冬季北极海冰与中国同期气温的关系

采用Hadley中心的海冰密集度资料和中国160站气温资料,对冬季北极海冰变化的主要模态进行了分析,定义了5个关键海区,重点讨论了冬季北极海冰异常与中国冬季气温的关系。结果表明,冬季北极海冰变化主要表现为第一模态,即太平洋、大西洋的海冰反位相分布。海冰变化的关键区域为区域Ⅰ巴伦支海、区域Ⅱ格陵兰海、区域Ⅲ戴维斯海峡、区域Ⅳ白令海以及区域Ⅴ鄂霍次克海。中国冬季平均气温、冬季最低气温、冬季最高气温均与北极关键海区的海冰异常有显著相关,但是与其对应的海区有所不同。     

冬季北极海冰与中国同期气温的关系

采用Hadley中心的海冰密集度资料和中国160站气温资料,对冬季北极海冰变化的主要模态进行了分析,定义了5个关键海区,重点讨论了冬季北极海冰异常与中国冬季气温的关系.结果表明,冬季北极海冰变化主要表现为第一模态,即太平洋、大西洋的海冰反位相分布.海冰变化的关键区域为区域Ⅰ巴伦支海、区域Ⅱ格陵兰海、区域Ⅲ戴维斯海峡、区...     

秋季区域海冰面积异常与冬季大气环流及东亚区域气候的关系

利用北极海冰面积资料和NCEP／NCAR再分析逐月高度场、风场资料以及中国160站气温资料，探讨秋季区域海冰异常与冬季大气环流及区域气候的关系，结果表明，秋季东西伯利亚海海冰的年际变化与北半球冬季大气环流及东亚冬季风有着密切的关系，秋季该海区海冰偏多（偏少），相应冬季东亚冬季风偏强（偏弱）；进一步分析发现秋季该海区海冰面积偏大（偏小），相应冬季中国大部地区气温明显偏低（偏高）。     

秋季北极海冰对中国冬季气温的影响

利用海冰资料、中国地面气候资料、环流特征量资料及NCEP/NCAR再分析资料,研究了秋季北极海冰变化对中国冬季平均气温、日气温变率以及异常低温天气的影响。分析结果表明,秋季北极海冰异常偏多年中国冬季常为暖冬;异常偏少年中国冬季常为冷冬,且异常低温天气出现频率更高,常发生低温灾害事件。秋季北极海冰通过影响后期的北半球极涡、东亚冬季风和西伯利亚高压进而影响中国冬季的平均气温,且通过影响冬季异常强西伯利亚高压的出现频次,影响中国冬季异常低温天气的发生频次。合成分析结果表明,秋季北极海冰异常偏少年的冬季,中国以北亚欧大陆高纬度的偏北风较强,且中国及其以北的中高纬度地区空气异常偏冷,导致极地和高纬度的冷空气易向南爆发,造成中国冬季气温偏低,异常低温天气频发。     

冬季北极涛动异常与新疆气温变化的关系

基于新疆96个气象站1961—2014年月平均气温、北极涛动指数和NCEP/NCAR再分析环流资料,分析了冬季北极涛动异常与新疆同期气温变化的关系及其影响。结果表明:冬季北极涛动指数与新疆冬季平均气温相关较好,42.7%的测站冬季气温与北极涛动指数的相关系数通过0.05显著性水平检验,主要集中在新疆北部地区。在冬季北极涛动指数偏强的7 a,新疆冬季气温偏高、偏低的概率分别为93.0%与6.3%;在冬季北极涛动指数异常偏低的14 a,冬季气温偏高、偏低的概率分别为41.5%和56.1%,偏低概率高于偏高概率。当冬季北极涛动指数偏强时,850 h Pa新疆及其北部广大区域盛行异常偏南风,不利于冷空气南下,新疆冬季气温高;反之,盛行异常偏北风,新疆冬季气温偏低。     

