Microwave signatures of the sea ice in the east Greenland current

Airborne microwave radiometer measurements at 5, 17, and 34 GHz have been carried out over the East Greenland Current. Sea ice signatures have been established for some of the basic ice types like first-year ice and multiyear ice. Other signatures have been experienced like that of presumably very old arctic ice and signatures associated more with the snow cover on the ice than with the ice itself. During MIZEX-83 measurements of total ice concentration were carried out.     

Effect of a snow cover on microwave backscatter from sea ice

The effect of a snow cover on sea ice upon radar backscatter at microwave frequencies (X- andKu-baud) can be important. The effect of scattering from the snow cover on thesigmadegof first-year ice is shown to be severe (5 cm of dry snow can raisesigmadegby 8 dB at 9 GHz), while that onsigmadegof multiyear ice is shown to be smaller. The low thermal conductivity of snow compared to that of sea ice effectively raises the temperature of the upper surface of the ice, resulting in higher dielectric constants for the ice, thereby modifying the backscatter both from the ice surface and from the scattering volume. The temperature effect of a 10-cm snow cover on 3-m-thick multiyear ice is to lower thesigmadegby only about 0.3 dB for air temperature of-20degC. The effect on 1-m-thick first-year ice is even less. Hence, the volume-scattering effect of snow is more important than the temperature effect. The presence of a wet snow cover can block the volume-scattering contribution of the multiyear ice. The effect of wet snow cover on first-year ice should be smaller than that Of dry, snow, becausesigmadegof wet snow is lower than that of dry snow.     

Four years of low-altitude sea ice broad-band backscatter measurements

The ability to use radar to discriminate Arctic Sea ice types has been investigated using surface-based and helicopter-borne scatterometer systems. The surface-based FM/CW radar operated at 1.5 GHz and at multiple frequencies in the 8-18-GHz region. Measurements were made at angles of10degto70degfrom nadir. The helicopter-based radar operated at the 8-18-GHz frequencies with incidence angles of0degto60deg. Extensive surface-truth measurements were made at or near the time of backscattar measurement to describe the physical and electrical properties of the polar scene. Measurements in the 8-18-GHz region verify the ability to discriminate multiyear, thick first-year, thin first-year, and pressure-ridged sea ice and lake ice. The lowest frequency, 9 GHz, was found to provide the greatest contrast between these ice categories, with significant levels of separation existing between angles from15degto70deg. The radar cross sections for like antenna polarizations, VV and HH, were very similar in absolute level and angular response. Cross-polarization, VH and HV, provided the greatest contrast between ice types, The 1.5-GHz measurements showed that thick first-year, thin first-year, and multiyear sea ice cannot be distinguished at10degto60degincidence angles with like polarization, VV, by backscatter alone; but that undeformed sea ice can be discriminated from pressure-ridged ice and lake ice. The effect of snow cover on the backscatter from thick first-year ice was also investigated. It contributes on the order of 0 to 4 dB, depending on frequency and incidence angle; the contribution of the snow layer increased with increasing frequency. Snow cover on smooth lake ice was found to be a major backscatter mechanism. Summer measurements demonstrate the inability to extend the knowledge of the backscatter from sea ice under spring conditions to all seasons.     

Stress and strain instruments developed for field measurements ofice

The instruments developed and operational experience gained in the measurement of strain rates and stresses in floating sea ice are described to indicate the total global loads occurring naturally against an artificial island or similar structure. A delta strainmeter and a thin-disk stress sensor were developed to service particular measurement needs for which suitable equipment was not available. The loading conditions studied have included slow-moving winter first-year ice at Tarsiut, Mukluk, and Kaubvik Islands in the Beaufort Sea, freely moving summer multiyear ice at Hans Island, and a pack-ice mixture at Katie's Floeberg. The instruments have also been deployed on a surging glacier on Spitzbergen in Norway     

基于AMSR-E数据的多年冰密集度反演算法研究

In recent years, the rapid decline of Arctic sea ice area(SIA) and sea ice extent(SIE), especially for the multiyear(MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square(rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.     

Bayesian classification of the ice cover of the Arctic seas

A classification of sea ice in the Arctic by age (multiyear; first-year; and first-year deformed ice, nilas, etc.) is developed based on the Bayesian approach using satellite radar data and taking into account regional peculiarities of these types of ice for different sectors of the Arctic. Estimations of a priori probabilities for each ice type, which are required for the use of the Bayesian classification, are obtained by the analysis of ice charts in the Arctic seas developed at the AARI in 2008–2013 using satellite data. A posterior probabilities are estimated visually by an expert. Types of sea ice distinguished by the expert on satellite images make it possible to create sample values of the radar-scattering cross section (RSCS). Examples of the proposed Bayesian classification of ice in the Laptev Sea according to Envisat satellite data are given.     

