喀拉海峡潮-地相互作用激发非线性内波的数值模拟

Nonlinear internal waves(NIWs) are ubiquitous around the Kara Sea, a part of the Arctic Ocean that is north of Siberia. Three hot spot sources for internal waves, one of which is the Kara Strait, have been identified based on Envisat ASAR. The generation and evolution of the NIWs through the interactions of the tide and topography across the strait is studied based on a nonhydrostatic numerical model. The model captures most wave characteristics shown by satellite data. A typical inter-packets distance on the Barents Sea side is about 25 km in summer, with a phase speed about 0.65 m/s. A northward background current may intensify the accumulation of energy during generation, but it has little influence on the other properties of the generated waves. The single internal solitary wave(ISW) structure is a special phenomenon that follows major wave trains, with a distance about 5–8 km. This wave is generated with the leading wave packets during the same tidal period. When a steady current toward the Kara Sea is included, the basic generation process is similar, but the waves toward the Kara Sea weaken and display an internal bore-like structure with smaller amplitude than in the control experiment. In winter, due to the growth of sea ice, stratification across the Kara Strait is mainly determined by the salinity, with an almost uniform temperature close to freezing. A pycnocline deepens near the middle of the water depth(Barents Sea side), and the NIWs process is not as important as the NIWs process in summer. There is no fission process during the simulation.     

北极气旋的季节、年际变化及其与北极海冰、大气遥相关的关系

The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts(ECMWF) ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU(central Russia)subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation(AO), North Atlantic Oscillation(NAO) and Pacific-North American Pattern(PNA). Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.     

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.     

2007和2012年北极最小海冰范围空间分布不同的原因分析

Satellite records show the minimum Arctic sea ice extents(SIEs) were observed in the Septembers of 2007 and2012, but the spatial distributions of sea ice concentration reduction in these two years were quite different.Atmospheric circulation pattern and the upper-ocean state in summer were investigated to explain the difference.By employing the ice-temperature and ice-specific humidity(SH) positive feedbacks in the Arctic Ocean, this paper shows that in 2007 and 2012 the higher surface air temperature(SAT) and sea level pressure(SLP)accompanied by more surface SH and higher sea surface temperature(SST), as a consequence, the strengthened poleward wind was favorable for melting summer Arctic sea ice in different regions in these two years. SAT was the dominant factor influencing the distribution of Arctic sea ice melting. The correlation coefficient is –0.84 between SAT anomalies in summer and the Arctic SIE anomalies in autumn. The increase SAT in different regions in the summers of 2007 and 2012 corresponded to a quicker melting of sea ice in the Arctic. The SLP and related wind were promoting factors connected with SAT. Strengthening poleward winds brought warm moist air to the Arctic and accelerated the melting of sea ice in different regions in the summers of 2007 and 2012. Associated with the rising air temperature, the higher surface SH and SST also played a positive role in reducing summer Arctic sea ice in different regions in these two years, which form two positive feedbacks mechanism.     

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).     

Rapid decrease in Antarctic sea ice in recent years

A 41-year Antarctic sea ice concentration(SIC) dataset derived from satellite passive microwave radiometers during the period of 1979–2019 has been used to analyze sea ice changes in recent decades. The trends of SIC and sea ice extent(SIE) are calculated during the periods of 1979–2019, 1979–2013, and 2014–2019. The trends show regionally dependent features. The SIC shows an increasing trend in most of the regions except the Bellingshausen Sea and Amundsen Sea(BA) during 1979–2019 and 1979–2013. The SIE trend shows a decreasing or decelerating trend in the period of 1979–2019((6 835±2 210) km2/a) compared with the 1979–2013 period((18 600±2 203) km~2/a). In recent years(2014–2019), the SIC and SIE have exhibited decreasing trends(–(34 567±3 521) km~2/month), especially in the Weddell Sea(WS) and Ross Sea(RS) during summer and autumn. The trends are related to regionally dependent causes. The analyses show that the SIC and SIE decreased in response to the warming trend of 2 m air temperature(T_(a-2m)) and have exhibited a good relationship with T_(a-2m) in summer and autumn in recent years. The sea ice decrease in the Antarctic is mainly caused by increases in absorbed energy and southward energy transportation in recent years, such as the increase in gained solar radiation and moist static energy from the south, which demonstrate notable regional characteristics. In the WS region, the local positive feedback from the additional absorbed solar radiation, resulting in warmer air and reduced sea ice, is the main reason for the sea ice decrease in recent years. The increase in southward energy transport has also favored a decrease in sea ice. In the RS region, the increase in southward-transported moist static energy has contributed to the decrease in sea ice, and the increases in cloud cover and longwave radiation have prevented sea ice growth.     

