Crucial physical characteristics of sea ice in the Arctic section of 143°–180°W during August and early September 2008

Sea-ice physical characteristics were investigated in the Arctic section of 143°-180°W during August and early September 2008. Ship-based observations show that both the sea-ice thickness and concentration recorded during southward navigation from 30 August to 6 September were remarkably less than those recorded during northward navigation from 3 to 30 August, especially at low latitudes. Accordingly, the marginal ice zone moved from about 74.0°N to about 79.5°N from mid-August to early September. Melt-pond coverage increased with increasing latitude, peaking at 84.4°N, where about 27% of ice was covered by melt ponds. Above this latitude, melt-pond coverage decreased evidently as the ice at high latitudes experienced a relatively short melt season and commenced its growth stage by the end of August. Regional mean ice thickness increased from 0.8 (±0.5) m at 75.0°N to 1.5 (±0.4) m at 85.0°N along the northward navigation while it decreased rapidly to 0.6 (±0.3) m at 78.0°N along the southward navigation. Because of relatively low ice concentration and thin ice in the investigated Arctic sector, both the short-term ice stations and ice camp could only be set up over multiyear sea ice. Observations of ice properties based on ice cores collected at the short-term ice stations and the ice camp show that all investigated floes were essentially isothermal with high temperature and porosity, and low density and salinity. Most ices had salinity below 2 and mean density of 800-860 kg/m~3 . Significant ice loss in the investigated Arctic sector during the last 15 a can be identified by comparison with the previous observations.     

基于中国北极考察布放浮标观测和数值模拟的海冰和积雪厚度变化分析

Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition(CHINARE) buoy data.Two polar hydrometeorological drifters,known as Zeno? ice stations,were deployed during CHINARE 2003.A new type of high-resolution Snow and Ice Mass Balance Arrays,known as SIMBA buoys,were deployed during CHINARE 2014.Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain.A simple approach was applied to estimate the average snow thickness on the basis of Zeno~ temperature data.Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys.A one-dimensional snow and ice thermodynamic model(HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories.The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts(ECMWF).The Zeno~ buoys drifted in a confined area during 2003–2004.The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno~ buoy data.The SIMBA buoys drifted from 81.1°N,157.4°W to 73.5°N,134.9°W in 15 months during2014–2015.The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of2.45 m before the onset of snow melt in May 2015;the last observation was approximately 1 m in late November2015.The ice thickness based on HIGHTSI agreed with SIMBA measurements,in particular when the seasonal variation of oceanic heat flux was taken into account,but the modelled snow thickness differed from the observed one.Sea ice thickness derived from SIMBA data was reasonably good in cold conditions,but challenges remain in both snow and ice thickness in summer.     

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 latitud...     

北极夏季海冰单轴抗压强度研究

The results on the uniaxial compressive strength of Arctic summer sea ice are presented based on the samples collected during the fifth Chinese National Arctic Research Expedition in 2012(CHINARE-2012). Experimental studies were carried out at different testing temperatures(-3,-6 and-9°C), and vertical samples were loaded at stress rates ranging from 0.001 to 1 MPa/s. The temperature, density, and salinity of the ice were measured to calculate the total porosity of the ice. In order to study the effects of the total porosity and the density on the uniaxial compressive strength, the measured strengths for a narrow range of stress rates from 0.01 to 0.03 MPa/s were analyzed. The results show that the uniaxial compressive strength decreases linearly with increasing total porosity, and when the density was lower than 0.86 g/cm3, the uniaxial compressive strength increases in a power-law manner with density. The uniaxial compressive behavior of the Arctic summer sea ice is sensitive to the loading rate, and the peak uniaxial compressive strength is reached in the brittle-ductile transition range. The dependence of the strength on the temperature shows that the calculated average strength in the brittle-ductile transition range, which was considered as the peak uniaxial compressive strength, increases steadily in the temperature range from-3 to-9°C.     

