北极熊栖息地稳定性的遥感评估方法

北极熊是北极最重要的哺乳动物之一,近年来数量却在减少。海冰作为北极熊狩猎、活动和繁殖的平台,是其栖息地的重要组成部分。因此其种群栖息地变化主要依赖于海冰变化。本文基于美国雪冰中心的海冰密集度和NOAA提供的ETOPO1基岩数据,分析了北极海冰密集度、开阔水域面积、海冰消退时间、海冰出现时间、开阔水域季节长度的年际变化,进而评价北极熊栖息地的稳定性。结果表明,海冰密集度呈现降低的趋势,开阔水域面积增大,多年冰数量减少,大多变为一年冰。海冰消退时间提前,海冰出现时间延后,开阔水域季节长度大幅增加,与1992年相比增加了72 d。19个栖息地中,巴伦支海是开阔水域面积和季节长度变化贡献最大的海域,增加速度分别为9.71×10³ km²/a和71.69 d/10a。以开阔水域季节长度变化率为依据,将北极熊栖息地划分为稳定、次稳定和不稳定3个等级。总共有3个稳定栖息地,包括分布在相对其他栖息地而言纬度较低的楚科奇海、西哈得孙湾和南哈得孙湾。13个次稳定栖息地,包括拉普捷夫海、喀拉海、东格陵兰、巴芬湾、戴维斯海峡、福克斯湾、布西亚湾、麦克林托克海峡、梅尔维尔子爵海峡、挪威湾、北波弗特、南波弗特和兰开斯特海峡。3个不稳定栖息地,均位于70°N以北,包括北极盆地、巴伦支海和凯恩盆地。稳定区主要位于低纬度,不稳定区全部位于高纬度。该分级结果表明高纬度地区虽然海冰覆盖多,但是年际变化十分显著,不稳定的3个区域内北极熊对海冰变化适应时间更少,年际迁移变化大,对北极熊的生存发展更为不利。     

基于NSIDC海冰产品的FY北极海冰数据集优化

北极海冰对全球气候起着非常重要的调制作用,海冰范围是海冰监测的基本参数。近40年,北极地区持续变暖,北极海冰显著减少,进而引发北极自然环境恶化、北半球极端天气频发、全球海平面上升等一系列环境和气候问题。准确获取北极海冰范围及其演变趋势,确定海冰变化对全球气候系统的响应,是研究和预测全球气候变化趋势的关键之一。HasISST和OISST海冰数据集在海冰监测中应用最为广泛,可为北极地区长时间序列海冰变化研究提供基础数据,但这2套数据集空间分辨率相对较低,应用于北极关键区对中国气候响应研究方面存在很大的局限,为解决这一问题和弥补国内海冰监测微波遥感数据的空白,2011年6月27日,国家卫星气象中心（National Satellite Meteorological Center, NSMC）发布了FY（Fengyun, FY）北极海冰数据集,该数据集利用搭载在FY卫星上的微波成像仪（Microwave Radiation Imager, MWRI）数据,使用Enhance NASA Team算法制作,该算法利用前向辐射传输模型模拟北极地区4种海表类型（海水、新生冰、一年冰和多年冰）在不同大气条件下MWRI辐射亮温,进而得到每种大气条件下0~100%的海冰覆盖度查找表（海冰覆盖度每次增加1%）,通过观测值与模拟值的比对得到海冰覆盖度,由该数据集计算得到的北极海冰范围在大部分区域与实际情况相符。该产品虽已进行通道间匹配误差修正和定位精度偏差订正,但由于其搭载的微波成像仪（Microwave Radiation Imager, MWRI）天线长度有限,造成传感器探测到的地物回波信号相对较弱,难以区分海冰和近岸附近的陆地,影响了该数据集的精度和应用。为解决这一问题,本文基于美国冰雪中心（National Snow and Ice Data Center, NSIDC）发布的海冰产品对FY海冰数据集进行优化,NSIDC产品利用判断矩阵对海岸线附近的像元进行识别,并对误差像元进行不同程度的修正,由NSIDC产品计算得到的北极海冰范围与实际情况更为符合。数据集优化大大提高了FY海冰数据集的精度,研究结果表明,优化后FY海冰数据集与NSIDC产品相关系数高达0.9997,且二者日、月、年平均最大海冰范围偏差仅为3.5%、1.9%、0.9%,且FY海冰数据集优化过程对其较好的空间分异特征无明显影响。该数据集可正确地反映北极海冰范围及其变化情况,且海岸线附近海冰的分布情况更准确,可为北极海冰变化研究提供可靠的基础数据。     