基于HY-2A散射计数据的极区海冰范围反演方法及其评估

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established.Four parameters are used for distinguishing between sea ice and ocean with Fisher's linear discriminant analysis method.The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013–2014 from the scatterometer aboard HY-2A(HY-2A-SCAT) backscatter data.The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder(SSMIS) sea ice concentration data.For both hemispheres,the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period.Compared with Synthetic Aperture Radar(SAR) imagery,the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge.Over some ice edge area,the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.     

Quantifying the contribution of natural variability to September Arctic sea ice decline

Arctic sea ice extent has been declining in recent decades. There is ongoing debate on the contribution of natural internal variability to recent and future Arctic sea ice changes. In this study, we contrast the trends in the forced and unforced simulations of carefully selected global climate models with the extended observed Arctic sea ice records. The results suggest that the natural variability explains no more than 42.3% of the observed September sea ice extent trend during 35 a(1979–2013) satellite observations, which is comparable to the results of the observed sea ice record extended back to 1953(61 a, less than 48.5% natural variability). This reinforces the evidence that anthropogenic forcing plays a substantial role in the observed decline of September Arctic sea ice in recent decades. The magnitude of both positive and negative trends induced by the natural variability in the unforced simulations is slightly enlarged in the context of increasing greenhouse gases in the 21st century.However, the ratio between the realizations of positive and negative trends change has remained steady, which enforces the standpoint that external forcing will remain the principal determiner of the decreasing Arctic sea ice extent trend in the future.     

欧亚大陆冬季温度对北极海冰减少的敏感性及非线性响应研究

The recent decline in the Arctic sea ice has coincided with more cold winters in Eurasia.It has been hypothesized that the Arctic sea ice loss is causing more mid-latitude cold extremes and cold winters,yet there is lack of consensus in modeling studies on the impact of Arctic sea ice loss.Here we conducted modeling experiments with Community Atmosphere Model Version 5(CAM5) to investigate the sensitivity and linearity of Eurasian winter temperature response to the Atlantic sector and Pacific sector of the Arctic sea ice loss.Our experiments indicate that the Arctic sea ice reduction can significantly affect the atmospheric circulation by strengthening the Siberian High,exciting the stationary Rossby wave train,and weakening the polar jet stream,which in turn induce the cooling in Eurasia.The temperature decreases by more than 1°C in response to the ice loss in the Atlantic sector and the cooling is less and more shifts southward in response to the ice loss in the Pacific sector.More interestingly,sea ice loss in the Atlantic and Pacific sectors together barely induces cold temperatures in Eurasia,suggesting the nonlinearity of the atmospheric response to the Arctic sea ice loss.     

A PROBABLE AVENUE TO EFFECT OF POLAR ICE ON NORTH PACIFIC SUBTROPICAL HIGH

This paper is based on the data for the period from 1953 to 1977, which are the monthly averaged ice cover in the Arctic area within 160° E-110° W and north of 50?N, the areal index of the North Pacific subtropical high and the monthly averaged sea surface temperature of the North Pacific. A statistical analysis of the lag correlations between the polar ice from November to July and the sea surface temperature from January to July, and the sea surface temperature from January to July and the subtropical high lagging zero through eleven months is performed.The analysis shows that the lag correlation regions between the polar ice during spring and the sea surface temperature almost coincide with the regions of the California Current and the paitial north equatorial current, and the regions of the California Current and the partial north equatorial current coincide with the principal lag correlation regions between the sea surface temperature and the subtropical high. All the results suggest that the tra     