Arctic sea ice distribution in summer based on aerial photos

1Introduction TheArcticOceanisoneoftheimportantcold sourcesontheearth,whichaffectsglobalclimateand oceancirculationseriously.Itsinteractionwithglobal climatesystemisrepresentedbyseaice,whichisthe mainfeatureonthesurfaceoftheArcticOcean(Aa- gaard,etal.,1989).Firstly,seaiceplaysapivotalrole intheheatandmassbalanceonthesurfaceoftheArc- ticOcean.Seaicenotonlyobstructstheheatexchange betweenatmosphereandocean,butalsoreflectsthe mostofthelocalsolarradiationbacktotheatmo- spherebecauseofitshighalb…     

基于CryoSat-2卫星测高数据的北极海冰体积估算方法

近30年来,北极海冰正发生着剧烈的变化。海冰体积是量化海冰变化的重要指标之一。本文以2015年CryoSat-2卫星测高数据和OSI SAF海冰类型产品为基础。提取了浮冰出水高度、积雪深度、海冰密集度、海冰类型等属性信息,通过数据内插、投影变换、栅格转换、空间重采样等工作将海冰属性信息统一为25 km×25 km分辨率的栅格数据集。根据流体静力学平衡原理,逐个估算栅格像元对应的海冰厚度值,将其与对应的海冰面积相乘,估算了北极海冰密集度大于75%海域的海冰体积,并分析了海冰厚度和体积的月变化和季节变化特征。用NASA IceBridge海冰厚度产品对反演的海冰厚度进行验证。结果表明二者相关系数为0.72,有较高的一致性。北极海冰平均厚度春季最大,夏季最小,分别约为2.99 m和1.77 m,最厚的海冰集中在格陵兰沿岸北部和埃尔斯米尔半岛以北海域。多年冰平均厚度大于一年冰。冬季海冰体积最大,约为23.30×103 km3,经过夏季的融化,减少了近70%。一年冰体积季节波动较大,而多年冰体积相对稳定,季节变化不明显。     

Some parameters in arctic sea ice dynamics from an expedition in the summer of 2003

1Introduction Seaiceoccupiesthemainpartofthesurfaceof theArcticOcean.ThefocusoftheSecondChineseNa- tionalArcticResearchExpedition(CHINAE-2003) wastounderstandthevariationsofarcticmarineenvi- ronmentsandtheseaiceeffectsontheclimatechanges ofglobalextent,inmiddleandlowerlatitudesareas, especiallyinChina.Therefore,thejointsea-ice-airob- servationforseaicestudieswasoneofthekeypro- jectsinCHINARE-2003.Theinvestigatedareacov- ered3000kmfromsouthtonorthand900kmfrom westtoeast.Seventemporali…     

Crucial physical characteristics of sea ice in the Arctic section of 143°-180°W during August and early September 2008

潮流是水下地形SAR成像的决定性因素之一,潮流的周期性变化使水下地形SAR成像与潮流场有密切的关系,同一水下地形不同时刻SAR影像不同。以台湾浅滩为例,基于5景不同时相的ERS-2 SAR影像和台湾浅滩实测水深数据,开展了水下地形SAR成像与潮流场的相关性分析。为了排除SAR影像自身成像质量对研究的影响,首先对5景SAR影像的成像质量进行评价,然后通过潮汐潮流数值计算确定SAR成像时刻的潮流场以及基于QuikScat散射计数据确定SAR成像时刻的海面风向。在上述基础上开展了SAR影像后向散射系数与实测水深的相关性分析,总结出水下地形SAR成像与潮流场的关系,结果表明,潮流场与水下地形SAR成像密切相关,当潮流流向与水下地形梯度方向一致或接近时,水下地形SAR成像效果最佳;对于同一水下地形,流向相反的两种潮流对应的SAR影像后向散射系数恰好相反,即SAR影像中的明暗条纹不同。相对于潮流流向的顺流与逆流风向的不同对水下地形SAR成像无影响。     

夏季北极海冰表皮温度实测资料与MODIS产品的对比分析

Ship-borne infrared radiometric measurements conducted during the Chinese National Arctic Research Expedition(CHINARE) in 2008, 2010, 2012, 2014, 2016 and 2017 were used for in situ validation studies of the Moderate Resolution Imaging Spectroradiometer(MODIS) sea ice surface temperature(IST) product.Observations of sea ice were made using a KT19.85 radiometer mounted on the Chinese icebreaker Xuelong between July and September over six years. The MODIS-derived ISTs from the satellites, Terra and Aqua, both show close correspondence with ISTs derived from radiometer spot measurements averaged over areas of 4 km×4 km, spanning the temperature range of 262–280 K with a ±1.7 K(Aqua) and ±1.6 K(Terra) variation. The consistency of the results over each year indicates that MODIS provides a suitable platform for remotely deriving surface temperature data when the sky is clear. Investigation into factors that cause the MODIS IST bias(defined as the difference between MODIS and KT19.85 ISTs) shows that large positive bias is caused by increased coverage of leads and melt ponds, while large negative bias mostly arises from undetected clouds. Thin vapor fog forming over Arctic sea ice may explain the cold bias when cloud cover is below 20%.     

