these freshwater sources matched the amount and rate at which fresh water accumulated in the North Atlantic during much of the period from 1965 through 1995. The changes in freshwater inputs and ocean storage occurred in conjunction with the amplifying North Atlantic Oscillation and rising air temperatures. Fresh water may now be accumulating in the Arctic Ocean and will likely be exported southward if and when the North Atlantic Oscillation enters into a new high phase.

The sea ice simulations by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models for the climate of the twentieth century and for global warming scenarios have been synthesized. A large number of model simulations realistically captured the climatological annual mean, seasonal cycle, and temporal trends of sea ice area over the Northern Hemisphere during 1979–99, although there is considerable scatter among the models. In particular, multimodel ensemble means show promising estimates very close to observations for the late twentieth century. Model projections for the twenty-first century demonstrate the largest sea ice area decreases generally in the Special Report on Emission Scenarios (SRES) A1B and A2 scenarios compared with the B1 scenario, indicating large multimodel ensemble mean reductions of −3.54 ± 1.66 × 105 km2 decade−1 in A1B, −4.08 ± 1.33 × 105 km2 decade−1 in A2, and −2.22 ± 1.11 × 105 km2 decade−1 in B1. The corresponding percentage reductions are 31.1%, 33.4%, and 21.6% in the last 20 yr of the twenty-first century, relative to 1979–99. Furthermore, multiyear ice coverage decreases rapidly at rates of −3.86 ± 2.07 × 105 km2 decade−1 in A1B, −4.94 ± 1.91 × 105 km2 decade−1 in A2, and −2.67 ± 1.7107 × 105 km2 decade−1 in B1, making major contributions to the total ice reductions. In contrast, seasonal (first year) ice area increases by 1.10 ± 2.46 × 105 km2 decade−1, 1.99 ± 1.47 × 105 km2 decade−1, and 1.05 ± 1.9247 × 105 km2 decade−1 in the same scenarios, leading to decreases of 59.7%, 65.0%, and 45.8% of the multiyear ice area, and increases of 14.1%, 27.8%, and 11.2% of the seasonal ice area in the last 20 yr of this century. Statistical analysis shows that many of the models are consistent in the sea ice change projections among all scenarios. The results include an evaluation of the 99% confidence interval of the model-derived change of sea ice coverage, giving a quantification of uncertainties in estimating sea ice changes based on the participating models. Hence, the seasonal cycle of sea ice area is amplified and an increased large portion of seasonally ice-covered Arctic Ocean is expected at the end of the twenty-first century. The very different changes of multiyear and seasonal ice may have significant implications for the polar energy and hydrological budgets and pathways.

This paper identified an atmospheric circulation anomaly–dipole structure anomaly in the Arctic atmosphere and its relationship with winter sea ice motion, based on the International Arctic Buoy Program (IABP) dataset (1979–98) and datasets from the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) for the period 1960–2002. The dipole anomaly corresponds to the second-leading mode of EOF of monthly mean sea level pressure (SLP) north of 70°N during the winter season (October–March) and accounts for 13% of the variance. One of its two anomalous centers is stably occupied between the Kara Sea and Laptev Sea; the other is situated from the Canadian Archipelago through Greenland extending southeastward to the Nordic seas. The dipole anomaly differs from one described in other papers that can be attributed to an eastward shift of the center of action of the North Atlantic Oscillation. The finding shows that the dipole anomaly also differs from the “Barents Oscillation” revealed in a study by Skeie. Since the dipole anomaly shows a strong meridionality, it becomes an important mechanism to drive both anomalous sea ice exports out of the Arctic Basin and cold air outbreaks into the Barents Sea, the Nordic seas, and northern Europe. When the dipole anomaly remains in its positive phase, that is, negative SLP anomalies appear between the Kara Sea and the Laptev Sea with concurrent positive SLP over from the Canadian Archipelago extending southeastward to Greenland, there are large-scale changes in the intensity and character of sea ice transport in the Arctic basin. The significant changes include a weakening of the Beaufort gyre, an increase in sea ice export out of the Arctic basin through Fram Strait and the northern Barents Sea, and enhanced sea ice import from the Laptev Sea and the East Siberian Sea into the Arctic basin. Consequently, more sea ice appears in the Greenland and the Barents Seas during the positive phase of the dipole anomaly. During the negative phase of the dipole anomaly, SLP anomalies show an opposite scenario in the Arctic Ocean and its marginal seas when compared to the positive phase, with the center of negative SLP anomalies over the Nordic seas. Correspondingly, sea ice exports decrease from the Arctic basin flowing into the Nordic seas and the northern Barents Sea because of the strengthened Beaufort gyre. The finding indicates that influences of the dipole anomaly on winter sea ice motion are greater than that of the winter AO, particularly in the central Arctic basin and northward to Fram Strait, implying that effects of the dipole anomaly on sea ice export out of the Arctic basin become robust. The dipole anomaly is closely related to atmosphere–ice–ocean interactions that influence the Barents Sea sector.

