A data-model intercomparison study of Arctic sea-ice variability

The dynamic-thermodynamic granular rheology sea-ice model of Tremblay and Mysak is validated against 40 years of observed sea-ice concentration (SIC) data. Subsequently, the mechanisms responsible for producing SIC anomalies in the model are evaluated by studying the coupled variance (using the singular value decomposition method, SVD) between the simulated SIC anomalies and the ice speed and air temperature anomalies. To execute this validation, a 49-year (1949-97) simulation (including a 9-year spin-up period) of the Arctic and peripheral sea-ice cover using daily varying winds and monthly mean air temperatures is produced. In general, the simulated SIC variations for 1958-97 in the East Siberian, Chukchi and Beaufort seas are in agreement with observations, while larger discrepancies occur in the Laptev and Kara seas. Moreover, the sensitivity of the model to southerly wind anomalies in creating summer SIC anomalies compares well with the observed sensitivity; however, the model's sensitivity to summer air temperature anomalies is weaker than observed. The summer SIC anomalies over an entire sea are not influenced by variations in the level of river runoff. Results from the SVD analysis show that the main source of variability in the peripheral seas is associated with the variation in the strength of the Arctic High; in the East Siberian and Laptev seas, the strengthening and weakening of the Transpolar Drift Stream also play an important role. Over the entire Arctic domain, surface air temperature anomalies are negatively correlated with sea-ice anomalies. Finally, the observed downward trend in total sea-ice cover in the last two decades as well as record minima in the East Siberian Sea are well reproduced in the simulation.     

Characteristics of Arctic synoptic activity, 1952–1989

Summary Synoptic activity for the Arctic is examined for the period 1952–1989 using the National Meteorological Center sea level pressure data set. Winter cyclone activity is most common near Iceland, between Svalbard and Scandinavia, the Norwegian and Kara seas, Baffin Bay and the eastern Canadian Arctic Archipelago; the strongest systems are found in the Iceland and Norwegian seas. Mean cyclone tracks, prepared for 1975–1989, confirm that winter cyclones most frequently enter the Arctic from the Norwegian and Barents seas. Winter anticyclones are most frequent and strongest over Siberia and Alaska/Yukon, with additional frequency maxima of weaker systems found over the central Arctic Ocean and Greenland.During summer, cyclonic activity remains common in the same regions as observed for winter, but increases over Siberia, the Canadian Arctic Archipelago and the Central Aretic, related to cyclogenesis over northern parts of Eurasia and North America. Eurasian cyclones tend to enter the Aretic Ocean from the Laptev Sea eastward to the Chukchi Sea, augmenting the influx of systems from the Norwegian and Barents seas. The Siberian and Alaska/Yukon anticyclone centers disappear, with anticyclone maxima forming over the Kara, Laptev, East Siberian and Beaufort seas, and southeastward across Canada. Summer cyclones and anticyclones exhibit little regional variability in mean central pressure, and are typically 5–10 mb weaker than their winter counterparts.North of 65°N, cyclone and anticyclone activity peaks curing summer, and is at a minimum during winter. Trends in cyclone and anticyclone activity north of 65°N are examined through least squares regression. Since 1952, significant positive trends are found for cyclone numbers during winter, spring and summer, and for anticyclone numbers during spring, summer and autumn.With 11 Figures     

Thermohaline water structure on the southwestern Chukchi Sea shelf under conditions of opposite regimes of atmospheric circulation in summer periods of 2003 and 2007

The results of two oceanographic surveys, carried out by TINRO-Center in August 2003 and 2007 in the southwestern part of the Chukchi Sea under conditions of opposite regimes of atmospheric circulation in the Eastern Arctic, are given. A stationary anticyclone with the center over the Beaufort Sea in 2007 favored the transport of warm air masses to the Arctic basin and more rapid ice melting. The surface layer temperature to the east of Wrangel Island reached 12°C (6–8°C above the normal). The upwelling of bottom waters was registered in the coastal zone due to the southeastern winds, the Siberian coastal current was not observed. In summer 2003, on the contrary, the cyclonic circulation type prevailed over the eastern seas of the Arctic, the northwestern winds in the coastal zone favored the spreading of the Siberian coastal current almost up to Bering Strait, the water temperature was 2–3°C below normal. The coastal thermal front was formed in both situations: in the first case, due to upwelling, in the second case, due to the spreading of cold coastal desalinated East Siberian waters.     

Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996

Along with significant changes in the Arctic climate system, the largest year-to-year variation in sea-ice extent (SIE) has occurred in the Laptev, East Siberian, and Chukchi seas (defined here as the area of focus, AOF), among which the two highly contrasting extreme events were observed in the summers of 2007 and 1996 during the period 1979–2012. Although most efforts have been devoted to understanding the 2007 low, a contrasting high September SIE in 1996 might share some related but opposing forcing mechanisms. In this study, we investigate the mechanisms for the formation of these two extremes and quantitatively estimate the cloud-radiation-water vapor feedback to the sea-ice-concentration (SIC) variation utilizing satellite-observed sea-ice products and the NASA MERRA reanalysis. The low SIE in 2007 was associated with a persistent anticyclone over the Beaufort Sea coupled with low pressure over Eurasia, which induced anomalous southerly winds. Ample warm and moist air from the North Pacific was transported to the AOF and resulted in positive anomalies of cloud fraction (CF), precipitable water vapor (PWV), surface LWnet (down-up), total surface energy and temperature. In contrast, the high SIE event in 1996 was associated with a persistent low pressure over the central Arctic coupled with high pressure along the Eastern Arctic coasts, which generated anomalous northerly winds and resulted in negative anomalies of above mentioned atmospheric parameters. In addition to their immediate impacts on sea ice reduction, CF, PWV and radiation can interplay to lead to a positive feedback loop among them, which plays a critical role in reinforcing sea ice to a great low value in 2007. During the summer of 2007, the minimum SIC is 31 % below the climatic mean, while the maximum CF, LWnet and PWV can be up to 15 %, 20 Wm^?2, and 4 kg m^?3 above. The high anti-correlations (?0.79, ?0.61, ?0.61) between the SIC and CF, PWV, and LWnet indicate that CF, PWV and LW radiation are indeed having significant impacts on the SIC variation. A new record low occurred in the summer of 2012 was mainly triggered by a super storm over the central Arctic Ocean in early August that caused substantial mechanical ice deformation on top of the long-term thinning of an Arctic ice pack that had become more dominated by seasonal ice.     

Distinct Modes of Winter Arctic Sea Ice Motion and Their Associations with Surface Wind Variability

Using monthly mean sea ice velocity data obtained from the International Arctic Buoy Programme (IABP) for the period of 1979–1998 and the monthly mean NCEP/NCAR re-analysis dataset (1960–2002), we investigated the spatiotemporal evolution of the leading sea ice motion mode (based on a complex correlation matrix constructed of normalized sea ice motion velocity) and their association with sea level pressure (SLP) and the predominant modes of surface wind field variability. The results indicate that the leadi...     

A box model study of the Greenland Sea,Norwegian Sea,and Arctic Ocean

We develop a simple dynamical system model of the Arctic Ocean and marginal seas by applying the Martinson, Killworth and Gordon box model of a high-latitude two-layer ocean to four regions connected together: the Greenland Sea, the Norwegian Sea, the Arctic Ocean, and the Greenland Gyre. The latter is a small convective region embedded in the northwest corner of the Norwegian Sea. The model for each region consists of a thermodynamic ice layer that covers two layers of saline water which can, under specific conditions, become statically unstable and hence create a state of active overturning. The system is forced by monthly mean atmospheric temperatures in the four regions, by continental runoffs and by inflows from adjacent oceans. The model predicts the ice thickness, and the temperature and salinity of the water in the upper layer of the four regions. Also determined are the water temperature and salinity of the lower layer in the Arctic Ocean box. The convective state of any given region, i.e. whether it is in an active overturning mode or not, is also determined as a continuous function of time. The different output variables of the model, which are the response to climatological forcing conditions, compare favourably with observed data. In the control run, the Arctic Ocean region is characterized by continuous ice cover, the Greenland Sea and Greenland Gyre have ice cover only during winter, and the Norwegian Sea region never forms an ice cover. Another feature of the control run is the winter time occurrence of convective overturning in the upper 200 m in the Greenland Gyre region. The model is also used for different anomaly experiments: a positive air temperature anomaly which represents a global warming of the earth, a negative salt anomaly in the Norwegian Sea which simulates the great salinity anomaly of the 1960s and 1970s, and an increase in the ice flux through Fram Strait which parameterizes anomalous ice production in the Arctic.     

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.     

