Severe winter weather as a response to the lowest Arctic sea-ice anomalies

Possible impact of reduced Arctic sea-ice on winter severe weather in China is investigated regarding the snowstorm over southern China in January 2008. The sea-ice conditions in the summer （July-September） and fall （September-November） of 2007 show that the sea-ice is the lowest that year. During the summer and fall of 2007, sea ice displayed a significant decrease in the East Siberian, the northern Chukchi Sea, the western Beaufort Sea, the Barents Sea, and the Kara Sea. A ECHAM5.4 atmospheric general circula- tion model is forced with realistic sea-ice conditions and strong thermal responses with warmer surface air temperature and higher-than-normal heat flux associated with the sea-ice anomalies are found. The model shows remote atmospheric responses over East Asia in January 2008, which result in severe snowstorm over southern China. Strong water-vapor transported from the Bay of Bengal and from the Pacific Ocean related to Arctic sea-ice anomalies in the fall （instead of summer） of 2007 is considered as one of the main causes of the snowstorm formation.     

Satellite-observed trends in the Arctic sea ice concentration for the period 1979–2016

Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ).     

Influence of the ocean surface temperature and sea ice concentration on regional climate changes in Eurasia in recent decades

Numerical experiments with the ECHAM5 atmospheric general circulation model have been performed in order to simulate the influence of changes in the ocean surface temperature (OST) and sea ice concentration (SIC) on climate characteristics in regions of Eurasia. The sensitivity of winter and summer climates to OST and SIC variations in 1998–2006 has been investigated and compared to those in 1968–1976. These two intervals correspond to the maximum and minimum of the Atlantic Long-Period Oscillation (ALO) index. Apart from the experiments on changes in the OST and SIC global fields, the experiments on OST anomalies only in the North Atlantic and SIC anomalies in the Arctic for the specified periods have been analyzed. It is established that temperature variations in Western Europe are explained by OST and SIC variations fairly well, whereas the warmings in Eastern Europe and Western Siberia, according to model experiments, are substantially (by a factor of 2–3) smaller than according to observational data. Winter changes in the temperature regime in continental regions are controlled mainly by atmospheric circulation anomalies. The model, on the whole, reproduces the empirical structure of changes in the winter field of surface pressure, in particular, the pressure decrease in the Caspian region; however, it substantially (approximately by three times) underestimates the range of changes. Summer temperature variations in the model are characterized by a higher statistical significance than winter ones. The analysis of the sensitivity of the climate in Western Europe to SIC variations alone in the Arctic is an important result of the experiments performed. It is established that the SIC decrease and a strong warming over the Barents Sea in the winter period leads to a cooling over vast regions of the northern part of Eurasia and increases the probability of anomalously cold January months by two times and more (for regions in Western Siberia). This effect is caused by the formation of the increased-pressure region with a center over the southern boundary of the Barents Sea during the SIC decrease and an anomalous advection of cold air masses from the northeast. This result indicates that, to estimate the ALO actions (as well as other long-scale climatic variability modes) on the climate of Eurasia, it is basically important to take into account (or correctly reproduce) Arctic sea ice changes in experiments with climatic models.     

Dense water formation and circulation in the Barents Sea

Dense water masses from Arctic shelf seas are an important part of the Arctic thermohaline system. We present previously unpublished observations from shallow banks in the Barents Sea, which reveal large interannual variability in dense water temperature and salinity. To examine the formation and circulation of dense water, and the processes governing interannual variability, a regional coupled ice-ocean model is applied to the Barents Sea for the period 1948-2007. Volume and characteristics of dense water are investigated with respect to the initial autumn surface salinity, atmospheric cooling, and sea-ice growth (salt flux). In the southern Barents Sea (Spitsbergen Bank and Central Bank) dense water formation is associated with advection of Atlantic Water into the Barents Sea and corresponding variations in initial salinities and heat loss at the air-sea interface. The characteristics of the dense water on the Spitsbergen Bank and Central Bank are thus determined by the regional climate of the Barents Sea. Preconditioning is also important to dense water variability on the northern banks, and can be related to local ice melt (Great Bank) and properties of the Novaya Zemlya Coastal Current (Novaya Zemlya Bank). The dense water mainly exits the Barents Sea between Frans Josef Land and Novaya Zemlya, where it constitutes 63% (1.2 Sv) of the net outflow and has an average density of 1028.07 kg m⁻³. An amount of 0.4 Sv enters the Arctic Ocean between Svalbard and Frans Josef Land. Covering 9% of the ocean area, the banks contribute with approximately 1/3 of the exported dense water. Formation on the banks is more important when the Barents Sea is in a cold state (less Atlantic Water inflow, more sea-ice). During warm periods with high throughflow more dense water is produced broadly over the shelf by general cooling of the northward flowing Atlantic Water. However, our results indicate that during extremely warm periods (1950s and late 2000s) the total export of dense water to the Arctic Ocean becomes strongly reduced.     