Substantial changes occurred in the North Atlantic during the twentieth century. Here the authors demonstrate, through the analysis of a vast collection of observational data, that multidecadal fluctuations on time scales of 50–80 yr are prevalent in the upper 3000 m of the North Atlantic Ocean. Spatially averaged temperature and salinity from the 0–300- and 1000–3000-m layers vary in opposition: prolonged periods of cooling and freshening (warming and salinification) in one layer are generally associated with opposite tendencies in the other layer, consistent with the notion of thermohaline overturning circulation. In the 1990s, widespread cooling and freshening was a dominant feature in the 1000–3000-m layer, whereas warming and salinification generally dominated in the upper 300 m, except for the subpolar North Atlantic where complex exchanges with the Arctic Ocean occur. The single-signed basin-scale pattern of multidecadal variability is evident from decadal 1000–3000-m temperature and salinity fields, whereas upper-ocean temperature and salinity distributions have a more complicated spatial pattern. Results suggest a general warming trend of 0.012° ± 0.009°C decade−1 in the upper-3000-m North Atlantic over the last 55 yr of the twentieth century, although during this time there are periods in which short-term trends are strongly amplified by multidecadal variability. Since warming (cooling) is generally associated with salinification (freshening) for these large-scale fluctuations, qualitatively tracking the mean temperature–salinity relationship, vertical displacement of isotherms appears to play an important role in this warming and in other observed fluctuations. Finally, since the North Atlantic Ocean plays a crucial role in establishing and regulating global thermohaline circulation, the multidecadal fluctuations of the heat and freshwater balance discussed here should be considered when assessing long-term climate change and variability, both in the North Atlantic and at global scales.

Five global climate models are used to estimate the local enhancement of Arctic warming attributable to sea ice retreat in B2-scenario greenhouse simulations. The models show a wide range of ice retreat, resulting in a corresponding range in the enhancement of warming. The enhancement is highly seasonal, varying locally from essentially zero in the summer to several degrees (°C) in the late autumn and early winter. Its magnitude increases with the threshold decline in ice concentration used to define retreat because higher thresholds better isolate the warming enhancement signal over ice retreat areas. A threshold of 20% ensures that all models in this study have enough ice retreat area to sample the enhancement because all start with ice concentrations at least that high over substantial northern hemisphere areas. All estimates are lower bounds because they do not account for advective effects.

Using monthly Arctic sea ice concentration data (1953–95) and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset (1958–99), possible feedbacks of sea ice variations in the Greenland and Barents Seas to the atmosphere are investigated. Winter (February–April) sea ice anomalies in the Greenland and Barents Seas display important feedback influences on the atmospheric boundary layer in terms of both thermodynamic and dynamic processes. The vertical gradients of potential pseudo-equivalent temperature (θse) between 850 and 700 hPa are greater over sea ice than over open water, implying that a more stable boundary layer forms below 700 hPa over sea ice. The effects of temperature advection are shown to account for a relatively small percentage of the temperature variance in area of sea ice feedbacks. Horizontal and vertical variations of the effects of sea ice on temperature in the Nordic and Barents Seas create the potential for d...

Arctic cyclone activity is investigated in the context of climate change and variability by using a modified automated cyclone identification and tracking algorithm, which differs from previously used algorithms by single counting each cyclone. The investigation extends earlier studies by lengthening the time period to 55 yr (1948– 2002) with a 6-hourly time resolution, by documenting the seasonality and the dominant temporal modes of variability of cyclone activity, and by diagnosing regional activity as quantified by the cyclone activity index (CAI). The CAI integrates information on cyclone intensity, frequency, and duration into a comprehensive index of cyclone activity. Arctic cyclone activity has increased during the second half of the twentieth century, while midlatitude activity generally decreased from 1960 to the early 1990s, in agreement with previous studies. New findings include the following. 1) The number and intensity of cyclones entering the Arctic from the midlatitudes has incre...

The influence of realistic Arctic sea ice anomalies on the atmosphere during winter is investigated with version 3.6 of the Community Climate Model (CCM3.6). Model experiments are performed for the winters with the most (1982/83) and least (1995/96) Arctic ice coverage during 1979–99, when ice concentration estimates were available from satellites. The experiments consist of 50-member ensembles: using large ensembles proved critical to distinguish the signal from noise. The local response to ice anomalies over the subpolar seas of both the Atlantic and Pacific is robust and generally shallow with large upward surface heat fluxes (>100 W m−2), near-surface warming, enhanced precipitation, and below-normal sea level pressure where sea ice receded, and the reverse where the ice expanded. The large-scale response to reduced (enhanced) ice extent to the east (west) of Greenland during 1982/83 resembles the negative phase of the Arctic Oscillation/North Atlantic Oscillation (AO/NAO) with a ridge over t...