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.     

GCM simulations of the Last Glacial Maximum surface climate of Greenland and Antarctica

 The LMDz variable grid GCM was used to simulate the Last Glacial Maximum (LGM, 21 ky Bp.) climate of Greenland and Antarctica at a spatial resolution of about 100 km.The high spatial resolution allows to investigate the spatial variability of surface climate change signals, and thus to address the question whether the sparse ice core data can be viewed as representative for the regional scale climate change. This study addresses primarily surface climate parameters because these can be checked against the, limited, ice core record. The changes are generally stronger for Greenland than for Antarctica, as the imposed changes of the forcing boundary conditions (e.g., sea surface temperatures) are more important in the vicinity of Greenland. Over Greenland, and to a limited extent also in Antarctica, the climate shows stronger changes in winter than in summer. The model suggests that the linear relationship between the surface temperature and inversion strength is modified during the LGM. The temperature dependency of the moisture holding capacity of the atmosphere alone cannot explain the strong reduction in snowfall over central Greenland; atmospheric circulation changes also play a crucial role. Changes in the high frequency variability of snowfall, atmospheric pressure and temperature are investigated and possible consequences for the interpretation of ice core records are discussed. Using an objective cyclone tracking scheme, the importance of changes of the atmospheric dynamics off the coasts of the ice sheets, especially for the high frequency variability of surface climate parameters, is illustrated. The importance of the choice of the LGM ice sheet topography is illustrated for Greenland, where two different topographies have been used, yielding results that differ quite strongly in certain nontrivial respects. This means that the paleo-topography is a significant source of uncertainty for the modelled paleoclimate. The sensitivity of the Greenland LGM climate to the prescribed sea surface conditions is examined by using two different LGM North Atlantic data sets. Received: 23 October 1997 / Accepted: 17 March 1998     

Atmospheric forcing of Fram Strait sea ice export: a closer look

Fram Strait is the primary region of sea ice export from the Arctic and therefore plays an important role in regulating the amount of sea ice and freshwater within the Arctic. We investigate the variability of Fram Strait sea ice motion and the role of atmospheric circulation forcing using daily data during the period 1979–2006. The most prominent atmospheric driver of anomalous sea ice motion across Fram Strait is an east–west dipole pattern of Sea Level Pressure (SLP) anomalies with centers of action located over the Barents Sea and Greenland. This pattern, also observed in synoptic studies, is associated with anomalous meridional winds across Fram Strait and is thus physically consistent with forcing changes in sea ice motion. The association between the SLP dipole pattern and Fram Strait ice motion is maximized at 0-lag, persists year-round, and is strongest on time scales of 10–60 days. The SLP dipole pattern is the second empirical orthogonal function (EOF) of daily SLP anomalies in both winter and summer. When the analysis is repeated with monthly data, only the Barents center of the SLP dipole remains significantly correlated with Fram Strait sea ice motion. However, after removing the leading EOF of monthly SLP variability (e.g., the North Atlantic Oscillation), the full east–west dipole pattern is recovered. No significant SLP forcing of Fram Strait ice motion is found in summer using monthly data, even when the leading EOF is removed. Our results highlight the importance of high frequency atmospheric variability in forcing Fram Strait sea ice motion.     

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.     

Simultaneous winter sea‐ice and atmospheric circulation anomaly patterns

Abstract

This study looks at simultaneous changes in atmospheric circulation and extremes in sea‐ice cover during winter. Thirty‐six years of ice‐cover data and 100‐kPa height and 50–100‐kPa thickness data are used. For the entire Arctic, the study found a general weakening of the Aleutian and Icelandic lows for heavy (i.e. severe) compared with light sea‐ice conditions suggesting reduced surface heating as a possible cause. The weakening of the two lows would also reduce meridional atmospheric circulation and poleward heat transport into the Arctic. The study also looks at three regions of high sea ice and atmospheric variability: the Bering Sea, the Davis Strait/Labrador Sea and the Greenland Sea. For the Bering Sea, heavy sea‐ice conditions were accompanied by weakening and westward displacement of the Aleutian Low again suggesting reduced surface heating and the formation of a secondary low in the Gulf of Alaska. This change in circulation is consistent with increased cold air advection over the Bering Sea and changes in storm tracks and meridional heat transport found in other studies. For the Davis Strait/Labrador Sea, heavy ice‐cover winters were accompanied by intensification of the Icelandic Low suggesting atmospheric temperature and wind advection and associated changes in ocean currents as the main cause of heavy ice. For the Greenland Sea no statistically significant difference was found. It is felt that this may be due to the important role that ice export through Fram Strait and ocean currents play in determining ice extent in this region.     