秋季巴伦支海海温异常对冬季我国渤海冰情的可能影响

本文利用美国NCEP/NCAR逐月的再分析资料、HadISST海温、中国160台站气温和反映渤海冰情轻重的渤海冰情等级资料,研究了前秋巴伦支海海温异常对后期渤海冰情和东亚冬季风的影响,并对相关的物理过程进行分析。结果表明,前秋巴伦支海关键区海温与该区域海冰密集度呈显著的负相关,且具有较好的持续性,通过调节随后冬季向大气释放的热通量,引起后期环流变化。偏高(偏低)年冬季亚洲纬向环流偏弱(偏强),东亚大槽加深(减弱),东亚冬季风加强(减弱),我国东北、华北及西北地区地区显著偏冷(偏暖),这与冬季渤海海冰异常的强度和范围都偏大(小)及与之相联系的环流异常相一致。进一步的分析揭示了联系上游关键区海温变化与后期东亚地区气候异常的重要途径,前秋巴伦支海海温偏高会导致200 hPa高度场形成一个自西向东的波列形式,在东亚局地Hadley环流异常的作用下,加强了我国北方地区地表的北风异常。因此,前秋巴伦支海海温异常可以作为冬季渤海冰情的预报因子。     

Characteristics of Winter Surface Air Temperature Anomalies in Moscow in 1970–2016 under Conditions of Reduced Sea Ice Area in the Barents Sea

On the basis of observational data on daily mean surface air temperature (SAT) and sea ice concentration (SIC) in the Barents Sea (BS), the characteristics of strong positive and negative winter SAT anomalies in Moscow have been studied in comparison with BS SIC data obtained in 1949–2016. An analysis of surface backward trajectories of air-particle motions has revealed the most probable paths of both cold and warm air invasions into Moscow and located regions that mostly affect strong winter SAT anomalies in Moscow. Atmospheric circulation anomalies that cause strong winter SAT anomalies in Moscow have been revealed. Changes in the ways of both cold and warm air invasions have been found, as well as an increase in the frequency of blocking anticyclones in 2005–2016 when compared to 1970–1999. The results suggest that a winter SIC decrease in the BS in 2005–2016 affects strong winter SAT anomalies in Moscow due to an increase in the frequency of occurrence of blocking anticyclones to the south of and over the BS.     

一个区域海洋——海冰——大气耦合模式中的北极气候偏差：年结果检验

The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature （SAT） over the Arctic Ocean, which contribute to the sea ice concentration （SIC） and sea surface temperature （SST） biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a l     

Influence of long-term regional and large-scale atmospheric circulation on the Baltic sea level

The connection between variations in the North Atlantic Oscillation (NAO) index and the Baltic sea level has been investigated for the period 1825–1997. The association between the NAO and the strength of the zonal geostrophic wind stress over the Northwest Atlantic suggests an NAO impact on Baltic sea level variations, because the monthly mean sea level mainly is determined by externally driven variations caused by wind conditions over the North Sea. Several period bands were found to have high correlation between oscillations in the winter (JFM) NAO index and the Baltic Sea winter mean sea level. The correlation was, however, higher in the 20th century than in the 19th. During the last two decades, the correlation between the NAO index and the sea level has been exceptionally high. The winter mean of a regional atmospheric circulation index had a correlation with the Kattegat winter mean sea level of 0.93. With the Baltic sea level the correlation was 0.91, compared with the NAO index correlation for the same period of 0.74. The regional index also showed a high correlation with the mean summer and mean autumn sea levels, when the corresponding seasonal NAO indices showed a weak connection. The temporal variation of the connection with the NAO index implies a regional atmospheric circulation occasionally differing from the large-scale circulation associated with the NAO. Seasonal means of the sea level in Stockholm do, however, reflect the regional wind climate to a large extent, and the Baltic sea level is a useful proxy for identifications of climatic dependencies in the region.     