Relationship Between Arctic Sea Ice Thickness Distribution and Climate of China

Based on the simulated ice thickness data from 1949 to 1999, monthly mean temperature data from 160 stations, and monthly mean 1°×1° precipitation data reconstructed from 749 stations in China from 1951 to 2000, the relationship between the Arctic sea ice thickness distribution and the climate of China is analyzed by using the singular value decomposition method. Climate patterns of temperature and precipitation are obtained through the rotated empirical orthogonal function analysis. The results are as follows. (1) Sea ice in Arctic Ocean has a decreasing trend as a whole, and varies with two major periods of 12-14 and 16-20 yr, respectively. (2) When sea ice is thicker in central Arctic Ocean and Beaufort-Chukchi Seas, thinner in Barents-Kara Seas and Baffin Bay-Labrador Sea, precipitation is less in southern China, Tibetan Plateau, and the north part of northeastern China than normal, and vice versa. (3) When sea ice is thinner in the whole Arctic seas, precipitation is less over the middle and lower reaches of Yellow River and north part of northeastern China, more in Tibetan Plateau and south part of northeastern China than normal, and the reverse is also true. (4) When sea ice is thinner in central Arctic Ocean, East Siberian Sea, Beaufort-Chukchi Seas, and Greenland Sea; and thicker in Baffin Bay-Labrador Sea, air temperature is higher in northeastern China, southern Tibetan Plateau, and Hainan Island than normal. (5) When sea ice is thicker in East Siberian Sea 5 months earlier, thinner in Baffin Bay-Labrador Sea 7-15 months earlier, air temperature is lower over the north of Tibetan Plateau and higher in the north part of northwestern China than normal, and a reverse correlation also exists.     

Relationship between Arctic sea ice thickness distribution and climate of China

Based on the simulated ice thickness data from 1949 to 1999,monthly mean temperature data from 160 stations,and monthly mean 1 × 1 precipitation data reconstructed from 749 stations in China from 1951 to 2000,the relationship between the Arctic sea ice thickness distribution and the climate of China is analyzed by using the singular value decomposition method.Climate patterns of temperature and precipitation are obtained through the rotated empirical orthogonal function analysis.The results are as follows.(1) Sea ice in Arctic Ocean has a decreasing trend as a whole,and varies with two major periods of 12-14 and 16-20 yr,respectively.(2) When sea ice is thicker in central Arctic Ocean and Beaufort-Chukchi Seas,thinner in Barents-Kara Seas and Baffin Bay-Labrador Sea,precipitation is less in southern China,Tibetan Plateau,and the north part of northeastern China than normal,and vice versa.(3) When sea ice is thinner in the whole Arctic seas,precipitation is less over the middle and lower reaches of Yellow River and north part of northeastern China,more in Tibetan Plateau and south part of northeastern China than normal,and the reverse is also true.(4) When sea ice is thinner in central Arctic Ocean,East Siberian Sea,Beaufort-Chukchi Seas,and Greenland Sea;and thicker in Baffin Bay-Labrador Sea,air temperature is higher in northeastern China,southern Tibetan Plateau,and Hainan Island than normal.(5) When sea ice is thicker in East Siberian Sea 5 months earlier,thinner in Baffin Bay-Labrador Sea 7-15 months earlier,air temperature is lower over the north of Tibetan Plateau and higher in the north part of northwestern China than normal,and a reverse correlation also exists.     

北极海冰变化对新疆冬季气温的影响研究

利用1961年12月—2022年2月新疆冬季气温、北极海冰等资料，探讨北极海冰变化影响新疆冬季气温的物理模态、影响机制。结果表明，北极海冰的变化与新疆大部冬季气温呈正相关，北极海冰变化通过改变北半球大气高低空配置进而影响新疆冬季气温。另外，不同海区的海冰变化对新疆冬季气温的影响有显著区别：格陵兰海—丹麦海峡、拉普捷夫海—东西伯利亚海海冰异常偏多时，新疆大部冬季气温偏高。巴伦支海—喀拉海、鄂霍次克海—白令海峡、哈德孙湾—戴维斯海峡海冰异常偏多时，新疆大部冬季气温偏低。     

Influence of Global Climate Changes in Past Centuries on the Chemical Composition of Bottom Sediments in the Chukchi Sea

The sedimentary cores from the southern and northern parts of the Chukchi Sea illustrate the influence of climate and environmental conditions on the chemical composition of bottom sediments accumulated at present and in the recent 500 years. The low concentration of biogenic (Ca, Br, Sr) and some redox-sensitive (Fe, Mn, Zn) elements is typical of the recent sediments accumulated in the areas with permanent ice cover and of the sediments accumulated during cold periods (Little Ice Age and especially the Maunder Minimum). The possibility is revealed of identifying cyclic changes in environmental conditions including sea ice extent in the concrete Arctic areas. This may be used to detail the regional forecast of future changes.     

