2018年北极太平洋区域夏季海冰物理及光学性质的研究

The reduction in Arctic sea ice in summer has been reported to have a significant impact on the global climate. In this study, Arctic sea ice/snow at the end of the melting season in 2018 was investigated during CHINARE-2018, in terms of its temperature, salinity, density and textural structure, the snow density, water content and albedo, as well as morphology and albedo of the refreezing melt pond. The interior melting of sea ice caused a strong stratification of temperature, salinity and density. The temperature of sea ice ranged from –0.8℃ to 0℃, and exhibited linear cooling with depth. The average salinity and density of sea ice were approximately 1.3 psu and 825 kg/m~3, respectively, and increased slightly with depth. The first-year sea ice was dominated by columnar grained ice. Snow cover over all the investigated floes was in the melt phase, and the average water content and density were 0.74% and 241 kg/m~3, respectively. The thickness of the thin ice lid ranged from 2.2 cm to 7.0 cm, and the depth of the pond ranged from 1.8 cm to 26.8 cm. The integrated albedo of the refreezing melt pond was in the range of 0.28–0.57. Because of the thin ice lid, the albedo of the melt pond improved to twice as high as that of the mature melt pond. These results provide a reference for the current state of Arctic sea ice and the mechanism of its reduction.     

CICE海冰模式中融池参数化方案的比较研究

冰面融池的反照率介于海水和海冰之间,获得较准确的融池覆盖率对认识极区气冰海耦合系统的热量收支有重要意义。在数值模式中,融池覆盖率的模拟结果直接影响到冰面反照率计算的准确性,本文对CICE5.0中的3种融池参数化方案进行了较系统的比较分析,结果显示3种方案各有优缺点,模拟结果都存在一些问题。cesm方案中判断融池冻结的条件更为合理。比较而言,融池冻结条件更改后的topo方案模拟的北冰洋区域平均融池覆盖率的年际变化幅度、融池覆盖范围、融池发展盛期持续时间与MODIS数据最接近。通过修改CICE5.0中的代码漏洞,研究了融池水的垂向渗透效应,这一效应会带来一些负面影响,如lvl方案中多年冰上几乎没有融池,说明目前的CICE模式中对于海冰渗透性演化或其他物理机制的处理仍有待改进。最后,着重讨论了topo方案的改进思路。     

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).     

基于Icepack海冰柱模式的融池反照率模拟研究

基于Icepack一维海冰柱模式,以2014年中国第6次北极科学考察长期冰站ICE06的3个融池的辐射参量和气象参量的连续观测作为大气强迫数据,对融池反照率及相关参量进行了模拟。本文引入观测的融池深度及海冰厚度作为初始条件,通过考虑融池覆盖率的作用,改进了平整冰融池参数化方案中海冰干舷的计算,修正了冰上可允许的最大融池深度,成功实现了对融池参数变化的模拟;同时,还修正了入射辐射分量比例系数与对应反照率分量权重系数不一致的问题。标准试验中,模拟的3个融池的反照率与观测结果之间的平均误差分别为0.01、0.05和0.13;入射辐射比例的敏感性试验结果表明,当可见光辐射比例增大8%时,融池反照率的模拟结果增大了6%～8%;融池表面再冻结试验的结果显示,当再冻结冰层厚度小于2 cm时,模拟冰面反照率的增加不足0.006,由此引起的表面能量收支减少了约1.1 W/m2。本文研究指出,准确的入射辐射比例对于改善北极海冰反照率模拟是必要的;并指出目前模式仍存在融池表面再冻结参数化、热收支计算、表面吹雪效应等有待解决的问题。     

中国第四次北极科学考察期间北极点附近海冰和融池的航空遥感观测

An aerial photography has been used to provide validation data on sea ice near the North Pole where most polar orbiting satellites cannot cover. This kind of data can also be used as a supplement for missing data and for reducing the uncertainty of data interpolation. The aerial photos are analyzed near the North Pole collected during the Chinese national arctic research expedition in the summer of 2010(CHINARE2010). The result shows that the average fraction of open water increases from the ice camp at approximately 87°N to the North Pole, resulting in the decrease in the sea ice. The average sea ice concentration is only 62.0% for the two flights(16 and 19 August 2010). The average albedo(0.42) estimated from the area ratios among snow-covered ice,melt pond and water is slightly lower than the 0.49 of HOTRAX 2005. The data on 19 August 2010 shows that the albedo decreases from the ice camp at approximately 87°N to the North Pole, primarily due to the decrease in the fraction of snow-covered ice and the increase in fractions of melt-pond and open-water. The ice concentration from the aerial photos and AMSR-E(The Advanced Microwave Scanning Radiometer-Earth Observing System) images at 87.0°–87.5°N exhibits similar spatial patterns, although the AMSR-E concentration is approximately 18.0%(on average) higher than aerial photos. This can be attributed to the 6.25 km resolution of AMSR-E, which cannot separate melt ponds/submerged ice from ice and cannot detect the small leads between floes. Thus, the aerial photos would play an important role in providing high-resolution independent estimates of the ice concentration and the fraction of melt pond cover to validate and/or supplement space-borne remote sensing products near the North Pole.     