Investigation of dynamic processes in the period of formation and development of the blocking anticyclone over European Russia in summer 2010

The blocking anticyclone (BA) observed in the summer of 2010 over the European part of Russia led to enormous economical damage, substantially increased the mortality of the population, and had serious negative consequences for human health. Dynamic processes in the troposphere, i.e., wave trains, which could contribute to anticyclone formation and sustenance, are investigated. In order to study these wave trains, three-dimensional Plumb vectors have been calculated and analyzed. It is shown that, in June 2010, three wave trains propagated eastward in the troposphere over the Atlantics. The first two wave trains, having reached Europe, continued to propagate in eastern and southeastern directions. Only the third wave train, upon reaching Europe, continued to propagate toward the northeast and, on June 17–19, entered northwestern Russia. The anticyclone, which started to form on June 18 precisely in this region, subsequently developed into a stable BA observed over European Russia up to mid-August. The propagation direction of the wave trains could change due to the formation of a double structure of the zonal flow in the troposphere. The wave trains are revealed in the middle of June in regions with increased cloudiness over the northwestern part of the Atlantic Ocean and over the northwestern and northern parts of the central United States. Eastwardpropagating wave trains, which could contribute to the intensification of the corresponding BAs that brought anomalously high temperatures to European Russia, were also revealed in July and August of 2010 and 1972. The calculated 10-day backward trajectories are analyzed to determine the character of motions of air particles that penetrated into the anticyclone over the region of Moscow during the 2010 summer in the period of its development.     

Role of sea ice in formation of wintertime arctic temperature anomalies

Numerical experiments with the ECHAM5 atmospheric general circulation model (AGCM) using the empirical HadISST1.1 data on sea surface temperature (SST) and sea ice concentration (SIC) in the 20th century as boundary conditions are analyzed. The experiments show that the model correctly reproduces the wintertime Arctic warming in the last 30 years of the 20th century but is unable to reproduce mid-20th century warming. Because the wintertime Arctic surface air temperature changes are closely related to SIC anomalies, it is assumed that one reason for this discrepancy is the lack of a negative SIC anomaly in the prescribed boundary conditions during a mid-20th century warm period. It is also shown that the model with-out prescribed ice cover changes does not reproduce a temperature trend in the Arctic in recent 30 years of the 20th century. The experimental results indicate that the mid-20th century warming was accompanied by a significant negative anomaly of the wintertime Arctic sea ice extent comparable to current trends and also point to a considerable contribution of natural variability to modern climate changes.     

2007-2018年黄渤海海冰气候特征及其对气象因子的响应

基于美国国家冰雪数据中心 （NSIDC） 海冰资料、美国国家环境预报中心 （NCEP） 再分析格点数据和黄渤海近岸13个气象站点逐日气温数据,通过相关分析和合成分析,研究了 2007-2018 年黄渤海海冰范围的变化特征,探讨了近 12 年黄渤海海冰范围对近岸陆地气温、大气环流和局地天气过程的响应。结果表明: （1） 黄渤海海冰范围年际振荡明显,近 12 年呈现先增加后减小的趋势,与同期黄渤海近岸气温呈显著负相关关系;每年 1 月下旬至 2 月下旬是一年中海冰范围最大的时期。（2） 海冰范围偏大与偏小年份东亚地区 500 hPa 大气环流形势呈现出近乎相反的分布。 （3） 东亚阻塞形势的建立是黄渤海海冰范围爆发性增大的一个前兆信号,它带来的大风降温天气是造成黄渤海海冰范围爆发性增大的重要原因.     

Autumn atmospheric preconditioning for interannual variability of wintertime sea-ice in the Okhotsk Sea

Relations in year-to-year variability between wintertime Sea-Ice Concentrations (SICs) in the Okhotsk Sea and atmospheric anomalies consisting of zonal and meridional 1000-hPa wind speeds and 850-hPa air temperatures are studied using a singular value decomposition analysis. It is revealed that the late autumn (October–November) atmospheric conditions strongly influence sea-ice variability from the same season (late autumn) through late winter (February—March), in which sea-ice extent is at its maximum. The autumn atmospheric conditions for the positive sea-ice anomalies exhibit cold air temperature anomalies over the Okhotsk Sea and wind anomalies blowing into the Okhotsk Sea from Siberia. These atmospheric conditions yield anomalous ocean-to-atmosphere heat fluxes and cold sea surface temperature anomalies in the Okhotsk Sea. Hence, these results suggest that the atmospheric conditions affect the sea-ice through heat anomalies stored in sea-ice and oceanic fields. The late autumn atmosphere conditions are related to large 700-hPa geopotential height anomalies over the Bering Sea and northern Eurasia, which are related to a stationary Rossby wave propagation over the North Pacific and that from the North Atlantic to Eurasia, respectively. In addition, the late autumn atmospheric preconditioning also plays an important role in the decreasing trend in the Okhotsk sea-ice extent observed from 1980 to the mid-1990s. Based on the lagged sea-ice response to the late autumn atmosphere, a simple seasonal prediction scheme is proposed for the February–March sea-ice extent using four-month leading atmospheric conditions. This scheme explains 45% of the variance of the Okhotsk sea-ice extent.     

