Arctic sea ice and Eurasian climate: A review

The Arctic plays a fundamental role in the climate system and has shown significant climate change in recent decades,including the Arctic warming and decline of Arctic sea-ice extent and thickness. In contrast to the Arctic warming and reduction of Arctic sea ice, Europe, East Asia and North America have experienced anomalously cold conditions, with record snowfall during recent years. In this paper, we review current understanding of the sea-ice impacts on the Eurasian climate.Paleo, observational and modelling studies are covered to summarize several major themes, including: the variability of Arctic sea ice and its controls; the likely causes and apparent impacts of the Arctic sea-ice decline during the satellite era,as well as past and projected future impacts and trends; the links and feedback mechanisms between the Arctic sea ice and the Arctic Oscillation/North Atlantic Oscillation, the recent Eurasian cooling, winter atmospheric circulation, summer precipitation in East Asia, spring snowfall over Eurasia, East Asian winter monsoon, and midlatitude extreme weather; and the remote climate response(e.g., atmospheric circulation, air temperature) to changes in Arctic sea ice. We conclude with a brief summary and suggestions for future research.     

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。     

Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3

Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice?Cocean?Cterrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1?year. In all regimes, ice thickness has high potential predictability for at least 2?years.     

近20 a驱动北极夏季迅速增暖和融冰的自然因素及过程

北极是全球气候系统平衡的重要一环,近20 a全球变暖现象中,北极迅速增温及融冰是最为引人关注的问题之一.人类影响无疑是过去几十年北极变暖背后的最主要的原因及驱动力,但气候系统的内在自然变率对北极的影响也不容忽视.本文指出,北极变暖的自然影响因子有一部分来源于热带太平洋东部海温的变化,热带太平洋通过由东部海温异常所驱动的...     

Interannual predictability of Arctic sea ice in a global climate model: regional contrasts and temporal evolution

The predictability of the Arctic sea ice is investigated at the interannual time scale using decadal experiments performed within the framework of the fifth phase of the Coupled Model Intercomparison Project with the CNRM-CM5.1 coupled atmosphere–ocean global climate model. The predictability of summer Arctic sea ice extent is found to be weak and not to exceed 2 years. In contrast, robust prognostic potential predictability (PPP) up to several years is found for winter sea ice extent and volume. This predictability is regionally contrasted. The marginal seas in the Atlantic sector and the central Arctic show the highest potential predictability, while the marginal seas in the Pacific sector are barely predictable. The PPP is shown to decrease drastically in the more recent period. Regarding sea ice extent, this decrease is explained by a strong reduction of its natural variability in the Greenland–Iceland–Norwegian Seas due to the quasi-disappearance of the marginal ice zone in the center of the Greenland Sea. In contrast, the decrease of predictability of sea ice volume arises from the combined effect of a reduction of its natural variability and an increase in its chaotic nature. The latter is attributed to a thinning of sea ice cover over the whole Arctic, making it more sensitive to atmospheric fluctuations. In contrast to the PPP assessment, the prediction skill as measured by the anomaly correlation coefficient is found to be mostly due to external forcing. Yet, in agreement with the PPP assessment, a weak added value of the initialization is found in the Atlantic sector. Nevertheless, the trend-independent component of this skill is not statistically significant beyond the forecast range of 3 months. These contrasted findings regarding potential predictability and prediction skill arising from the initialization suggest that substantial improvements can be made in order to enhance the prediction skill.     

Simulation of sea ice and ocean variability in the arctic during 1955–2002 with an intermediate complexity model

Abstract

A number of recent sea‐ice and ocean changes in the Arctic and subarctic regions are simulated using the global University of Victoria (UVic) Earth System Climate Model version 2.6. This is an intermediate complexity model which includes a three‐dimensional ocean model (MOM 2.2), an energy‐moisture balance model for the atmosphere with heat and moisture transport, and a dynamic‐thermodynamic sea‐ice model with elastic‐viscous‐plastic rheology. The model is first spun up for 1800 years with monthly wind stress forcing derived from the National Centers for Environmental Prediction (NCEP) climatology winds and a pre‐industrial atmospheric CO₂ concentration of 280 ppm. After a second spin‐up for the period 1800–1947 with daily climatology winds‐tress forcing, and a linearly increasing atmospheric CO₂ concentration, the model is run with interannually varying wind stresses for the period 1948–2002 with an average forcing interval of 2.5 days and an exponentially increasing atmospheric CO₂ concentration varying from 315 to 365 ppm. However, the analysis of the model output is only carried out for the years 1955–2002.