Arctic sea ice long-term dynamics according to the satellite microwave data

The main results of processing the long-term satellite data in different spectral ranges and with different spatial resolutions used to map Arctic sea ice parameters are presented. The advantages of the methods developed in order to estimate these parameters on the basis of microwave sensor measurements are indicated. The specific features of the long-term dynamics of the main sea ice geophysical parameters (the sea ice area and distribution during the summer minimum, ice age structure and thickness, multiyear ice concentration, times of ice melt and freeze onset, etc.) are presented. The effect of changes in sheet ice on the status of large Arctic mammals is estimated.     

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。     

Discrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF)

Abstract

Sea ice type is one of the most sensitive variables in Arctic sea ice monitoring, and it is important for the retrieval of ice thickness. In this study, we analyzed various waveform features that characterize the echo waveform shape and Sigma0 (i.e., backscatter coefficient) of CryoSat-2 synthetic aperture radar altimeter data over different sea ice types. Arctic and Antarctic Research Institute operational ice charts were input as reference. An object-based random forest (ORF) classification method is proposed with overall classification accuracy of 90.1%. Accuracy of 92.7% was achieved for first-year ice (FYI), which is the domain ice type in the Arctic. Accuracy of 76.7% was achieved at the border of FYI and multiyear ice (MYI), which is better than current state-of-the-art methods. Accuracy of 83.8% was achieved for MYI. Results showed the overall accuracy of the ORF method was increased by ～8% in comparison with other methods, and the classification accuracy at the border of FYI and MYI was increased by ～10.5%. Nevertheless, ORF classification performance might be influenced by the selected waveform features, snow loading, and the ability to distinguish sea ice from leads.     

结合纹理特征的SVM海冰分类方法研究

海冰分类是遥感监测领域中的重要应用之一,海冰分类的准确性对于评估海冰冰情、保证航海安全和开辟北极航道具有重要的意义。针对海冰分类问题,本文选用Sentinel-1遥感数据,结合纹理特征分析,提出了一种改进的SAR海冰分类方法。该方法选用灰度共生矩阵提取特征值,通过实验得到适宜用于海冰分类的多特征组合,在此基础上利用支持向量机开展SAR海冰类型的分类研究。实验结果表明,该方法可以实现对海冰SAR图像中一年冰、多年冰和海水3种类型识别,与传统的海冰分类方法神经网络和最大似然法相比较,使用SVM分类方法,结合纹理特征开展海冰类型监测是可行的,同时也表明多特征组合有利于提高SAR图像的分类精度,从而验证了本方法的有效性,为海冰分类提供了一种新思路。     

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.     

基于卫星高度计的北极海冰厚度变化研究

A modified algorithm taking into account the first year(FY) and multiyear(MY) ice densities is used to derive a sea ice thickness from freeboard measurements acquired by satellite altimetry ICESat(2003–2008). Estimates agree with various independent in situ measurements within 0.21 m. Both the fall and winter campaigns see a dramatic extent retreat of thicker MY ice that survives at least one summer melting season. There were strong seasonal and interannual variabilities with regard to the mean thickness. Seasonal increases of 0.53 m for FY the ice and 0.29 m for the MY ice between the autumn and the winter ICESat campaigns, roughly 4–5 month separation, were found. Interannually, the significant MY ice thickness declines over the consecutive four ICESat winter campaigns(2005–2008) leads to a pronounced thickness drop of 0.8 m in MY sea ice zones. No clear trend was identified from the averaged thickness of thinner, FY ice that emerges in autumn and winter and melts in summer. Uncertainty estimates for our calculated thickness, caused by the standard deviations of multiple input parameters including freeboard, ice density, snow density, snow depth, show large errors more than 0.5 m in thicker MY ice zones and relatively small standard deviations under 0.5 m elsewhere. Moreover, a sensitivity analysis is implemented to determine the separate impact on the thickness estimate in the dependence of an individual input variable as mentioned above. The results show systematic bias of the estimated ice thickness appears to be mainly caused by the variations of freeboard as well as the ice density whereas the snow density and depth brings about relatively insignificant errors.     