2013年北极最小海冰范围比2012年增加的原因分析

北极海冰范围从1979年有卫星观测资料以来呈现明显下降趋势,尤其是9月份。2012年9月北极海冰范围达到有观测记录以来的最小值,而2013年9月比2012年同期增加了60%。增加的区域主要在东西伯利亚海区、楚科奇海和波弗特海区。本文应用距平和经验模态分解方法,分析了美国国家冰雪数据中心的北极海冰卫星数据、欧洲预报中心的夏季底层大气环流数据和上层海洋的温度,指出2013年北极最小海冰范围比2012年在北冰洋太平洋扇区增加的原因,是由于表面气温(SAT)降低、海平面气压(SLP)升高、气旋式风场异常、表面空气中水汽含量(SH)降低以及海表面温度(SST)降低5个条件形成的冰-SAT、冰-SST和冰-汽(SH)3个正反馈机制共同作用造成的。     

北极高密集度冰区海冰的多时间尺度变化特征及其极端低值事件分析

利用美国冰雪中心(NSIDC)高分辨率海冰密集度等多种数据,定义了北极高密集度冰区(High concentration ice region:HCIR)海冰变化指数,在此基础上研究了1989—2017年HCIR海冰多尺度变化特征及其极端低值事件的可能形成原因。结果表明:北极HCIR海冰密集度具有显著的单峰型季节变化特征,4月密集度最高,9月密集度最低,年较差达17.70%,兼有夏季融冰期短、冬季结冰期长且持续稳定的特点。HCIR海冰存在显著的年际年代际变化,在2007年发生了年代际转折以后,海冰变化指数的年际变化幅度和频次明显加强,且在2016、2012、2007、2011、2008和2010年依次出现海冰密集度极端降低事件;2016年9月初HCIR海冰密集度达到历史最低值,接近50%。对HCIR海冰密集度极端低值事件的统计研究表明,29年间共出现874天(次)极端低值事件,约占总频次的8%;空间上海冰密集度的降低主要出现在沿HCIR边界线一带,存在巴伦支海-喀拉海北缘的斯瓦尔巴群岛-北地群岛和东西伯利亚-波弗特海两个中心区域,该空间分布与气旋式大气环流引起的北冰洋Ekman漂流的辐散分布相一致。这表明HCIR海冰密集度的极端降低与极涡的动力作用有关,同时风场对海冰的动力辐散作用还会引起HCIR开阔水域的扩大,进一步加强海冰反照率的正反馈机制,使得热力和动力作用耦合起来共同影响HCIR海冰的加速融化。     

Ocean–Atmosphere Interactions in the Barents Sea from Reanalyses Data

Izvestiya, Atmospheric and Oceanic Physics - In this study we detail the mechanism of positive feedback linking variability of the oceanic heat flux in the Barents Sea, the sea-ice area and the...     

北大西洋秋季“三极子”海温结构对冬季大气环流场的影响

利用NCEP再分析资料、Hadley中心的海表面温度(SST)资料等,从北大西洋秋季海表面温度异常(SSTA)变化入手,对其影响后期冬季大气环流场的机制进行了分析。研究结果如下:(1)北大西洋SST异常与大气环流异常之间存在着相互作用;(2)秋季北大西洋SSTA具有较好的持续性,"正负正"海温异常空间分布导致12月巴伦支海上空500hPa位势高度异常偏高;(3)异常环流形势对应的海表面风异常场(SSWA)通过阶段性风-蒸发-SST异常反馈机制(WES机制)利于海温异常分布的持续及对上空异常大气环流的反馈;(4)三极子海温结构中负异常海温自10月份开始有自西向东的移动,风作用下蒸发加大,伴随上升运动自欧洲西部爱尔兰群岛出现自西向东移动的降水正异常区,潜热释放有利于冬季巴伦支海上空的异常高压脊发展。研究表明,北大西洋秋季SSTA通过阶段性海气相互作用机制影响海洋温度分布和大气环流异常,对后期冬季中国东北部的气候变化产生影响。     