The simulated maximum and minimum sea‐ice areas for the Arctic are within 6% of the observed climatologies for the years 1978–2001. The model output also shows a small downward trend in sea‐ice extent, which, however, is smaller than has been observed during the past few decades. In addition, the model simulates a decrease in sea‐ice thickness in the SCICEX (SCientific ICe EXpeditions) measurement area in the central Arctic that is consistent with, but smaller than, that observed from submarine sonar profiling data.

The observed variability and magnitude of the export of sea ice through Fram Strait is quite well captured in the simulation. The change in correlation between the North Atlantic Oscillation (NAO) index and the sea‐ice export around 1977 as found in a data study by Hilmer and Jung (2000) is also reproduced. Within the Arctic basin the model simulates well the patterns and the timing of the two major regimes of wind‐forced sea‐ice drift circulation (cyclonic and anticyclonic) as found earlier by Proshutinsky and Johnson (1997). The influence of variations in the Fram Strait ice export on the strength of the North Atlantic thermohaline circulation and surface air temperature are also determined. In particular, it is shown that 3–4 years after a large ice export, the maximum meridional overturning streamfunction decreases by more than 10%.

The temperature and salinity increase at depths of 200–300 m, as observed in the eastern Arctic by Morison et al. (1998), between the USS Pargo cruise in 1993 and the Environmental Working Group (EWG) Joint USRussian Arctic Atlas climatology for the years 1948–87, are just visible in the model simulation. The increases are more noticeable, however, when the ocean model data are averaged over the pentade 1995–2000 and compared with model data averaged over the pentade 1955–60. The fact that these, and some of the other modelled changes, are smaller than the observed changes can likely be attributed to the relatively coarse resolution of the UVic Earth System Climate Model (3.6°E‐W and 1.8°N‐S). Nevertheless, the fact that the model captures qualitatively many of the recent sea‐ice and ocean changes in the Arctic suggests that it can be successfully used to investigate other Arctic‐North Atlantic Ocean climate interactions during past and future eras.     

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.     

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

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

近20年来中国极地大气科学研究进展

南极、北极和青藏高原是地球上的 3大气候敏感地区 ,是多个国际计划研究全球变化的关键地区。中国的南极和北极实地考察研究 ,分别始于 2 0世纪 80和 90年代 ,起步较晚 ,但近 2 0余年来有较大的进展。极地大气科学考察与研究是极地科学研究的重要组成部分。讫今为止 ,中国已组织了 2 0次南极考察和 3次北极考察 ,建立了中国南极长城站、中山站和北极黄河站等 3个常年科学考察站 ;进行了常规地面气象、Brewer大气臭氧、近地面物理、高层大气物理、冰雪和大气化学等观测 ,获得了较为系统的极地大气科学第一手资料 ;开展了有关极地与全球变化的研究 ,取得了新的进展。南极地区大气温度、臭氧和海冰的气候变化在时间和空间上都是多样的。南极地区的增暖主要发生在南极半岛地区 ,在南极大陆主体并不明显 ,近 10余年来还有降温趋势。中国南极长城站和中山站的观测资料也证实了这一点。此外 ,还揭示了南极半岛西侧和罗斯海外围的海冰变化具有“翘翘板”特征 ,由此定义的南极涛动指数可用来讨论南极海冰状况和海冰关键区的活动 ;用实地考察资料研究了极地不同下垫面的近地面物理和海 -冰 -气相互作用特征 ,给出了边界层特征参数 ;讨论了极地天气气候和大气环境特征及其对东亚大气环流和中国天气气候的影响 ;利用     

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.     

Climate tendencies of changes in multiyear sea ice thickness in the Arctic Basin (1970–2005)

The area integral of the sea ice thickness in the Arctic Basin is estimated from the measurements of sea ice surface fluctuations at drift-ice stations. The 1970–1990 linear trend is indicative of an approximately 10-cm reduction in the average sea ice thickness over the entire Arctic Basin, which makes 3% of the average ice thickness (about 3 m). Seasonal changes made 40 cm. The amplitude of variations of the average ice thickness in that period is 20 cm with a period of changes of approximately 6–8 years. The observations were interrupted during 1991–2003 and then resumed in 2004. During 1990–2005, the old ice thickness over the entire Arctic Basin decreased, on average, by 110 cm.     