Impacts of SIS and CICE as Sea Ice Components in BCC_CSM on the Simulation of the Arctic Climate

Sea ice is a sensitive indicator of climate change and an important component of climate system models. The Los Alamos Sea Ice Model 5.0(CICE5.0) was introduced to the Beijing Climate Center Climate System Model(BCC_CSM) as a new alternative to the Sea Ice Simulator(SIS). The principal purpose of this paper is to analyze the impacts of these two sea ice components on simulations of basic Arctic sea ice, atmosphere, and ocean states. Two sets of experiments were conducted with the same configurations except for the sea ice component used, i.e., SIS and CICE. The distributions of sea ice concentration and thickness reproduced by the CICE simulations in both March and September were closer to actual observations than those reproduced by SIS simulations, which presented a very thin sea ice cover in September. Changes in sea ice conditions also brought about corresponding modifications to the atmosphere and ocean circulation. CICE simulations showed higher agreement with the reference datasets than did SIS simulations for surface air temperature, sea level pressure, and sea surface temperature in most parts of the Arctic Ocean. More importantly, compared with simulations with SIS, BCC_CSM with CICE revealed stronger Atlantic meridional overturning circulation(AMOC), which is more consistent with actual observations. Thus, CICE shows better performance than SIS in BCC_ CSM. However, both components demonstrate a number of common weaknesses, such as overestimation of the sea ice cover in winter, especially in the Nordic Sea and the Sea of Okhotsk. Additional studies and improvements are necessary to develop these components further.     

Sea ice thickness measurement in spring season in Bothnian Bay using an electromagnetic induction instrument

As an important component of the cryosphere,sea ice is very sensitive to the climate change.The study of the sea ice physics needs accurate sea ice thickness.This paper presents an electromagnetic-induction(EM) technique which can be used to measure the sea ice thickness distribution efficiently,and the successful application in Bothnian Bay.Based on the electromagnetic field theory and the electrical properties of sea ice and seawater,EM technique can detect the distance between the instrument and the ice/water interface accurately,than the sea ice thickness is obtained.Contrastive analysis of the apparent conductivity data obtained by EM and the value of drill-hole at same positions allows a construction of a transformable formula of the apparent conductivity to sea ice thickness.The verification of the sea ice thickness calculated by this formula indicates that EM technique is able to get reliable sea ice thickness with average relative error of only 12%.The statistic of all ice thickness profiles shows that the level ice distribution in Bothnian Bay was 0.4-0.6 m.     

Status of the Recent Declining of Arctic Sea Ice Studies

In the past 30 years, a large-scale change occurred in the Arctic climatic system, which had never been observed before 1980s. At the same time, the Arctic sea ice experienced a special evolution with more and more rapidly dramatic declining. In this circumstance, the Arctic sea ice became a new focus of the Arctic research. The recent advancements about abrupt change of the Arctic sea ice are reviewed in this paper .The previous analyses have demonstrated the accelerated declining trend of Arctic sea ice extent in the past 30 years, based on in-situ and satellite-based observations of atmosphere, as well as the results of global and regional climate simulations. Especially in summer, the rate of decrease for the ice extents was above 10% per decade. In present paper, the evolution characteristics of the arctic sea ice and its possible cause are discussed in three aspects, i.e. the sea ice physical properties, the interaction process of sea ice, ocean and atmosphere and its response and feedback mechanism to global and arctic climate system.     

