On the Arctic Ocean ice thickness response to changes in the external forcing

Submarine and satellite observations show that the Arctic Ocean ice cover has undergone a large thickness reduction and a decrease in the areal extent during the last decades. Here the response of the Arctic Ocean ice cover to changes in the poleward atmospheric energy transport, F _wall, is investigated using coupled atmosphere-ice-ocean column models. Two models with highly different complexity are used in order to illustrate the importance of different internal processes and the results highlight the dramatic effects of the negative ice thickness—ice volume export feedback and the positive surface albedo feedback. The steady state ice thickness as a function of F _wall is determined for various model setups and defines what we call ice thickness response curves. When a variable surface albedo and snow precipitation is included, a complex response curve appears with two distinct regimes: a perennial ice cover regime with a fairly linear response and a less responsive seasonal ice cover regime. The two regimes are separated by a steep transition associated with surface albedo feedback. The associated hysteresis is however small, indicating that the Arctic climate system does not have an irreversible tipping point behaviour related to the surface albedo feedback. The results are discussed in the context of the recent reduction of the Arctic sea ice cover. A new mechanism related to regional and temporal variations of the ice divergence within the Arctic Ocean is presented as an explanation for the observed regional variation of the ice thickness reduction. Our results further suggest that the recent reduction in areal ice extent and loss of multiyear ice is related to the albedo dependent transition between seasonal and perennial ice i.e. large areas of the Arctic Ocean that has previously been dominated by multiyear ice might have been pushed below a critical mean ice thickness, corresponding to the above mentioned transition, and into a state dominated by seasonal ice.     

Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

Declining summer snowfall in the Arctic: causes, impacts and feedbacks

Recent changes in the Arctic hydrological cycle are explored using in situ observations and an improved atmospheric reanalysis data set, ERA-Interim. We document a pronounced decline in summer snowfall over the Arctic Ocean and Canadian Archipelago. The snowfall decline is diagnosed as being almost entirely caused by changes in precipitation form (snow turning to rain) with very little influence of decreases in total precipitation. The proportion of precipitation falling as snow has decreased as a result of lower-atmospheric warming. Statistically, over 99% of the summer snowfall decline is linked to Arctic warming over the past two decades. Based on the reanalysis snowfall data over the ice-covered Arctic Ocean, we derive an estimate for the amount of snow-covered ice. It is estimated that the area of snow-covered ice, and the proportion of sea ice covered by snow, have decreased significantly. We perform a series of sensitivity experiments in which inter-annual changes in snow-covered ice are either unaccounted for, or are parameterized. In the parameterized case, the loss of snow-on-ice results in a substantial decrease in the surface albedo over the Arctic Ocean, that is of comparable magnitude to the decrease in albedo due to the decline in sea ice cover. Accordingly, the solar input to the Arctic Ocean is increased, causing additional surface ice melt. We conclude that the decline in summer snowfall has likely contributed to the thinning of sea ice over recent decades. The results presented provide support for the existence of a positive feedback in association with warming-induced reductions in summer snowfall.     

Impact of clouds on the surface radiation balance of the Arctic Ocean

Summary The relationship between clouds and the surface radiative fluxes over the Arctic Ocean are explored by conducting a series of modelling experiments using a one-dimensional thermodynamic sea ice model. The sensitivity of radiative flux to perturbations in cloud fraction and cloud optical depth are determined. These experiments illustrate the substantial effect that clouds have on the state of the sea ice and on the surface radiative fluxes. The effect of clouds on the net flux of radiation at the surface is very complex over the Arctic Ocean particularly due to the presence of the underlying sea ice. Owing to changes in surface albedo and temperature associated with changing cloud properties, there is a strong non-linearity between cloud properties and surface radiative fluxes. The model results are evaluated in three different contexts: 1) the sensitivity of the arctic surface radiation balance to uncertainties in cloud properties; 2) the impact of interannual variability in cloud characteristics on surface radiation fluxes and sea ice surface characteristics; and 3) the impact of climate change and the resulting changes in cloud properties on the surface radiation fluxes and sea ice characteristics.With 11 Figures     