Estimation of seasonal and long-term variability of oceanological conditions in the Bering Strait

Carried out is analysis of variations of temperature, salinity, and currents in the Bering Strait area based on the data of American and Russian-American studies of the Bering Strait during the period from 1992 to 2010. Major attention is paid to the analysis of the long-term variability of water dynamics using the data of observations at the autonomous buoy stations in the Russian and American parts of the Bering Strait. Revealed are the trends towards the increase in the velocity of the Pacific water transport to the Chukchi Sea and Arctic Ocean, as well as the absence of the significant trend towards the changes in the temperature and salinity of deep waters in the Bering Strait. Estimated is the seasonal variability of hydrophysical conditions.     

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     

BCC_CSM北极海冰模拟性能的改进对东亚冬季气候模拟的影响

国家气候中心气候系统模式(BCC_CSM)将美国Los Alamos国家实验室发展的海冰模式CICE5.0替代原有的海冰模式SIS,形成一个新版本耦合模式,很好地提高了模式对北极海冰和北极气候的模拟能力.在此基础上,本文评估新耦合模式对1985-2014年东亚冬季气候的模拟性能,检验北极海冰模拟性能的改进对东亚冬季气候...     

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.     

北极地区极昼气候突变现象及转型成因研究

基于1979-2018年的NCEP-DOE Reanalysis Ⅱ逐日再分析数据,采用模糊C均值聚类算法(Fuzzy C-Means Algorithm,FCMA)将北极地区极昼期间的气候分为寒干型、半寒干型、半暖湿型及暖湿型4种.在夏季北极海冰快速减少的气候背景下,这4种气候型控制的区域也相应发生了明显变化.其中,...     

Climatic variations of ice conditions in different regions of the Barents Sea

Presented are the results of studying the regional peculiarities of climatic variations of spatiotemporal distribution of ice in the Barents Sea water area in 1977?C2010. Demonstrated is the dynamics of the interannual and seasonal variability of main elements of the ice regime (ice cover area, ice edge position, and ice period duration). Revealed are the common features and differences in the ice conditions in the water areas under study. It has been found that there is a significant feedback between the specific ice coverage in different areas of the sea. The climatic variations of the total ice coverage of the Barents Sea for the period of 1960?C2010 are analyzed using the electronic database on the Barents Sea ice coverage. It can be supposed that the current warm phase of climatic variations in the Barents Sea is coming to the end.     

Using δ<Superscript>18</Superscript>O as a Tracer of the Formation of Water Masses in the Laptev Sea. Part 1. Quantification of Ice Formation and Melting

Data on salinity and δ¹⁸O from the NASA open-source database are used to estimate the Laptev Sea water mass transformation during ice formation and melting. The indicator of these processes is salinity variation. The estimates for the Laptev Sea show that the amount of meltwater can reach 40% for the sea water with salinity below 7 psu. In this case, sea water salinity reduction due to the meltwater inflow alone can be equal to 0.2-0.7 psu. In the sea water with salinity above 7 psu, ice formation prevails over ice melting. This process is the most strongly pronounced in the range of sea water salinity from 15 to 25 psu. In this salinity range, the average water removal for the ice formation makes up 9% (the maximum is 24%), and the average salinity growth is 0.5 psu (the maximum is 1.7 psu). The most transformed sea water masses during ice formation are located in the bottom layer of the shallow southern and southeastern parts of the Laptev Sea, where the sea depth is not more than 50 m.     

Semidiurnal frequency of the fields of the Arctic ice rarefaction and compression from the MTVZA-GYa satellite radiometer data

The spatiotemporal variability is considered ofthe field of ice rarefaction and compression in the Arctic due to the passage of semidiurnal tidal waves. A simplified method is developed for identification of such fields on the maps of the scattering index (SI) of ice computed from the MTVZA-GYa radiometer data. It is demonstrated that the low and high values of ice SI are ob served at tidal rarefactions and compressions, respectively. The analysis of the maps of extreme values of SI observed in overlapping semidiurnal and diurnal MTVZA-GYa measurements corroborated the existence of semidiurnal periodicity of alternating fields of the Arctic ice rarefaction and compression and revealed no variability in ice SI in the areas where tidal wave phases converge (there the convergence amplitude is minimum).