北极冬季季节性海冰双模态特征分析

近年来北极海冰快速变化,北极中央区边缘正由以多年冰为主转为季节性海冰为主。通过对北极冬季季节性海冰的EOF分解发现,2002-2012年期间北极季节性海冰变化的前两模态主要体现为2005年和2007年的季节性海冰距平。其中第二模态主要体现了北极海冰在2005年的一种极端变化,而第一模态不仅体现了北极海冰在2007年的变化,还体现了北极季节性海冰的从负位相到正位相的转变。通过比较发现,在研究时段北极季节性海冰最主要的变化发生在北极太平洋扇区,在2007年,冬季季节性海冰距平发生位相转变,2007-2010年一直维持正位相,北极太平洋扇区冬季季节性海冰保持显著正距平。太平洋扇区表面温度最大异常也发生在2007年,从大气环流来看,2007年之后波弗特海区异常高压有利于夏季太平洋扇区海冰的减少,而西风急流的减弱有利于夏季波弗特海区异常高压的维持,结合夏季海冰速度,顺时针的冰速分布有利于海冰离开太平洋扇区,因而会导致冬季太平洋扇区季节性海冰转为正距平并且从2007年一直维持到2010年。     

The chemical, physical and structural properties of estuarine ice in Great Bay, New Hampshire

The purpose of this study was to provide general information on the chemical, physical and structural properties of estuarine ice and show how it compares with sea ice found at higher latitudes in order to determine whether the ice in Great Bay can be used as an analog in the study of arctic sea ice.Ice cores and water samples were collected during the 1983–1984 winter season at Adams Point in Great Bay, New Hampshire. Concentrations of chloride, nitrogen (as nitrate and nitrite), bromide, phosphate, sulfate and silicate were determined for samples chosen on the basis of identifiable stratigraphic layers (i.e. bubble size and shape, sediment layers, etc.).Similarities between ice formation in Great Bay and those in the arctic regions include the nature of the freezing process and the ice types produced. In addition, the distribution and concentration of chemical constituents were found to be similar to those observed in arctic sea ice. Factors affecting the chemistry of the ice in Great Bay include rainfall during the freezing season, the presence of sediment layers in the ice cores, the nature of incorporation of brine into the crystal structure of the ice and the drainage of brine.     

HY-2卫星扫描微波辐射计数据反演北极海冰漂移速度

本文基于最大互相关法,利用海洋二号（HY-2）卫星扫描微波辐射计37 GHz通道多时相垂直极化亮温数据,获取了北极海冰漂移速度。采用2012年和2013年国际北极浮标计划海冰现场观测数据,对利用微波辐射计亮温资料反演的冬季北极海冰漂移速度进行了定量验证,结果表明:流速和流向均方根误差分别为1.12 cm/s和16.37°,从一定程度上说明了HY-2卫星扫描微波辐射计亮温数据反演海冰漂移速度的可行性。此外,使用美国国防气象卫星F-17搭载的专用微波成像仪91 GHz通道垂直极化亮温,采用高斯拉普拉斯滤波方法进行处理,结合最大互相关法反演的海冰漂移速度,优于法国海洋开发研究院海冰漂移速度产品。     

1979-2012年北极海冰运动学特征初步分析

利用美国冰雪数据中心(NSIDC)发布的海冰速度和范围数据,本文分析了1979—2012年间北极海冰的运动学特征,以及北极海冰运动与分布范围演变之间的关系。结合欧洲中期天气预报中心(ECMWF)发布的2007和2012年高分辨率的气压场、风场数据,探讨了北极风场和气压场与海冰运动、辐散辐合和海冰面积的关系。结果表明,在1979-2012年间北极海冰平均运动速度呈显著增强的趋势,冬季海冰平均运动速度增加趋势明显强于夏季;北极、波弗特-楚科奇海域和弗拉姆海峡的冬、夏季海冰平均运动速度的增加率分别为2.1%/a和1.7%/a、2.0%/a和1.6%/a以及4.9%/a和2.2%/a。1979-2012年北极海冰平均运动速度和范围的相关性为-0.77,二者存在显著的负相关关系。北极冬季和夏季风场的长期变化趋势与海冰平均运动速度的变化趋势一致,冬季和夏季的相关系数分别为0.50和0.48。风场和气压场对海冰的运动、辐散及重新分布发挥着重要作用。2007年夏季,第234~273天波弗特海域一直被高压系统控制,波弗特涡旋加强,使得波弗特海域海冰聚集在北极中央区;顺时针的风场促使海冰向格陵兰岛和加拿大北极群岛以北聚合。2012年,白令海峡和楚科奇海域处于低压和高压系统的交界处,盛行偏北风,海冰从北极东部往西部输运,加拿大海盆的多年海冰因离岸运动而辐散,向楚科奇海域的海冰输运增加,受太平洋入流暖水影响,移入此区域的海冰加速融化,从而加剧海冰的减少。     