Solar radiation penetrating through sea ice under very low solar altitude

Based on the optical data for transmitted radiation through sea ice in the Arctic during the late autumn and early winter of 2007,the authors studied the arriving solar radiation,reflected radiation and transmitted radiation under very low solar altitude.Through the atmosphere,the light of the arriving solar radiation at short wavelength was weakened,with the spectral distribution of double peaks centered at 490 nm and 683 nm.The magnitude of the peak at 683 nm even exceeded that at 490 nm under the very low solar radiation condition.The reflection was lower than that in summertime because of the thin thicknesses of ice and snow,allowing higher ratio of heat to enter the sea ice and snow.When higher ratio of solar radiation entered sea ice in late autumn,the new ice freezing would be affected.The spectral reflectivity from snow surface was almost a constant,but the reflection without snow decreased at longer wavelengths.In the transmission spectrum,the light of 490nm was dominant.It indicates that the radiation at longer wavelength was weakened by sea ice.Therefore,under the condition of low solar altitude,the radiation at shorter wavelength was weakened by the atmosphere while the radiation at longer wavelength was weakened by the sea ice.The combined effect of atmosphere and sea ice made the solar radiation under sea ice much weaker.The absorption of sea ice for the longer-wavelength radiation allowed the sea ice to gain more heat to slow down the freezing process.     

The research of Polar sea ice and its role in climate change

As an important part of global climate system, the Polar sea ice is effccting on global climate changes through ocean surface radiation balance, mass balance, energy balance as well as the circulating of sea water temperature and salinity. Sea ice research has a centuries - old history. The many correlative sea ice projects were established through the extensive international cooperation during the period from the primary research of intensity and the boaring capacity of sea ice to the development of sea/ice/air coupled model. Based on these reseamhes, the sea ice variety was combined with the global climate change. All research about sea ice includes： the physical properties and processes of sea ice and its snow cover, the ecosystem of sea ice regions, sea ice and upper snow albedo, mass balance of sea ice regions, sea ice and climate coupled model. The simulation suggests that the both of the area and volume of polar sea ice would be reduced in next century. With the developing of the sea ice research, more scientific issues are mentioned. Such as the interaction between sea ice and the other factors of global climate system, the seasonal and regional distribution of polar sea ice thickness, polar sea ice boundary and area variety trends, the growth and melt as well as their influencing factors, the role of the polynya and the sea/air interactions. We should give the best solutions to all of the issues in future sea ice studying.     

2015—2020年辽东湾海冰冰情时空特征及其影响因素

受冬季强寒潮侵袭,辽东湾会出现大范围结冰现象。为了分析2015—2020年辽东湾海冰冰情的变化规律与影响因素,本文选取Sentinel-1A/B数据开展辽东湾海冰监测。首先,采用巴氏距离选择最优纹理特征组合,再利用最大似然方法实现海冰分类;然后,根据上述海冰分类结果,分析海冰冰情等级、海冰外缘线、海冰面积、海冰类型和海冰结冰概率等冰情特征的变化规律;最后,研究海水深度、海温、气温和风速与海冰冰情的关系。主要结论如下：① 采用不同纹理特征组合方法和本文方法对2020年2月1日Sentinel-1B影像进行实验,结果表明本文方法的总体分类精度和Kappa系数分别为93.16%和0.85,分类精度最高。② 11月末到12月海冰类型以初生冰为主,间有灰冰;1月到2月中上旬以灰冰为主,间有初生冰和白冰;2月下旬到3月上旬的海冰类型以灰冰和初生冰为主。辽东湾内部结冰概率存在差异,北部沿岸结冰概率高于南部,东部结冰概率高于西部。辽东湾海冰冰情受海水深度、海温和气温影响明显,受风速影响较小。     