北极夏季海冰反照率的观测和数值模拟试验

在中国第3次北极科学考察浮冰站开展了积雪/海冰反照率观测.本文对观测结果进行了分析,并结合一维高分辨雪/冰模式(HIGHTSI)对3个常用的反照率参数化方案在天气尺度的表现进行了评估.观测期间测站反照率变化范围0.75～0.85,其天气尺度变化同天气和表面冰、雪状况紧密相关,降雪和吹雪过程可改变表面积雪厚度及水平分布,...     

误差订正对2018年夏季次季节尺度海冰预测的作用

北极海冰次季节尺度预测在针对破冰船和商船的实际服务中十分重要,但常常受制于气候模拟的模拟能力。本研究提出了一种误差订正方法并分别应用到两个气候模式：海洋一所地球系统模式（FIOESM）和美国国家环境预报中心（NCEP）的气候预报系统（CFS）,来改善北极海冰60天尺度的预测。本研究的预测工作是中国第9次北极科学考察和2018年夏季中远集团北极商业航行的业务化海冰服务保障的重要部分。模式起报时间分别是2018年7月1日、8月1日和9月1日,预报时效均是60天。结果显示,FIOESM整体上低估了海冰密集度的数值,平均偏差可达30%。误差订正对海冰密集度（SIC）的均方根偏差（RMSE）的改进比例可达27%,对海冰外缘线（SIE）的整体偏差（IIEE）的改进比例为10%。而对于CFS,SIE在边缘区域的过高估计是其主要特点。误差订正导致了SIC的RMSE改进了7%,而对SIE的IIEE改进了17%。在海冰范围预测方面,FIOESM预测的最小范围数值和时间点都和观测接近,而CFS的预测结果偏差较大。另外和其他S2S模式的结果比较发现,本研究提出的误差订正方法对存在较大偏差的预测结果改进更为有效。     

北极海冰密集度预报对大气强迫敏感性的个例研究

A regional Arctic configuration of the Massachusetts Institute of Technology general circulation model （MIT-gcm） is used as the coupled ice-ocean model for forecasting sea ice conditions in the Arctic Ocean at the Na-tional Marine Environmental Forecasting Center of China （NMEFC）, and the numerical weather prediction from the National Center for Environmental Prediction Global Forecast System （NCEP GFS） is used as the atmospheric forcing. To improve the sea ice forecasting, a recently developed Polar Weather Research and Forecasting model （Polar WRF） model prediction is also tested as the atmospheric forcing. Their forecasting performances are evaluated with two different satellite-derived sea ice concentration products as initializa-tions： （1） the Special Sensor Microwave Imager/Sounder （SSMIS） and （2） the Advanced Microwave Scanning Radiometer for EOS （AMSR-E）. Three synoptic cases, which represent the typical atmospheric circulations over the Arctic Ocean in summer 2010, are selected to carry out the Arctic sea ice numerical forecasting experiments. The evaluations suggest that the forecasts of sea ice concentrations using the Polar WRF atmo-spheric forcing show some improvements as compared with that of the NCEP GFS.     

北极中央区海冰密集度与云量相关性分析

本文使用海冰密集度以及低云、中云、高云的日平均数据,借助滑动相关分析方法,研究了北极中央区海冰密集度与云量之间的相关性,分析了海冰与云的相互作用机制。研究表明,在春季海冰融化季节(4、5月)、秋季海冰冻结季节(10、11月),低云与海冰密集度之间表现为较好的负相关,表明在这段时间内冰区海面蒸发强烈,对低云的形成有重要贡献。在10月和11月,中云与海冰密集度也有很好的负相关,表明秋季低云可以通过抬升形成中云。高云与海冰密集度之间并没有明显的相关性,可能原因:一方面海冰的空间分布对高云无影响,另一方面,高云主要影响到达的短波辐射,从而影响海冰的融化和冻结速度,与海冰厚度有直接显著的关系,而与海冰密集度的关系不明显。此外,在海冰密集度与低云存在较好负相关的情况下会出现某些年份相关性不好的情况,我们的研究发现这是北极中央区与周边海区发生了海冰交换或云交换的结果。     

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。     

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.     