Characterization of sea ice and its snow cover in the Arctic Pacific sector during the summer of 2016

A comprehensive analysis of sea ice and its snow cover during the summer in the Arctic Pacific sector was conducted using the observations recorded during the 7th Chinese National Arctic Research Expedition(CHIANRE-2016) and the satellite-derived parameters of the melt pond fraction(MPF) and snow grain size(SGS)from MODIS data. The results show that there were many low-concentration ice areas in the south of 78°N, while the ice concentration and thickness increased significantly with the latitude above the north of 78°N during CHIANRE-2016. The average MPF presented a trend of increasing in June and then decreasing in early September for 2016. The average snow depth on sea ice increased with latitude in the Arctic Pacific sector. We found a widely developed depth hoar layer in the snow stratigraphic profiles. The average SGS generally increased from June to early August and then decreased from August to September in 2016, and two valley values appeared during this period due to snowfall incidents.     

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman ?lter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.     

基于CryoSat-2数据的2010-2017年北极海冰厚度和体积的季节与年际变化特征

北极海冰变化影响着全球物质平衡、能量交换和气候变化。本文基于CryoSat-2测高数据和OSI SAF海冰密集度及海冰类型产品,分析了2010-2017年北极海冰面积、厚度和体积的季节和年际变化特征,结合NCEP再分析资料探讨了融冰期北极气温异常和夏季风异常对海冰变化的影响。结果表明,结冰期海冰面积的增加量波动较大,海冰厚度的增加量呈明显下降趋势。融冰期海冰厚度的减小量波动较大,2013年以后融冰期海冰面积的减小量逐年增加。海冰体积的变化趋势和面积变化更相似,融冰期的减小速率大于结冰期的增加速率。融冰期北极海表面大气温度异常与海冰融化量正相关。夏季风影响海冰的辐合和辐散,在弗拉姆海峡海冰的输运过程中起关键作用,促进了北冰洋表层水向大洋深层的传输。     

对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估

本文评估了地球系统模式FIO-ESM(First Institute of Oceanography-Earth System Model)基于集合调整Kalman滤波同化实验对1992-2013年北极海冰的模拟能力。结果显示:尽管同化资料只包括了全球海表温度和全球海面高度异常两类数据,而并没有对海冰进行同化,但实验结果能很好地模拟出与观测相符的北极海冰基本态和长期变化趋势,卫星观测和FIO-ESM同化实验所得的北极海冰覆盖范围在1992-2013年间的线性变化趋势分别为-7.06×105和-6.44×105 km2/(10a),同化所得的逐月海冰覆盖范围异常和卫星观测之间的相关系数为0.78。与FIO-ESM参加CMIP5(Coupled Model Intercomparison Project Phase 5)实验结果相比,该同化结果所模拟的北极海冰覆盖范围的长期变化趋势和海冰密集度的空间变化趋势均与卫星观测更加吻合,这说明该同化可为利用FIO-ESM开展北极短期气候预测提供较好的预测初始场。     

Spatio-temporal analysis of the melt onset dates over Arctic sea ice from 1979 to 2017

The melt onset dates(MOD) over Arctic sea ice plays an important role in the seasonal cycle of sea ice surface properties, which impacts Arctic surface solar radiation absorbed by the ice-ocean system. Monitoring interannual variations in MOD is valuable for understanding climate change. In this study, we investigated the spatio-temporal variability of MOD over Arctic sea ice and 14 Arctic sub-regions in the period of 1979 to 2017 from passive microwave satellite data. A set of mathematical and ...     

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。     

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.     