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.     

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.     

Interdecadal climate variability in the subpolar North Atlantic

The statistical relationships between various components of the subpolar North Atlantic air-sea-ice climate system are reexamined in order to investigate potential processes involved in interdecadal climate variability. It is found that sea surface temperature anomalies concentrated in the Labrador Sea region have a strong impact upon atmospheric sea level pressure anomalies over Greenland, which in turn influence the transport of freshwater and ice anomalies out of the Arctic Ocean, via Fram Strait. These freshwater and ice anomalies are advected around the subpolar gyre into the Labrador Sea affecting convection and the formation of Labrador Sea Water. This has an impact upon the transport of North Atlantic Current water into the subpolar gyre and thus, also upon sea surface temperatures in the region. An interdecadal negative feedback loop is therefore proposed as an internal source of climate variability within the subpolar North Atlantic. Through the lags associated with the correlations between different climatic components, observed horizontal advection time scales, and the use of Boolean delay equation models, the time scale for one cycle of this feedback loop is determined to have a period of about 21 years.     

The demise of Arctic sea ice during stabilisation at high greenhouse gas concentrations

A climate model experiment was conducted using the HadCM3 climate model and a scenario in which the atmospheric CO₂ concentration was increased over 70 years from pre-industrial concentrations to 4 times this level and then stabilised for more than a 1,000 years. During the period of stabilisation the global atmospheric surface temperatures continued to rise as the deep oceans adjusted towards a new equilibrium. However, even after 1,000 years this new equilibrium had not been reached. During the first 600 years, Arctic and Antarctic winter sea ice thickness and area covered declined with a significant impact on the global radiation budget. After this period the area of the Arctic covered by sea ice entered a 150 years period during which time it underwent a series of oscillations. Following the oscillation the centre of the Arctic basin became ice free throughout the year. A sensitivity experiment demonstrates that although the sea ice extent can be greatly reduced through the artificial heating of the mixed layer, prior to the onset of the oscillatory phase the ice recovers over 15 years. Understanding the causes of this oscillatory phase may elucidate the mechanisms of variability in the Arctic in the present climate and in future policy relevant scenarios. We have investigated the atmospheric and oceanic forcing on the ice during the oscillatory phase, and find that the behaviour is linked to a redistribution of Arctic Ocean heat stores.     

北极海冰变化的时间和空间型

利用 4 4a(195 1～ 1994年 )北极海冰密度逐月资料 ,分析提出了一种与北极冰自然季节变化相吻合的分季法 ,并根据这种分季法 ,使用EOF分解 ,揭示了北极各季海冰面积异常的特征空间型及其对应的时间变化尺度。结果表明 :(1)北极冰面积异常变化的关键区 ,冬季 (2～ 4月 )主要位于北大西洋一侧的格陵兰海、巴伦支海和戴维斯海峡以及北太平洋一侧的鄂霍次克海和白令海 ,夏季 (8～ 10月 )则主要限于从喀拉海、东西伯利亚海、楚科奇海到波佛特海的纬向带状区域内 ,格陵兰海和巴伦支海是北极海冰面积异常变化的最重要区域 ;(2 )春 (5～ 7月 )、秋 (11月～次年 1月 )季各主要海区海冰面积异常基本呈同相变化 ,夏季东西伯利亚海、楚科奇海、波佛特海一带海冰面积异常和喀拉海呈反相变化 ,而冬季巴伦支海、格陵兰海海冰面积异常和戴维斯海峡、拉布拉多海、白令海、鄂霍次克海的海冰变化呈反相变化 ;(3)北极冰总面积过去 4 4a来确实经历了一种趋势性的减少 ,并且叠加在这种趋势变化之上的是年代尺度变化 ,其中春季 (5～ 7月 )海冰面积异常变化对年平均北极冰总面积异常变化作出了主要贡献 ;(4)位于北太平洋一侧极冰面积异常型基本具有半年的持续性 ,而位于北大西洋一侧极冰面积异常型具有半年至一年的持续性     

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.     