北极海冰融化影响东亚冬季天气和气候的研究进展以及学术争论焦点问题

北极历来是影响东亚冬季天气、气候的关键区域之一。北极表面增暖要比全球平均快2~3倍,即所谓北极的放大效应。随着全球增暖的持续以及北极海冰的持续融化,北极的生态环境正在发生显著的变化,进而可能对北半球中、低纬度的天气、气候产生影响。本文概述了有关北极海冰融化影响冬季东亚天气、气候的主要研究进展,特别是自2000年以来,北极海冰异常偏少影响东亚冬季气候变率以及极端严寒事件的可能途径、存在的科学问题,以及学术界的争论焦点。秋、冬季节是北极海冰快速形成时期,此时北极海冰对大气环流的影响要强于大气对海冰的影响。近二十年来的研究结果表明,北极海冰异常偏少,不仅影响北冰洋局地的气温和降水变化,而且通过复杂的相互作用和反馈过程,对北半球中、低纬度的天气、气候产生影响。北极海冰通过以下两个可能机制来影响东亚冬季的天气、气候:（1）北极海冰的负反馈机制;（2）由海冰异常偏少引起的平流层-对流层相互作用机制。秋、冬季节北极海冰持续异常偏少,特别是,巴伦支海-喀拉海海冰异常偏少,既可以加强冬季西伯利亚高压（东亚冬季风偏强）,也可以导致冬季风偏弱。导致海冰影响不确定性的部分原因是:（1）夏季北极大气环流状态影响北极海冰异常偏少对冬季大气环流的反馈效果;（2）冬季大气环流对北极海冰异常偏少响应的位置、强度不同造成的。秋、冬季节北极海冰持续异常偏少,在适宜的条件下（例如,前期夏季北极大气环流的热力和动力条件,有利于加强北极海冰偏少对冬季大气的反馈作用）,可以激发出有利于冬季亚洲大陆极端严寒过程的大气环流异常。目前学术界争论焦点主要集中在以下两个方面:（1）关于北极增暖、北极海冰融化对中纬度区域影响的争论;（2）关于1980年代后期以来,冬季欧亚大陆表面气温呈现降温趋势的原因。目前,有关北极海冰融化影响冬季欧亚大陆次季节变化以及极端天气、气候事件的过程和机制,我们认知非常有限,亟需开展深入细致的研究。     

Potential effect of nuclear war smokefall on sea ice

A large nuclear war could produce massive quantities of smoke from burning cities and industries. A portion of this smoke would fall out on Arctic sea ice, thus lowering its albedo and potentially increasing the solar energy absorbed by the ice and the snow that covers it. We use a one-dimensional thermodynamic sea ice model to examine the effect of smokefall on the seasonal variation of sea ice. In particular, we test the sensitivity of the model results to the time of year, duration, and latitude of smokefall.Sea ice thickness variations and the period of summer ice-free conditions are sensitive to the season of smokefall. The largest sea ice perturbations are generated by smokefall in spring. In this case the period of ice-free conditions during the summer can increase by 2 – 3.5 months between 67.5° N and 82.5° N. In any given season, the annual cycle of sea ice is not very sensitive to the duration of smokefall. The equilibrium annual cycle of sea ice variation is restored within a few years of smokefall when the smoke is flushed out of the ice/snow system.Since the sea ice model used here is not a comprehensive global climate model, it is difficult to predict the mid-latitude climate effects of the massive, but temporary, Arctic sea ice changes. However, our results suggest that future global climate model simulations of the effects of nuclear war smoke include interactive sea ice calculations.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2?m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations.     

On modelling the seasonal thermodynamic cycle of sea ice in studies of climatic change