Geophysics of sea ice in the Baltic Sea: A review

With improved observation methods, increased winter navigation, and increased awareness of the climate and environmental changes, research on the Baltic Sea ice conditions has become increasingly active. Sea ice has been recognized as a sensitive indicator for changes in climate. Although the inter-annual variability in the ice conditions is large, a change towards milder ice winters has been detected from the time series of the maximum annual extent of sea ice and the length of the ice season. On the basis of the ice extent, the shift towards a warmer climate took place in the latter half of the 19th century. On the other hand, data on the ice thickness, which are mostly limited to the land-fast ice zone, basically do not show clear trends during the 20th century, except that during the last 20 years the thickness of land-fast ice has decreased. Due to difficulties in measuring the pack-ice thickness, the total mass of sea ice in the Baltic Sea is, however, still poorly known. The ice extent and length of the ice season depend on the indices of the Arctic Oscillation and North Atlantic Oscillation. Sea ice dynamics, thermodynamics, structure, and properties strongly interact with each other, as well as with the atmosphere and the sea. The surface conditions over the ice-covered Baltic Sea show high spatial variability, which cannot be described by two surface types (such as ice and open water) only. The variability is strongly reflected to the radiative and turbulent surface fluxes. The Baltic Sea has served as a testbed for several developments in the theory of sea ice dynamics. Experiences with advanced models have increased our understanding on sea ice dynamics, which depends on the ice thickness distribution, and in turn redistributes the ice thickness. During the latest decade, advance has been made in studies on sea ice structure, surface albedo, penetration of solar radiation, sub-surface melting, and formation of superimposed ice and snow ice. A high vertical resolution has been found as a prerequisite to successfully model thermodynamic processes during the spring melt period. A few observations have demonstrated how the river discharge and ice melt affect the stratification of the oceanic boundary layer below the ice and the oceanic heat flux to the ice bottom. In general, process studies on ice–ocean interaction have been rare. In the future, increasingly multidisciplinary studies are needed with close links between sea ice physics, geochemistry and biology.     

北极海冰输出研究综述

北极海冰对全球气候变化起重要的指示作用。除了海水冻结和融化过程以外,通过弗拉姆海峡(Fram Strait)的海冰输出也是影响北极海冰质量变化的重要动力机制。观测数据中的多源卫星遥感数据(尤其是辐射计观测数据)在获取大尺度连续观测方面具有独特的优势,在研究北极海冰输出面积通量变化方面有着广泛应用。本文总结了北极弗拉姆海峡、其他通道(S-FJL、FJL-SZ、加拿大群岛、Nares海峡通道)海冰输出面积或体积通量,着重介绍了弗拉姆海峡不同年龄海冰输出情况,并总结和分析了影响北极海冰输运的大尺度大气活动模态。最后,本文阐明北极海冰输出方面现有研究的不足之处以及未来的突破方向。     

BCC_CSM对北极海冰的模拟:CMIP5和CMIP6历史试验比较

本文利用北京气候中心气候系统模式(BCC_CSM)在最近两个耦合模式比较计划(CMIP5和CMIP6)的历史试验模拟结果,对北极海冰范围和冰厚的模拟性能进行了比较,结果表明:(1) CMIP6改善了CMIP5模拟海冰范围季节变化过大的问题,总体上更接近观测结果;(2)两个CMIP试验阶段中BCC_CSM模拟的海冰厚度都偏小,但CMIP6试验对夏季海冰厚度过薄问题有所改进。通过对影响海冰生消过程的冰面和冰底热收支的分析,我们探讨了上述模拟偏差以及CMIP6模拟结果改善的成因。分析表明,8?9月海洋热通量、向下短波辐射和反照率对模拟结果的误差影响较大,CMIP6试验在这些方面有较大改善;而12月至翌年2月,CMIP5模拟的北极海冰范围偏大主要是海洋热通量偏低所导致,CMIP6模拟的海洋热通量较CMIP5大,但北大西洋表层海流的改善才是巴芬湾附近海冰外缘线位置改善的主要原因。CMIP试验模拟的夏季海冰厚度偏薄主要是因为6?8月海洋热通量和冰面热收支都偏大,而CMIP6试验模拟的夏季海冰厚度有所改善主要是由于海洋热通量和净短波辐射的改善。海冰模拟结果的改善与CMIP6海冰模块和大气模块参数化的改进有直接和间接的关系,通过改变短波辐射、冰面反照率和海洋热通量,使BCC_CSM模式对北极海冰的模拟性能也得到有效提高。     

Interaction of an anticyclonic eddy with sea ice in the western Arctic Ocean: an eddy-resolving model study