末次盛冰期以来巴伦支海-喀拉海古海洋环境及海冰研究进展

巴伦支海-喀拉海是北冰洋最大的边缘海,能够对环境变化做出快速的响应和反馈,是全球气候变化最为敏感的区域之一,其古海洋环境演变及海冰变化研究是全球气候变化研究的重要组成部分。末次盛冰期以来,该区域的古海洋环境受到太阳辐射、海流强度、海平面变化、温盐环流和河流输入等因素影响发生了一系列不同尺度的波动。巴伦支海受到北大西洋暖水和极地冷水两大水团相互作用的影响,在水团交界处 （极锋) 由于不同水团性质的差异,导致其海水温度、盐度及海冰发生剧烈变化。而喀拉海则受到叶尼塞河和鄂毕河大量淡水输入影响,海流系统较巴伦支海相对复杂,沉积物主要来源于河流输入的陆源物质,并可以通过磁化率的分析明确区分两条河流的陆源物质。由于受到冷水和暖水的相互作用,巴伦支海-喀拉海海冰变化迅速,并且在全新世中晚期存在 0.4 ka 和 0.95 ka 的变化周期,但海冰变化的影响因素并不是单一的,而是气候系统内部各因子相互作用的结果。目前古海冰重建研究工作主要为定性研究,定量研究相对较少,所选用的重建指标也相对单一,另外存在年代框架差、分辨率低等不足。本文以巴伦支海和喀拉海为中心,总结了其快速气候突变事件、古温度盐度、海平面及海冰的变化,对影响因素进行了探讨,并通过分析末次盛冰期以来古海洋环境研究的不足,提出了相应的展望。     

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。     

热带太平洋海温异常对北极海冰的可能影响

本文利用1950-2015年间Hadley环流中心海冰和海温资料及NCEP/NCAR再分析资料,研究了热带太平洋海温异常对北极海冰的可能影响,并从大气环流和净表面热通量两个角度探讨了可能的物理机制。结果表明,在ENSO事件发展年的夏、秋季节,EP型与CP型El Niño事件与北极海冰异常的联系无明显信号。而La Niña事件期间北极海冰出现显著异常,并且EP型与CP型La Niña之间存在明显差异。EP型La Niña发生时,北极地区巴伦支海、喀拉海关键区海冰异常减少,CP型La Niña事件则对应着东西伯利亚海、楚科奇海地区海冰异常增加。在EP型La Niña发展年的夏、秋季节,热带太平洋海温异常通过遥相关波列,使得巴伦支海、喀拉海海平面气压为负异常并与中纬度气压正异常共同构成类似AO正位相的结构,形成的风场异常有利于北大西洋暖水的输入,同时造成暖平流,偏高的水汽含量进一步加强了净表面热通量收入,使得巴伦支海、喀拉海海冰异常减少。而在CP型La Niña发展年的夏季,东西伯利亚海、楚科奇海关键区受其东侧气旋式环流的影响,以异常北风分量占主导,将海冰从极点附近由北向南输送到关键区,海冰异常增加,而净表面热通量的作用较小。     

北极海冰输出区域海冰运动变化特征及其与北极航道适航性的关系

随着北极地区气候变暖的加剧,北极海冰正在急剧消融,海冰的减少增加了北极地区航道的适航性。本文利用遥感数据反演得到的海冰运动产品对北极海冰输出区域以及东北航道以北区域的海冰运动特征进行了量化。结果显示,从北极中央海域向弗拉姆海峡以及格陵兰海流出海冰的南向位移量呈现出显著增长趋势,海冰的平均南向位移量在2007-2014年间达到1511 km,是2007年之前（617 km）的两倍以上,反映了北极穿极流（TDS）强度在不断增强。通过长时间序列分析发现,春季东北航道以北区域的海冰北向漂移速度在喀拉海呈现+0.04 厘米/秒/年的显著增长趋势（P<0.05）。海冰北向漂移对于东北航道的开通具有显著的影响,在拉普捷夫海与喀拉海,海冰北向运动速度与航道适航期的决定系数分别达到0.33（P<0.001）和0.15（P<0.05）。东西伯利亚海、拉普捷夫海以及喀拉海存在冰间湖区域的春季海冰面积变化与航道的适航期密切相关,海冰的北向漂移对拉普捷夫海和喀拉海的海冰面积减少也有显著影响,这说明北向漂移促进了海冰的离岸输送,造成海冰面积减少的同时形成冰间水道或冰间湖促使航道开通。为探究大气环流指数对海冰运动以及东北航道适航期的影响,本文利用大气再分析数据计算了中央北极指数（CAI）和北极大气偶极子异常（DA）指数。相关性分析表明,CAI比DA更能解释东北航道的适航期,而且CAI能够解释北极海冰输出区域海冰南向位移量变化的45%。最近10年,夏季正相位的CAI进一步加强,通过加强海冰离岸输运和冰间湖活动加剧了东北航道区域海冰变薄及其强度变弱,从而促进了东北航道的开通。     