Recent work in modelling climatic changes due to increased atmospheric CO₂ has shown the maximum change to occur in the polar regions as a result of seasonal reductions in sea ice coverage. Typically, sea ice thermodynamics is modelled in a very simple way, whereby the storage of both sensible and latent heat within the ice is ignored, and the effects of snow cover on conductivity and on surface albedo and of oceanic heat flux on bottom ablation may also be neglected. This paper considers whether omission of these processes is justified within the context of quantitatively determining regional climatic changes. A related question, whether omission of ice dynamics can be justified, is not considered.Relatively complete one-dimensional models of sea-ice thermodynamics have previously been developed and tested for a variety of environmental conditions by Maykut and Untersteiner (1969, 1971) and by Semtner (1976). A simpler model which neglects the storage of sensible and latent heat is described in the Appendix to Semtner (1976). In that model, the errors in annual-mean ice thickness which would arise from neglect of heat storage can be compensated by increases in albedo and in conductivity. Here we examine the seasonal cycle of ice thickness predicted by such a model and find significant errors in phase (one month lead) and in amplitude (50% overestimate). The amplitude errors are enhanced as snowfall and oceanic heat flux diminish (or are neglected). This suggests that substantial errors may occur in climate simulations which use very simple formulations of sea ice thermodynamics, whereby early and excessive melting exaggerates the seasonal disappearance of sea ice.To illustrate the above point, two models are configured to examine the local response of Arctic sea ice to a quadrupling of atmospheric CO₂. The first model neglects a number of physical processes and mimics the behavior of sea ice found in Manabe and Stouffer (1980), both for present and enhanced levels of CO₂. The more complete second model gives a better simulation of Arctic ice for the present level of CO₂ and shows a reduced response to CO₂ quadrupling relative to that in Manabe and Stouffer (1980). In particular, the change in surface temperature is cut by a factor of two. In view of this result, a more complete treatment of sea ice thermodynamics would seem warranted in further studies of climate change. Only a minor computational increase is required.A portion of this study is supported by the U.S. Department of Energy as a part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

The role of sea ice in the temperature-precipitation feedback of glacial cycles

The response of the hydrological cycle to climate variability and change is a critical open question, where model reliability is still unsatisfactory, yet upon which past climate history can shed some light. Sea ice is a key player in the climate system and in the hydrological cycle, due to its strong albedo effect and its insulating effect on local evaporation and air-sea heat flux. Using an atmospheric general circulation model with specified sea surface temperature and sea-ice distribution, the role of sea ice in the hydrological cycle is investigated under last glacial maximum (LGM) and present day conditions, and by studying its contribution to the “temperature-precipitation feedback”. By conducting a set of sensitivity experiments in which the albedo and thickness of the sea ice are varied, the various effects of sea ice in the hydrological cycle are isolated. It is demonstrated that for a cold LGM like state, a warmer climate (as a result of reduced sea-ice cover) leads to an increase in snow precipitation over the ice sheets. The insulating effect of the sea ice on the hydrological cycle is found to be larger than the albedo effect. These two effects interact in a nonlinear way and their total effect is not equal to summing their separate contribution.     

Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model

A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system sensitivity.     

Climate model sensitivity to sea ice albedo parameterization

Summary Three one-year experimental simulations with the National Center for Atmospheric Research Community Climate Model (NCAR CCM) were performed with three sea ice albedo parameterizations and compared with control run results to examine their impact on polar surface temperature, planetary albedo and clouds. The first integration utilized sea ice albedos of the Arctic Basin for the spring and summer of 1977 derived from defence Meteorological Satellite Imagery (DMSP). The second simulation employed prescribed lead and melt pond fractions and an albedo weighting scheme. The third simulation involved the coupling of an interactive sea ice/snow albedo parameterization made a function of surface state.Results show that prescribed, and assumed true satellite sea ice albedos produced higher planetary albedos than those calculated with the standard CCM sea ice albedo scheme in the control run. As a result, lower temperatures (up to 0.5 K) and increased cloudiness are generated for the Arctic region. The standard CCM sea ice albedo scheme is used as an adjustment to maintain normal temperatures for the polar oceans. The radiative impact of leads and melt ponds warmed sea ice regions only for short time periods. The third scheme generated markedly lower planetary albedos (reductions of 0.07 to 0.17) and higher surface temperatures (up to 2.0 K) than control values.The CCM simulates a gradual decrease in spring and summer Arctic cloud cover whereas observations show a sharp spring increase. Examination of the CCM code, particularly the cloud parameterization, is required to address this problem.With 12 Figures     

Light-absorbing particles in snow and ice: Measurement and modeling of climatic and hydrological impact

Light absorbing particles(LAP, e.g., black carbon, brown carbon, and dust) influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance(a.k.a., surface darkening), which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice(LAPSI) has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.     

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.     