基于高效统计模型预测9月北极航道沿线海冰范围

The rapid decrease in Arctic sea ice cover and thickness not only has a linkage with extreme weather in the midlatitudes but also brings more opportunities for Arctic shipping routes and polar resource exploration, both of which motivate us to further understand causes of sea-ice variations and to obtain more accurate estimates of seaice cover in the future. Here, a novel data-driven method, the causal effect networks algorithm, is applied to identify the direct precursors of September sea-ice extent covering the Northern Sea Route and Transpolar Sea Route at different lead times so that statistical models can be constructed for sea-ice prediction. The whole study area was also divided into two parts: the northern region covered by multiyear ice and the southern region covered by seasonal ice. The forecast models of September sea-ice extent in the whole study area(TSIE) and southern region(SSIE) at lead times of 1–4 months can explain over 65% and 79% of the variances, respectively,but the forecast skill of sea-ice extent in the northern region(NSIE) is limited at a lead time of 1 month. At lead times of 1–4 months, local sea-ice concentration and sea-ice thickness have a larger influence on September TSIE and SSIE than other teleconnection factors. When the lead time is more than 4 months, the surface meridional wind anomaly from northern Europe in the preceding autumn or early winter is dominant for September TSIE variations but is comparable to thermodynamic factors for NSIE and SSIE. We suggest that this study provides a complementary approach for predicting regional sea ice and is helpful in evaluating and improving climate models.     

The physical structures of snow and sea ice in the Arctic section of 150°-180°W during the summer of 2010

The physical structures of snow and sea ice in the Arctic section of 150°-180°W were observed on the basis of snow-pit, ice-core, and drill-hole measurements from late July to late August 2010. Almost all the investigated floes were first-year ice, except for one located north of Alaska, which was probably multi-year ice transported from north of the Canadian Arctic Archipelago during early summer. The snow covers over all the investigated floes were in the melting phase, with temperatures approaching 0℃ and densities of 295-398 kg/m3 . The snow covers can be divided into two to five layers of different textures, with most cases having a top layer of fresh snow, a round-grain layer in the middle, and slush and/or thin icing layers at the bottom. The first-year sea ice contained about 7%-17% granular ice at the top. There was no granular ice in the lower layers. The interior melting and desalination of sea ice introduced strong stratifications of temperature, salinity, density, and gas and brine volume fractions. The sea ice temperature exhibited linear cooling with depth, while the salinity and the density increased linearly with normalized depth from 0.2 to 0.9 and from 0 to 0.65, respectively. The top layer, especially the freeboard layer, had the lowest salinity and density, and consequently the largest gas content and the smallest brine content. Both the salinity and density in the ice basal layer were highly scattered due to large differences in ice porosity among the samples. The bulk average sea ice temperature, salinity, density, and gas and brine volume fractions were-0.8℃, 1.8, 837 kg/m3 , 9.3% and 10.4%, respectively. The snow cover, sea ice bottom, and sea ice interior show evidences of melting during mid-August in the investigated floe located at about 87°N, 175°W.     

Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data

Sea-ice concentration is a key item in global climate change research.Recent progress in remotely sensed sea-ice concentration product has been stimulated by the use of a new sensor,advanced microwave scanning radiometer for EOS(AMSR-E),which offers a spatial resolution of 6 km×4 km at 89GHz.A new inversion algorithm named LASI(linear ASI) using AMSR-E 89GHz data was proposed and applied in the antarctic sea areas.And then comparisons between the LASI ice concentration products and those retrieved by the other two standard algorithms,ASI(arctic radiation and turbulence interaction study sea-ice algorithm) and bootstrap,were made.Both the spatial and temporal variability patterns of ice concentration differences,LASI minus ASI and LASI minus bootstrap,were investigated.Comparative data suggest a high result consistency,especially between LASI and ASI.On the other hand,in order to estimate the LASI ice concentration errors introduced by the tie-points uncertainties,a sensitivity analysis was carried out.Additionally an LASI algorithm error estimation based on the field measurements was also completed.The errors suggest that the moderate to high ice concentration areas(>70%) are less affected(never exceeding 10%) than those in the low ice concentration.LASI and ASI consume 75 and 112 s respectively when processing the same AMSR-E time series thourghout the year 2010.To conclude,by using the LASI algorithm,not only the seaice concentration can be retrieved with at least an equal quality as that of the two extensively demonstrated operational algorithms,ASI and bootstrap,but also in a more efficient way than ASI.     

渤海和北极海冰组构及晶体结构特征分析

渤海一年冰的组构和晶体结构表现出的冰的非连续生长速率使得冰层底部具有气泡含量不同的许多分层;静水生长的灰冰具有典型的粒状冰和柱状冰;融化-重冻结冰和重叠冰具有特定的晶体结构.位于北冰洋72°24.037'N,153°33.994'W,长2.2m的冰心样为三年冰,并且发现其内有一种新的晶体类型,定义为碎屑凝聚冰.由位于北冰洋74°58.614'N,160°31.830'W,长4.86m的冰心样的晶体结构分析发现它过去为冰脊,后经融化-冻结改造形成冰丘的证据.