近年北极东北和西北航道开通状况分析

利用微波卫星遥感数据对北极东北航道和西北航道近年来的冰情变化,以及影响航道开通的关键区域和每年的开通状况进行了分析和总结,并对航道未来的可能冰情状况进行了展望,期望对航道利用者有所帮助。东北航道全线开通期主要集中在8月下旬至10月上旬,开通总天数多在40~50d;西北航道南线开通期主要集中在8月上中旬至10月上旬,开通总天数多在50~60d;西北航道北线开通时间主要集中在9月。东北航道冰情最为复杂的是连接拉普捷夫海和喀拉海的北地群岛区域海冰,也是影响航道开通的关键区。影响西北航道南线开通的关键主要是威廉王岛附近维多利亚海峡、威尔士王子岛东侧的皮尔海峡和北侧巴罗海峡区域的海冰状况;影响北线开通的关键区域是班克斯岛西北部的麦克卢尔海峡和梅尔维尔子爵海峡;东北航道可通航性优于西北航道。虽然气候变化大背景下北极海冰总量减少,但由于海冰流动性增强,局部海冰变化愈发复杂,海冰分布年际差异较大,需要加强北极海冰监测和预报能力,为未来航道利用提供保障。     

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。     

利用综合评分方法评估CMIP5模式对北极海冰的模拟能力

北极海冰冰盖自20世纪以来经历了前所未有的缩减,这使得北极海冰异常对大气环流的反馈作用日益显现。尽管目前的气候模式模拟北极海冰均为减少的趋势,但各模式间仍然存在较大的分散性。为了评估模式对于北极海冰变化及其气候效应的模拟能力,我们将海冰线性趋势和年际异常两者结合起来构造了一种合理的衡量指标。我们还强调巴伦支与卡拉海的重要性,因为前人研究证明此区域海冰异常是近年来影响大尺度大气环流变异的关键因子。根据我们设定的标准,CMIP5模式对海冰的模拟可被归为三种类型。这三组多模式集合平均之间存在巨大的差异,验证了这种分组方法的合理性。此外,我们还进一步探讨了造成模式海冰模拟能力差别的潜在物理因子。结果表明模式所采用的臭氧资料集对海冰模拟能力有显著的影响。     

Arctic summer sea ice phenology including ponding from 1982 to 2017

Information on the Arctic sea ice climate indicators is crucial to business strategic planning and climate monitoring. Data on the evolvement of the Arctic sea ice and decadal trends of phenology factors during melt season are necessary for climate prediction under global warming. Previous studies on Arctic sea ice phenology did not involve melt ponds that dramatically lower the ice surface albedo and tremendously affect the process of sea ice surface melt. Temporal means and trends of the Arctic sea ice phenology from 1982 to 2017 were examined based on satellite-derived sea ice concentration and albedo measurements. Moreover, the timing of ice ponding and two periods corresponding to it were newly proposed as key stages in the melt season. Therefore, four timings, i.e., date of snow and ice surface melt onset (MO), date of pond onset (PO), date of sea ice opening (DOO), and date of sea ice retreat (DOR); and three durations, i.e., melt pond formation period (MPFP, i.e., MO–PO), melt pond extension period (MPEP, i.e., PO–DOR), and seasonal loss of ice period (SLIP, i.e., DOO–DOR), were used. PO ranged from late April in the peripheral seas to late June in the central Arctic Ocean in Bootstrap results, whereas the pan-Arctic was observed nearly 4 days later in NASA Team results. Significant negative trends were presented in the MPEP in the Hudson Bay, the Baffin Bay, the Greenland Sea, the Kara and Barents seas in both results, indicating that the Arctic sea ice undergoes a quick transition from ice to open water, thereby extending the melt season year to year. The high correlation coefficient between MO and PO, MPFP illustrated that MO predominates the process of pond formation.     

北极巴伦支海海冰多年变化特征研究

本文采用2003～2016年SSMI海冰密集度和NCEP气温、风场等数据,通过计算海冰覆盖率、增长期长度、冬季负积温和风拖曳力等参数,分析了巴伦支海海冰的变化特征及其与热力、动力影响因素之间的联系。结果显示,因西南部存在常年无冰区,巴伦支海14a平均的海冰覆盖率低于50%;覆盖率总体呈现下降趋势,冰情呈现"重—中等—轻"的变化过程,2012年后甚至出现夏季无冰的情况;增长期长度先增后减,起止时刻均有推迟;冬季负积温是影响巴伦支海冰情轻重的重要因素,与年平均海冰覆盖率距平和最大覆盖率的相关系数分别为-0.90和-0.89;风拖曳力的改变可在短期内引起海冰覆盖率急剧变化,是海冰边缘区产生流冰的主要原因,易对油气资源开发的海洋平台产生危害。