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。     

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     

秋季北极海冰变化对长江中下游地区冬季气温的影响

利用英国哈德莱中心海冰密集度资料,通过相关、合成等统计方法分析秋季北极海冰变化对长江中下游地区冬季气温的影响,发现拉普捷夫海以北及东西伯利亚海以东海区的海冰密集度变化可作为预测长江中下游地区冬季气温的前兆信号。当拉普捷夫海以北及东西伯利亚海以东海区海冰密集度偏高时,欧亚中高纬中部地区2 m气温经向梯度增大,乌拉尔山地区阻塞偏弱,欧亚中高纬以纬向环流为主,长江中下游冬季气温偏高,反之亦然。     

冬春季节北极海冰的年际和年代际变化

利用1953～1990年海冰密集度资料,研究了冬、春季节北极海冰的时空变化特征.结果表明:冬,春季节海冰变率大的海区主要有巴伦支海、格陵兰海、巴芬湾、戴维斯海峡以及白令海;在巴芬湾、戴维斯海峡和白令海海区,冬季海冰变率比春季的大;冬、春季节喀拉海、巴伦支海海冰面积均与春季白令海海冰面积呈反向变化关系,与巴芬湾、戴维斯海峡海冰面积也存在相反的变化趋势.分析还表明:北极海冰面积还表现出年代际时间尺度变化,尤其在冬季.春季格陵兰海海冰明显存在12年变化周期,而在冬、春季节,喀拉海、巴伦支海海冰存在l0年变化周期.     

2011年冬季长江流域气温持续偏低的可能成因探析

利用长江流域50个气象台站的气温资料、NCEP再分析资料和美国国家冰雪数据中心的北极海冰资料,分析了2011年冬季长江流域气温持续偏低的可能成因。结果表明,乌拉尔山阻塞高压和西伯利亚高压异常偏强及稳定维持,是长江流域冬季气温持续偏低的主要影响系统,其持续天数和强度均为1961年以来历史最大值。进一步分析表明,冬季乌山阻高和西伯利亚高压强度偏强和持续天数偏多易发生在La Nina年,500 hPa环流特征类似于La Nina年冬季平均环流条件;北极海冰面积异常偏小使冬季西伯利亚高压得到加强和乌山阻高持续。La Nina事件和北极海冰面积异常偏小是长江流域冬季气温持续偏低的重要外强迫因子。     

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.     

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.     

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.     

冬季欧亚大陆盛行天气型与北极增暖异常的可能联系

利用ERA-interim的再分析资料和英国大气数据中心的海冰密集度资料,通过复矢量经验正交分析方法(CVEOF),本文研究了自1979-2016年37个冬季(12月1日至次年2月28日)共3330 d对流层中层500 hPa欧亚盛行天气型主要时空变化特征及其与近年来北极对流层中、低层增暖异常和北极海冰减少的可能联系。结果表明,CVEOF1解释了总异常动能的15. 82%,其两个子模态空间型分别表现为三极子型(0°和180°位相)和偶极子型(90°和270°位相)。其中,180°和270°位相的天气型发生时,冬季北极对流层中、低层偏暖,盛行暖北极-冷欧亚的大气环流形势。前期秋季从巴伦支海海域以东到波弗特海海域的海冰密集度(SIC)异常偏少可能是其影响因素之一。近年来这两个位相(180°和270°位相)的发生频次逐渐增多,与冬季频发的极端低温事件有紧密联系。在2005/2006年和2011/2012年冬季的冷事件中,180°和270°位相的发生频次明显偏多。因此,秋季从巴伦支海海域以东到波弗特海海域的SIC偏少,冬季北极对流层中、低层异常偏暖,有利于180°和270°位相天气型盛行,可能是导致冬季极端天气事件频发的主要原因之一。     

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.     

Arctic climate change in 21st century CMIP5 simulations with EC-Earth

The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.     

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.