Arctic Sea‐Ice extent and anomalies, 1953–1984

Abstract

A study is presented of the seasonal and interannual variability of Arctic sea‐ice extent over the 32‐year period 1953–84. The data set used consists of monthly sea‐ice concentration values given on a 1°‐latitude grid and represents a 7‐year extension of the 25‐year data set analysed by Walsh and Johnson (1979). By focussing attention on the variability in seven distinct subregions that circumscribe the polar region, a number of interesting spatial patterns emerge in the regional seasonal cycles and anomalies of ice coverage. For example, the time‐scale of the smoothed anomaly fluctuations varies from a 4–6 year cycle in the western Arctic (e.g. the Beaufort Sea) to a decadal one in the eastern Arctic (e.g. the Barents Sea). Also, in agreement with earlier studies, a significant out‐of‐phase relationship was found between the 25‐month smoothed anomalies in the Beaufort and Chukchi Sea region and the Greenland Sea. It is proposed that this behaviour is related to atmospheric pressure anomalies associated with the see‐saw in winter air temperature between northern Europe and western Greenland. Finally, a particularly large 9‐year ice anomaly in the Greenland Sea that was centred on 1968 appears to have evolved into a substantial 4‐year Labrador Sea anomaly that peaked in 1972. Both of these anomalies coincided with the passage of the “ Great Salinity Anomaly”, which traversed cyclonically around the subpolar gyre in the northern North Atlantic during the period 1968–82.     

Variability of Fram Strait sea ice export: causes, impacts and feedbacks in a coupled climate model

Analyses of a 500-year control integration of the global coupled atmosphere–sea ice–ocean model ECHAM5.0/MPI-OM show a high variability in the ice export through Fram Strait on interannual to decadal timescales. This variability is mainly determined by variations in the sea level pressure gradient across Fram Strait and thus geostrophic wind stress. Ice thickness anomalies, formed at the Siberian coast and in the Chukchi Sea, propagate across the Arctic to Fram Strait and contribute to the variability of the ice export on a timescale of about 9 years. Large anomalies of the ice export through Fram Strait cause fresh water signals, which reach the Labrador Sea after 1–2 years and lead to significant changes in the deep convection. The associated anomalies in ice cover and ocean heat release have a significant impact on air temperature in the Labrador Sea and on the large-scale atmospheric circulation. This affects the sea ice transport and distribution in the Arctic again. Sensitivity studies, simulating the effect of large ice exports through Fram Strait, show that the isolated effect of a prescribed ice/fresh water anomaly is very important for the climate variability in the Labrador Sea. Thus, the ice export through Fram Strait can be used for predictability of Labrador Sea climate up to 2 years in advance.     

北极海冰年际变化对东亚中纬度夏季陆面热力异常的指示作用及其可能原因

本文分析了夏季东亚中纬度近地面温度和春、夏北极海冰时空变化特征,探讨了格陵兰海、巴伦支海海冰异常变化与夏季东亚中纬度陆面热力异常在年际上的可能联系。结果表明:(1)1950—2014年,东亚中纬度夏季近地面温度明显增暖,并伴有明显的年际变化,年际变率最大值的区域主要位于40°N以北至贝加尔湖地区;春、夏格陵兰海和巴伦支海的海冰也呈现明显的减少趋势,同时表现出较强的年际变化特征。(2)春、夏格陵兰海、巴伦支海海冰异常对东亚中纬度夏季陆面热力异常具有一定的指示作用:春、夏格陵兰海、巴伦支海海冰异常偏多,通常对应夏季东亚中纬度近地面的东亚中纬度夏季增暖现象;反之亦然。(3)春、季格陵兰海、巴伦支海北极海冰指数(Arctic Sea Ice Index,ASII)高值年(海冰异常偏多年份),贝加尔湖及西南的蒙古高原地区通常为大范围的异常高压控制,有利于近地面温度升高;同时由于乌拉尔山阻塞高压减弱,极地南下的冷空气减弱,有利于东亚中纬度区域的温度升高。而ASII低值年的情形则相反,贝加尔湖以南地区受异常低压控制,乌拉尔山阻塞高压增强,冷空气易向南侵袭,不利于东亚中纬度近地面升温。     

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.     