A case study of a modelled episode of low Arctic sea ice

Simulations of the Arctic sea ice cover over the last 32 years generated by the HadGEM1 coupled climate model are able to capture the observed long term decline in mean September ice extent. HadGEM1 is also capable of producing an episode of low September ice extent of similar magnitude to the anomalously low extent observed in 2007. Using a heat budget analysis, together with diagnostics partitioning the changes in ice and snow mass into thermodynamic and dynamic components, we analyse the factors driving the long term decline in the ice mass and extent as well as those causing the modelled low ice event. The long term decline in the mass of ice and snow in HadGEM1 is largely due to extra melting during the summer, partly at the top surface of the ice, and partly via extra heating from the ocean as it warms due to the ice retreat. The episode of low summer ice extent is largely driven by the synoptic conditions over the summer moving the ice across and out of the Arctic basin, and also due to pre-conditioning of the snow and ice which is thinner than usual in the Eastern Arctic at the start of the melt season. This case study demonstrates that although HadGEM1 does not capture the persistent dipole pressure anomaly observed during the summer of 2007, it represents broadly similar mechanisms of generating a low ice extent.     

Boundary layer stability and Arctic climate change: a feedback study using EC-Earth

Amplified Arctic warming is one of the key features of climate change. It is evident in observations as well as in climate model simulations. Usually referred to as Arctic amplification, it is generally recognized that the surface albedo feedback governs the response. However, a number of feedback mechanisms play a role in AA, of which those related to the prevalent near-surface inversion have received relatively little attention. Here we investigate the role of the near-surface thermal inversion, which is caused by radiative surface cooling in autumn and winter, on Arctic warming. We employ idealized climate change experiments using the climate model EC-Earth together with ERA-Interim reanalysis data to show that boundary-layer mixing governs the efficiency by which the surface warming signal is ‘diluted’ to higher levels. Reduced vertical mixing, as in the stably stratified inversion layer in Arctic winter, thus amplifies surface warming. Modelling results suggest that both shortwave—through the (seasonal) interaction with the sea ice feedback—and longwave feedbacks are affected by boundary-layer mixing, both in the Arctic and globally, with the effect on the shortwave feedback dominating. The amplifying effect will decrease, however, with climate warming because the surface inversion becomes progressively weaker. We estimate that the reduced Arctic inversion has slowed down global warming by about 5% over the past 2 decades, and we anticipate that it will continue to do so with ongoing Arctic warming.     

Ice-free glacial northern Asia due to dust deposition on snow

During the Last Glacial Maximum (LGM, 21 kyr BP), no large ice sheets were present in northern Asia, while northern Europe and North America (except Alaska) were heavily glaciated. We use a general circulation model with high regional resolution and a new parameterization of snow albedo to show that the ice-free conditions in northern Asia during the LGM are favoured by strong glacial dust deposition on the seasonal snow cover. Our climate model simulations indicate that mineral dust deposition on the snow surface leads to low snow albedo during the melt season. This, in turn, caused enhanced snow melt and therefore favoured snow-free peak summer conditions over almost the entire Asian continent during the LGM, whereas perennial snow cover is simulated over a large part of eastern Siberia when glacial dust deposition is not taken into account.     

The effect of snow on Antarctic sea ice simulations in a coupled atmosphere-sea ice model

 The effect of a snow cover on sea ice accretion and ablation is estimated based on the ‘zero-layer’ version sea ice model of Semtner, and is examined using a coupled atmosphere-sea ice model including feedbacks and ice dynamics effects. When snow is disregarded in the coupled model the averaged Antarctic sea ice becomes thicker. When only half of the snowfall predicted by the atmospheric model is allowed to land on the ice surface sea ice gets thicker in most of the Weddell and Ross Seas but thinner in East Antarctic in winter, with the average slightly thicker. When twice as much snowfall as predicted by the atmospheric model is assumed to land on the ice surface sea ice also gets much thicker due to the large increase of snow-ice formation. These results indicate the importance of the correct simulation of the snow cover over sea ice and snow-ice formation in the Antarctic. Our results also illustrate the complex feedback effects of the snow cover in global climate models. In this study we have also tested the use of a mean value of 0.16 Wm^-1 K^-1 instead of 0.31 for the thermal conductivity of snow in the coupled model, based on the most recent observations in the eastern Antarctic and Bellingshausen and Amundsen Seas, and have found that the sea ice distribution changes greatly, with the ice becoming much thinner by about 0.2 m in the Antarctic and about 0.4 m in the Arctic on average. This implies that the magnitude of the thermal conductivity of snow is of considerable importance for the simulation of the sea ice distribution. An appropriate value of the thermal conductivity of snow is as crucial as the depth of the snow layer and the snowfall rate in a sea ice model. The coupled climate models require accurate values of the effective thermal conductivity of snow from observations for validating the simulated sea ice distribution under the present climate conditions. Received: 20 November 1997/Accepted: 27 July 1998     