BCC-CSM2-MR模式对北极海冰和气候的模拟及预估

基于第六次耦合模式比较计划（CMIP6）,使用新一代全球模式BCC-CSM2-MR的历史试验和未来共享社会经济路径（SSPs）数据,依据Hadley中心的海表面温度和海冰密集度数据及NCEP/NCAR I再分析资料,评估了BCC-CSM2-MR模式对北极海冰及北极气候的模拟能力,并对未来变化进行了预估。结果表明：BCC-CSM2-MR模式可以较好再现北极海冰密集度、近地层大气平均温度和海表温度的多年平均空间分布特征。但模式对北极局地大气平均温度模拟存在一定偏差,可能在一定程度上导致相应地区海冰的模拟存在差异。21世纪,北极海冰范围持续减少,9月减少趋势显著,3月减少趋势相对较弱。3月北极大部地区表现为一致的增温,仅在北大西洋局部出现一定程度的降温,9月北极大气增温幅度弱于3月。与地表平均温度不同,3月和9月的北极大部地区海表温度均出现增加,且9月海表温度的增幅大于3月,仅拉布拉多海海温出现下降。     

Expected change of hydrologic cycle in Northern Eurasia due to disappearance of multiyear sea ice in the Arctic Ocean

The effects are considered that global warming and rapid sea ice decline in the Arctic (up to the formation of ice-free conditions in the Arctic Ocean in summer) made on the hydrological regime of Northern Eurasia. Ensemble computations of climate are provided and changes in the atmospheric water cycle and in water balance in large catchment areas after the loss of multiyear sea ice in the Arctic are estimated. Considerable changes in the hydrological regime are demonstrated on the example of the large catchments of the Siberian rivers; the changes are especially manifested in the period of intense snow melting, i.e., in spring and in early summer. It is revealed that the increase in the frequency of spring floods is expected in the river catchments adjoining the Arctic Ocean. It is demonstrated that the Arctic Ocean ice reduction does not exert as significant influence on variations in the water cycle in Northern Eurasia as the global warming does.     

Effect of the large-scale atmospheric circulation on the variability of the Arctic Ocean freshwater export

Freshwater (FW) leaves the Arctic Ocean through sea-ice export and the outflow of low-salinity upper ocean water. Whereas the variability of the sea-ice export is known to be mainly caused by changes in the local wind and the thickness of the exported sea ice, the mechanisms that regulate the variability of the liquid FW export are still under investigation. To better understand these mechanisms, we present an analysis of the variability of the liquid FW export from the Arctic Ocean for the period 1950–2007, using a simulation from an energy and mass conserving global ocean–sea ice model, coupled to an Energy Moisture Balance Model of the atmosphere, and forced with daily winds from the NCEP reanalysis. Our results show that the simulated liquid FW exports through the Canadian Arctic Archipelago (CAA) and the Fram Strait lag changes in the large-scale atmospheric circulation over the Arctic by 1 and 6 years, respectively. The variability of the liquid FW exports is caused by changes in the cyclonicity of the atmospheric forcing, which cause a FW redistribution in the Arctic through changes in Ekman transport in the Beaufort Gyre. This in turn causes changes in the sea surface height (SSH) and salinity upstream of the CAA and Fram Strait, which affect the velocity and salinity of the outflow. The SSH changes induced by the large-scale atmospheric circulation are found to explain a large part of the variance of the liquid FW export, while the local wind plays a much smaller role. We also show that during periods of increased liquid FW export from the Arctic, the strength of the simulated Atlantic meridional overturning circulation is reduced and the ocean heat transport into the Arctic is increased. These results are particularly relevant in the context of global warming, as climate simulations predict an increase in the liquid FW export from the Arctic during the twenty-first century.     

Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model

The upper limit of climate predictability in mid and high northern latitudes on seasonal to interannual time scales is investigated by performing two perfect ensemble experiments with the global coupled atmosphere–ocean–sea ice model ECHAM5/MPI-OM. The ensembles consist of six members and are initialized in January and July from different years of the model’s 300-year control integration. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric climate parameters. The predictability of the atmospheric circulation is small except for southeastern Europe, parts of North America and the North Pacific, where significant predictability occurs with a lead time of up to half a year. The predictability of 2 m air temperature shows a large land–sea contrast with highest predictabilities over the sub polar North Atlantic and North Pacific. A combination of relatively high persistence and advection of sea surface temperature anomalies into these areas leads to large predictability. Air temperature over Europe, parts of North America and Asia shows significant predictability of up to half a year in advance. Over the ice-covered Arctic, air temperature is not predictable at time scales exceeding 2 months. Sea ice thickness is highly predictable in the central Arctic mainly due to persistence and in the Labrador Sea due to dynamics. Surface salinity is highly predictable in the Arctic Ocean, northern North Atlantic and North Pacific for several years in advance. We compare the results to the predictability due to persistence and show the importance of dynamical processes for the predictability.     

Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia.     

Regional Arctic sea ice variations as predictor for winter climate conditions

Seasonal prediction skill of winter mid and high northern latitudes climate from sea ice variations in eight different Arctic regions is analyzed using detrended ERA-interim data and satellite sea ice data for the period 1980–2013. We find significant correlations between ice areas in both September and November and winter sea level pressure, air temperature and precipitation. The prediction skill is improved when using November sea ice conditions as predictor compared to September. This is particularly true for predicting winter NAO-like patterns and blocking situations in the Euro-Atlantic area. We find that sea ice variations in Barents Sea seem to be most important for the sign of the following winter NAO—negative after low ice—but amplitude and extension of the patterns are modulated by Greenland and Labrador Seas ice areas. November ice variability in the Greenland Sea provides the best prediction skill for central and western European temperature and ice variations in the Laptev/East Siberian Seas have the largest impact on the blocking number in the Euro-Atlantic region. Over North America, prediction skill is largest using September ice areas from the Pacific Arctic sector as predictor. Composite analyses of high and low regional autumn ice conditions reveal that the atmospheric response is not entirely linear suggesting changing predictive skill dependent on sign and amplitude of the anomaly. The results confirm the importance of realistic sea ice initial conditions for seasonal forecasts. However, correlations do seldom exceed 0.6 indicating that Arctic sea ice variations can only explain a part of winter climate variations in northern mid and high latitudes.     

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.     

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.     

Properties of adjoint sea ice sensitivities to atmospheric forcing and implications for the causes of the long term trend of Arctic sea ice

Based on adjoint sensitivities of the coupled Massachusetts Institute of Technology ocean–sea ice circulation model, the potential influence of thermodynamic atmospheric forcing on the interannual variability of the September sea ice area (AREA) and volume (VOLUME) in the Arctic is investigated for the three periods 1980–1989, 1990–1999 and 2000–2009. Sensitivities suggest that only large forcing anomalies prior to the spring melting onset in May can influence the September sea ice characteristics while even small changes in the atmospheric variables during subsequent months can significantly influence September sea ice state. Specifically, AREA close to the ice edge in the Arctic seas is highly sensitive to thermodynamic atmospheric forcing changes from June to July. In contrast, VOLUME is highly sensitive to atmospheric temperature changes occurring during the same period over the central parts of the Arctic Ocean. A comparison of the sea ice conditions and sensitivities during three different periods reveals that, due to the strong decline of sea ice concentration and sea ice thickness, sea ice area became substantially more sensitive to the same amplitude thermodynamic atmospheric forcing anomalies during 2000–2009 relative to the earlier periods. To obtain a quantitative estimate of changes that can be expected from existing atmospheric trends, adjoint sensitivities are multiplied by monthly temperature differences between 1980s and two following decades. Strongest contributions of surface atmospheric temperature differences to AREA and VOLUME changes are observed during May and September. The strongest contribution from the downward long-wave heat flux to AREA changes occurs in September and to VOLUME changes in July–August. About 62 % of the AREA decrease simulated by the model can be explained by summing all contributions to the thermodynamic atmospheric forcing. The changing sea ice state (sensitivity) is found to enhance the decline and accounts for about one third of the explained reduction. For the VOLUME decrease, the explained fraction of the decrease is only about 37 %.