北极秋季海冰减少与亚洲大陆冬季温度异常

本文使用SVD等诊断分析方法探讨北极秋季海冰密集度与亚洲冬季温度异常之间的关系。结果表明,近30余年来,北极秋季海冰减少伴随着亚洲大陆冬季温度降低,但青藏高原地区、北冰洋和北太平洋沿岸除外。北极秋季海冰密集度减小激发欧亚大陆和北冰洋北部两个区域位势高度的改变,这种异常的变化模态从秋季持续到冬季。位势高度异常的负值中心位于巴伦支海和喀拉海。位势高度异常的正值中心位于蒙古区域。与重力位势高度异常伴随的风场异常为亚洲冬季温度降低提供自北向南的冷气流。随着北极海冰的不断减少,其与亚洲大陆冬季温度降低之间的关系将为气候长期预测提供参考。     

Arctic sea-ice motion and its relation to pressure field

Daily Arctic sea-ice motion maps during the winter seasons (December–March) from December 1988 to March 2003 derived from NSCAT, QuikSCAT, SSM/I, and AMSRE data by a wavelet analysis method have been merged with those derived from buoy data. These merged sea-ice motion data have been used to study the circulation regimes and winter-to-winter variability of Arctic sea-ice motion. The relation between sea-ice motion and the pressure field in the Arctic Ocean was also studied by applying Principal Component Analysis (PCA) to the monthly merged sea-ice motion data and the monthly pressure field data from IABP. The mean Arctic sea-ice motion map of the 15 winter seasons has two distinct features: the Beaufort Gyre and a cyclonic circulation system in the Eurasian Basin, which moves ice from the Laptev Sea to Fram Strait. The strengths and sizes of the two features change from one winter season to another. Seasons with a strong or normal Beaufort Gyre alternate with seasons with a weak or no Beaufort Gyre every one to three seasons. The principal components of the first two modes of PCA of the monthly sea-ice motion are closely correlated with their counterparts of the monthly pressure field in the Arctic Ocean. The mode-one components of these two anomalies alternate between anticyclonic and cyclonic circulation systems. The correlation between Arctic Oscillation indexes and the principal components of the first mode of PCA of the monthly Arctic sea-ice motion is low but statistically significant.     

巴伦支海海冰异常对初夏大气环流和东亚天气影响的数值研究

本文利用在ＮＣＡＲ气候模式ＣＣＭ１（Ｒ１５Ｌ１２）基础上改变为用于长期数值预报的ＣＣＭ１（Ｒ１５Ｌ７），以１９９１年５月２日１２时（ＧＭＴ）国家气象中心客观分析资料为初始场，分别以巴伦支海附近海域不同的海冰边界作为下垫面极冰条件，进行了相应相应的月长期数值预报试验。以研究该海区海冰对大气环流特别是东亚天气的影响。试验〈Ａ〉以接近于９１年５月平均冰边界作为极冰边界条件，试验〈Ｂ〉和试验〈Ｃ〉分别对应     

1982—2001年与2002—2021年北极秋季海冰的时空变化及原因

基于北极海冰密集度、海冰范围、大气环流和海温数据,研究了1982—2001年与2002—2021年两阶段各20 a间北极秋季海冰的时空变化特征及其原因。结果表明,近20 a（2002—2021年）北极海冰密集度的下降中心由过去（1982—2001年）的楚科奇海及白令海峡一带,转移至亚欧大陆海岸的巴伦支海附近,且海冰范围每10 a减少量由0.44×10⁶ km²增长至0.72×10⁶ km²,减少速度加快约64%。秋季北极海冰范围与海水表面温度（Sea Surface Temperature,SST）、表面气温（Surface Air Temperature,SAT）及比湿（Specific Humidity）均呈显著负相关。2002—2021年的相关系数较1982—2001年有所提高,且与温度相关系数最高的月份提前了一个月。通过对海水表面温度、表面气温、比湿、气压场和风场的经验正交分解（Empirical Orthogonal Function,EOF）可知,1982—2001年间,北极地区的温度及比湿的上升中心集中在楚科奇海及白令海峡一带;2002—2021年间,上升中心则转移至巴伦支海一带。气压场和风场在前后两阶段也出现了中心转移的分布变化。北极地区大气与海洋环流各因素的协同变化影响着北极海冰的消融。