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。     

Molecular genetic diversity of bacteria in the bottom section of arctic sea ice from the Canada Basin

PCR-DGGE approach was used to analyze bacterial diversity in the bottom section of seven arctic sea ice samples colleted from the Canada Basin. Thirty-two 16S rDNA sequences were obtained from prominent DGGE bands. The closest relatives of these sequences are found to be those of cultivated or uncultured bacteria from antarctic or arctic sea ice. Phylogenetic analysis clustered these sequences or phylotypes within α- proteobacteria, γ-proteobacteria and CFB (cytophaga-flexibacter-bacteroides) group. Sequences belonging to γ-proteobacteria were dominant and members of the CFB group were highly abundant. It was suggested that the CFB group was the representative of the bottom section of sea ice samples.     

On the future navigability of Arctic sea routes: High-resolution projections of the Arctic Ocean and sea ice

The rapid Arctic summer sea ice reduction in the last decade has lead to debates in the maritime industries on the possibility of an increase in cargo transportation in the region. Average sailing times on the North Sea Route along the Siberian Coast have fallen from 20 days in the 1990s to 11 days in 2012–2013, attributed to easing sea ice conditions along the Siberian coast. However, the economic risk of exploiting the Arctic shipping routes is substantial. Here a detailed high-resolution projection of ocean and sea ice to the end of the 21st century forced with the RCP8.5 IPCC emission scenario is used to examine navigability of the Arctic sea routes. In summer, opening of large areas of the Arctic Ocean previously covered by pack ice to the wind and surface waves leads to Arctic pack ice cover evolving into the Marginal Ice Zone. The emerging state of the Arctic Ocean features more fragmented thinner sea ice, stronger winds, ocean currents and waves. By the mid 21st century, summer season sailing times along the route via the North Pole are estimated to be 13–17 days, which could make this route as fast as the North Sea Route.     

北极中央区海冰低密集度现象研究

近年,北极中央密集冰区出现海冰低密集度的异常现象。为了探讨这一现象的成因,本文使用ERA-Interim再分析资料,定义了北极中央区海冰低密集度（LCCA）指数,研究了2009-2016年的6-9月北极中央区发生的海冰低密集度现象。分析表明,研究时段内在北极中央区发生了6次明显的海冰低密集度（LCCA峰值）过程。在这些过程中,局地气温异常并不是导致海冰低密集度现象发生最主要的因素;海冰低密集度区域的形态及冰速场分布均与大气环流场相对应;在LCCA指数峰值发生前均有气旋中心出现在北冰洋70°N以北并伴随向北移动,气旋引起海冰辐散,同时所携带的较低纬度的热量导致海冰迅速融化。在6次过程中,有3次为气旋影响配合北极偶极子（DA）型环流。LCCA指数与84°N平均向北温度平流和北极中央区海冰速度散度呈正相关。在LCCA指数峰值前,温度平流对海冰低密集度区域形成的影响大于海冰辐散的影响。     

基于合成孔径雷达遥感的北极海冰总形变率分析

基于RADARSAT地球物理处理器系统(RGPS)的北极海冰运动散度、旋度和剪切产品,本文计算了北极海冰总形变率,给出了所有RGPS产品时空覆盖范围的总形变率空间分布和时间平均总形变率大于0.01d-1的概率分布。结果表明:对整个RGPS数据库而言(时间跨度从1996年11月至2008年4月),平均总形变率为0.020 4d-1,总形变率大于0.01d-1的数据样本为总样本的45.89%。总形变率高值主要分布在近岸海域,靠近北极点附近的总形变率相对较小。北极海冰总形变率随季节变化,夏季平均总形变率及总形变率大于0.01d-1发生概率要比冬季大,其中,夏季总形变率大于0.01d-1发生概率为59%,而冬季要比夏季低18%。其可能机制主要是,夏季北极地区温度升高,形成海冰融化-破碎-更易融化-更易破碎的放大效果,导致北极海冰总形变率变大。