Climate fluctuations of the Weddell Sea and its surroundings in a transient climate change scenario

The response of the Weddell Sea and Antarctic Peninsula to anthropogenic forcing simulated by a global climate model is analyzed. The model, despite its low resolution, is able to capture several aspects of the observed regional pattern of climate change. A strong warming and depletion of the sea ice cover in the western Weddell Sea contrasts with a slight cooling and a sea-ice extension in the eastern Weddell Sea. This simulated long-term climate change is modulated by interdecadal variability but also affected by some abrupt regional changes in the oceanic mixed layer depth. Between 1960 and 2030 a reorganization of the deep convection activity in the Weddell Sea sustains the opposition between the eastern and western Weddell Sea. The deep convection collapses in the western Weddell Sea in the 2030s. The sea ice retreat trend is then followed by an increase of the sea ice cover in the western Weddell Sea. In the eastern Weddell Sea another abrupt collapse of the deep convection activity occurs around 2080. This event is followed by a rapid cooling and sea ice extension during the next 20 years. Most of the surface changes are associated with large-scale atmospheric circulation changes that project on the dominant mode of natural variability but also with oceanic convection and circulation changes.     

The climatic response of the Arctic Ocean to Soviet river diversions

A numerical model is constructed to evaluate the effect of river diversions on the circulation of the Arctic Ocean, including the climatically important response in the extent of sea ice. The ocean model solves the primitive equations of motion in finite-difference form for the irregular geometry of the Arctic Ocean and Greenland/Norwegian Sea, using 110 km horizontal grid spacing and up to 13 unevenly spaced levels in the vertical. Annual mean atmospheric conditions and river discharges are specified from observations. The presence of sea ice is diagnosed on the basis of model ocean temperature; and the effects of sea ice on the surface fluxes of momentum, heat, and salt are included in a simplified way. Lateral exchanges at the southernmost boundary are held near observed values but respond to circulation changes in the Greenland/Norwegian Sea. Three equilibrium solutions are obtained by eighty-year integrations from simple initial conditions: the first with inflow from all rivers, the second with one-third of the inflow diverted from four major rivers (the Ob, Yenesei, Dvina, and Pechora), and the third with total diversion from those rivers. The middle case corresponds to maximal diversions which are either planned or envisioned by the Soviet Union over the next fifty years, whereas the final extreme case is run in the event that model sensitivity is low relative to that of nature.The control integration gives a good simulation of known water masses and currents. In the Central Arctic, for example, the model correctly predicts a strong shallow halocline, a relatively warm intermediate layer of Atlantic origin, and a temperature jump across the deep Lomonosov Ridge. The overall pattern of surface salinity and the margin of the pack ice are also properly simulated.When runoff into the marginal Kara and Barents Seas is diverted, either in part or in full, almost no effect on the halocline results in the Central Arctic. In particular, deep convection does not develop in the Eurasian Basin, the possibility of which was suggested by Aagaard and Coachman (1975). The vertical stability within the two marginal seas is considerably decreased by the total diversion of four rivers, but not to the point of convective overturning. The surface currents in this area change to confine the water with increased salinity to the shelf region. At deeper levels, an increased salinity tongue spreads into the deep basins of the ice-free Greenland/Norwegian Sea, where existing deep convection is slightly enhanced. As a result, there is some additional heat loss from the Atlantic layer before it enters the Central Arctic. The ice extent remains nearly the same as before within the Kara and Barents Seas. In fact, since modified bottom currents over the continental shelf bring in less heat from the Greenland Sea, an increased thickness of sea ice may result there, in spite of reduced vertical stability. These model responses are generally in agreement with those suggested by Micklin (1981) and by Soviet investigations of the effect of river diversions. These annualmean results should be regarded as tentative, pending confirmation by studies which include the seasonal cycles of runoff and atmospheric forcing.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