Selected topics in arctic atmosphere and climate

This paper summarizes the main elements of four IPY projects that examine the Arctic Atmosphere. All four projects focus on present conditions with a view to anticipating possible climate change. All four investigate the Arctic atmosphere, ocean, ice, and land interfacial surfaces. One project uses computer models to simulate the dynamics of the Arctic atmosphere, storms, and their interactions with the ocean and ice interface. Another project uses statistical methods to infer transports of pollutants as simulated in large-scale global atmospheric and oceanic models verifying results with available observations. A third project focuses on measurements of pollutants at the ice-ocean?Catmosphere interface, with reference to model estimates. The fourth project is concerned with multiple, high accuracy measurements at Eureka in the Canadian Archipelago. While these projects are distinctly different, led by different teams and interdisciplinary collaborators, with different technical approaches and methodologies, and differing objectives, they all strive to understand the processes of the Arctic atmosphere and climate, and to lay the basis for projections of future changes. Key findings include: ? Decreased sea ice leads to more intense storms, higher winds, reduced surface albedo, increased surface air temperature, and enhanced vertical mixing in the upper ocean. ? Arctic warming may affect toxic chemicals by remobilizing persistent organic pollutants and augmenting mercury deposition/retention in the environment. ? Changes in sea ice can dramatically change processes in and at the ice surface related to ozone, mercury and bromine oxide and related chemical/physical properties. ? Structure and properties of the Arctic atmospheric??troposphere to stratosphere??and tracking of transport of pollution and smoke plumes from mid-latitudes to the poles.     

Sea ice in the Barents Sea: seasonal to interannual variability and climate feedbacks in a global coupled model

Sea ice variability in the Barents Sea and its impact on climate are analyzed using a 465-year control integration of a global coupled atmosphere–ocean–sea ice model. Sensitivity simulations are performed to investigate the response to an isolated sea ice anomaly in the Barents Sea. The interannual variability of sea ice volume in the Barents Sea is mainly determined by variations in sea ice import into Barents Sea from the Central Arctic. This import is primarily driven by the local wind field. Horizontal oceanic heat transport into the Barents Sea is of minor importance for interannual sea ice variations but is important on longer time scales. Events with strong positive sea ice anomalies in the Barents Sea are due to accumulation of sea ice by enhanced sea ice imports and related NAO-like pressure conditions in the years before the event. Sea ice volume and concentration stay above normal in the Barents Sea for about 2 years after an event. This strongly increases the albedo and reduces the ocean heat release to the atmosphere. Consequently, air temperature is much colder than usual in the Barents Sea and surrounding areas. Precipitation is decreased and sea level pressure in the Barents Sea is anomalously high. The large-scale atmospheric response is limited with the main impact being a reduced pressure over Scandinavia in the year after a large ice volume occurs in the Barents Sea. Furthermore, high sea ice volume in the Barents Sea leads to increased sea ice melting and hence reduced surface salinity. Generally, the climate response is smallest in summer and largest in winter and spring.     

Ice and climate modeling: An editorial essay

The growth and decay of ice sheets are driven by forces affecting the seasonal cycles of snowfall and snowmelt. The external forces are likely to be variations in the earth's orbit which cause differences in the solar radiation received. Radiational control of snowmelt is modulated by the seasonal cycles of snow albedo and cloud cover. The effects of orbital changes can be magnified by feedbacks involving atmospheric CO₂ content, ocean temperatures and desert areas. Climate modeling of the causes of the Pleistocene ice ages involves modeling the interactions of all components of the climate system; snow, sea ice, glacier ice, the ocean, the atmosphere, and the solid earth. Such modeling is also necessary for interpreting oxygen isotope records from ice and ocean as paleoclimatic evidence.