The dramatic decline of summer sea ice extent and thickness has been witnessed in the western Arctic Ocean in recent decades, which hasmotivated scientists to search for possible factors driving the sea ice variability. An eddy-resolving, ice-ocean coupled model covering the entire Arctic Ocean is implemented, with focus on the western Arctic Ocean. Special attention is paid to the summer Alaskan coastal current (ACC), which has a high temperature (up to 5℃ ormore) in the upper layer due to the solar radiation over the open water at the lower latitude. Downstream of the ACC after Barrow Point, a surface-intensified anticyclonic eddy is frequently generated and propagate towards the Canada Basin during the summer season when sea ice has retreated away from the coast. Such an eddy has a warm core, and its source is high-temperature ACC water. A typical warm-core eddy is traced. It is trapped just below summer sea ice melt water and has a thickness about 60 m. Temperature in the eddy core reaches 2-3℃, and most water inside the eddy has a temperature over 1℃. With a definition of the eddy boundary, an eddy heat is calculated, which can melt 1 600 km² of 1mthick sea ice under extreme conditions.     

Dominant climate factors influencing the Arctic runoff and association between the Arctic runoff and sea ice

By using the Arctic runoff data from R-ArcticNET V4.0 and ArcticRIMS, trends of four major rivers flowing into the Arctic Ocean, whose climate factor plays an important role in determining the variability of the Arctic runoff, are investigated. The results show that for the past 30 years, the trend of the Arctic runoff is seasonally dependent. There is a significant trend in spring and winter and a significant decreasing trend in summer, leading to the reduced seasonal cycle. In spring, surface air temperature is the dominant factor influencing the four rivers. In summer, precipitation is the most important factor for Lena and Mackenzie, while snow cover is the most important factor for Yenisei and Ob. For Mackenzie, atmospheric circulation does play an important role for all the seasons, which is not the case for the Eurasian rivers. The authors further discuss the relationships between the Arctic runoff and sea ice. Significant negative correlation is found at the mouth of the rivers into the Arctic Ocean in spring, while significant positive correlation is observed just at the north of the mouths of the rivers into the Arctic in summer. In addition, each river has different relationship with sea ice in the eastern Greenland Sea.     

渤海冬季海冰反照率变化

渤海海冰对于大尺度气候变化比较敏感,基于CLARA-A1-SAL数据分析了1992~2008年冬季（12、1、2月）渤海海冰区域反照率的时空变化,同时分析了海冰密集度、海冰外延线面积和海水表面温度的变化与海冰反照率的相互关系。渤海海冰区域反照率随时间波动变化且变化趋势不明显,趋势线斜率仅为0.0388%。年际变化在9.93%~14.5%之间,平均值为11.79%。海冰反照率在1999,2000和2005等重冰年的值明显高于其他年份,在1994,1998,2001和2006等轻冰年的值较低。从单个月份反照率来看,12月海冰反照率的增加趋势（趋势线斜率0.0988%）明显高于1月和2月,1月的海冰反照率平均值（12.9%）高于另外两个月份。海冰反照率和海冰密集度呈明显的正相关关系;和海表面温度呈负相关关系（显著性水平90%）。     

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。     

地球系统模式FIO-ESM对北极海冰的模拟和预估

评估了地球系统模式FIO-ESM(First Institute of Oceanography-Earth System Model)基于CMIP5(Coupled Model Intercomparison Project Phase 5)的历史实验对北极海冰的模拟能力,分析了该模式基于CMIP5未来情景实验在不同典型浓度路径(RCPs,Representative Concentration Pathways)下对北极海冰的预估情况。通过与卫星观测的海冰覆盖范围资料相比,该模式能够很好地模拟出多年平均海冰覆盖范围的季节变化特征,模拟的气候态月平均海冰覆盖范围均在卫星观测值±15%范围以内。FIO-ESM能够较好地模拟1979-2005年期间北极海冰的衰减趋势,模拟衰减速度为每年减少2.24×104 km2,但仍小于观测衰减速度(每年减少4.72×104 km2)。特别值得注意的是:不同于其他模式所预估的海冰一直衰减,FIO-ESM对21世纪北极海冰预估在不同情景下呈现不同的变化趋势,在RCP2.6和RCP4.5情景下,北极海冰总体呈增加趋势,在RCP6情景下,北极海冰基本维持不变,而在RCP8.5情景下,北极海冰呈现继续衰减趋势。