NUMERICAL SIMULATIONS ON INFLUENCES OF VARIATION OF SEA ICE THICKNESS AND EXTENT ON ATMOSPHERIC CIRCULATION*

By using a 2-layer AGCM designed by Institute of Atmospheric Physics,Chinese Academy of Sciences.this paper investigates influences of thickness and extent variations in Arctic sea ice on the atmosphere circulation,particularly on climate variations in East Asia.The simulation results have indicated that sea ice thickness variation in the Arctic exhibits significant influences on simulation results,particularly on East Asian monsoon.A nearly reasonable distribution of sea ice thickness in the model leads directly to stronger winter and summer monsoon over East Asia.and improves the model's simulation results for Siberia high and Icelandic low in winter.On the other hand,sea ice thickness variation can excite a teleconnection wave train across Asian Continent,and in low latitudes,the wave propagates from the western Pacific across the equator to the eastern Pacific.In addition,the variation of sea ice thickness also influences summer convective activitiesover the low latitudes including South China Sea and around the Philippines.Effects of winter sea ice extents in the Barents Sea on atmospheric circulation in the following spring and summer are also significant.The simulation result shows that when winter sea ice extent in the target region is larger (smaller) than normal.(1)in the following spring (averaged from April to June).positive (negative) SLP anomalies occupy the northern central Pacific.which leads directly to weakened (deepened)Aleutian low.and further favors the light (heavy) sea ice condition in the Bering Sea:(2)in the following summer,thermal depression in Asian Continent is deepened (weakened).and the subtropical high in the northwestern Pacific shifts northward(southward) from its normal position and to be strengthened (weakened).     

NUMERICAL SIMULATIONS ON INFLUENCES OF VARIATION OF SEA ICE THICKNESS AND EXTENT ON ATMOSPHERIC CIRCULATION

By using a 2-layer AGCM designed by Institute of Atmospheric Physics,Chinese Academy ofSciences.this paper investigates influences of thickness and extent variations in Arctic sea ice onthe atmosphere circulation,particularly on climate variations in East Asia.The simulation resuhshave indicated that sea ice thickness variation in the Arctic exhibits significant influences onsimulation results,particularly on East Asian monsoon.A nearly reasonable distribution of sea icethickness in the model leads directly to stronger winter and summer monsoon over East Asia.andimproves the model's simulation results for Siberia high and Icelandic low in winter.On the otherhand,sea ice thickness variation can excite a teleconnection wave train across Asian Continent,andin low latitudes,the wave propagates from the western Pacific across the equator to the easternPacific.In addition,the variation of sea ice thickness also influences summer convective activitiesover the low latitudes including South China Sea and around the Philippines.Effects of winter sea ice extents in the Barents Sea on atmospheric circulation in the followingspring and summer are also significant.The simulation result shows that when winter sea iceextent in the target region is larger (smaller) than normal.(1)in the following spring (averagedfrom April to June).positive (negative) SLP anomalies occupy the northern central Pacific.whichleads directly to weakened (deepened)Aleutian low.and further favors the light (heavy) sea icecondition in the Bering Sea:(2)in the following summer,thermal depression in Asian Continent isdeepened (weakened).and the subtropical high in the northwestern Pacific shifts northward(southward) from its normal position and to be strengthened (weakened).     

Synoptic Climatology of the Southern Beaufort Sea Troposphere with Comparisons to Surface Winds

Synoptic-scale atmospheric circulation patterns drive wind forcing of dynamic and thermodynamic processes in Arctic sea ice. Synoptic typing and compositing are common techniques used to identify a limited number of prevailing weather classifications that govern a region's climate. This work investigates atmospheric circulation patterns (surface to 250?hPa) for the southern Beaufort Sea and corresponding surface wind regimes within each synoptic type. Significant changes (p?<?0.05) in relative frequencies of a number of synoptic types were attributed to declining summer sea ice. Corresponding upper-level circulation anomalies show increasingly meridional atmospheric circulation. Synoptic Types 9 and 11 were identified as key October-November-December circulation features that represent deepening of the Aleutian low with concomitant strengthening of pressure gradients over the southern Beaufort Sea. Classification of coastal-based wind observations shows a shift towards increased easterly wind forcing. A case study of surface wind data from the CCGS Amundsen (2009–2011) provided a direct example of the surface wind regime within the marginal ice zone within each synoptic type during a period of reduced Arctic sea-ice cover.