Polar Sea Ice Identification and Classification Based on HY-2A/SCAT Data

In this paper,a Bayesian sea ice detection algorithm is first used based on the HY-2A/SCAT data,and a backpropagation(BP)neural network is used to classify the Arctic sea ice type.During the implementation of the Bayesian sea ice detection algorithm,linear sea ice model parameters and the backscatter variance suitable for HY-2A/SCAT were proposed.The sea ice extent obtained by the Bayesian sea ice detection algorithm was projected on a 12.5 km grid sea ice map and validated by the Advanced Microwave Scanning Radiometer 2(AMSR2)15%sea ice concentration data.The sea ice extent obtained by the Bayesian sea ice detection al-gorithm was found to be in good agreement with that of the AMSR2 during the ice growth season.Meanwhile,the Bayesian sea ice detection algorithm gave a wider ice edge than the AMSR2 during the ice melting season.For the sea ice type classification,the BP neural network was used to classify the Arctic sea ice type(multi-year and first-year ice)from January to May and October to De-cember in 2014.Comparison results between the HY-2A/SCAT sea ice type and Equal-Area Scalable Earth Grid(EASE-Grid)sea ice age data showed that the HY-2A/SCAT multi-year ice extent variation had the same trend as the EASE-Grid data.Classification errors,defined as the ratio of the mismatched sea ice type points between HY-2A/SCAT and EASE-Grid to the total sea ice points,were less than 12%,and the average classification error was 8.6%for the study period,which indicated that the BP neural network classification was a feasible algorithm for HY-2A/SCAT sea ice type classification.     

Three Decades of Sea-Ice Variability in Jiaozhou Bay Revealed by Landsat Observations

In this study, we used Landsat images and meteorological data to examine the spatiotemporal distribution and variability of sea ice in Jiaozhou Bay(JZB) between 1986 and 2016. The results show that JZB is not always covered by sea ice in winter, but in some extreme cases, sea ice has covered more than one-third of the sea area of the bay. Sea ice in JZB has generally formed between January 1 and February 5, primarily along the coast, and gradually expanding to the central area of the bay. Both meteorological and artificial factors have played important roles in modulating the sea ice distribution. We found sea ice coverage to have been strongly correlated with the accumulated freezing-degree days nine days before the occurrence of sea ice(R2 = 0.767). North-northwest surface winds have dominated the freezing period of sea water in the JZB, and wind speed has exerted a more significant influence on the formation of sea ice when the sea ice coverage has been generally small. Additionally, artificial factors began to affect the expansion of sea ice in JZB since 2007. The construction of the Jiao-Zhou-Bay Bridge(JZBB) is believed to have retarded water flow and reduced the tidal prism, thereby leading to the formation of an ice bridge along the JZBB, which effectively prevents the southward expansion of sea ice.     

Crystals and fabrics analysis of an Arctic thermal growth multi-year ice sample

One of sea ice core samples was taken from Arctic by the First Chinese National Arctic Research Expedition Team in 1999. 20 vertical and 2 horizontal ice sections were cut out of the ice core sample 2.22 m in length, which covered the ice sheet from surface to bottom except losses for during sampling and section cutting. From the observation and analysis of the fabrics and crystals along the depth of the ice core sample, followings were found. Whole ice sheet consists of columnar, refrozen clastic pieces, granular, columnar, refrozen clastic pieces, granular, columnar and refrozen clastic pieces. This indicates that the ice core sample was 3-year old, and the ice sheet surface thawed and the melt water flowed into ice sheet during summer. Hence, the annual energy balance in Arctic can be determined by the ice sheet surface thawing in summer, and bottom growth in winter. The thickness of the ice sheet is kept constantly at a certain position based on the corresponding climate and ocean conditions; A new     

The progress in the study of Arctic pack ice ecology

The sea ice community plays an important role in the Arctic marine ecosystem. Because of the predicted environmental changes in the Arctic environment and specifically related to sea ice, the Arctic pack ice biota has received more attention in recent years using modem ice-breaking research vessels. Studies show that the Arctic pack ice contains a diverse biota and besides ice algae, the bacterial and protozoan biomasses can be high. Surprisingly high primary production values were observed in the pack ice of the central Arctic Ocean. Occasionally biomass maximum were discovered in the interior of the ice floes, a habitat that had been ignored in most Arctic studies. Many scientific questions, which deserve special attention, remained unsolved due to logistic limitations and the sea ice characteristics. Little is know about the pack ice community in the central Arctic Ocean. Almost no data exists from the pack ice zone for the winter season. Concerning the abundance of bacteria and protozoa, more studies are needed to understand the microbial network within the ice and its role in material and energy flows. The response of the sea ice biota to global change will impact the entire Arctic marine ecosystem and a long-term monitoring program is needed. The techniques, that are applied to study the sea ice biota and the sea ice ecology, should be improved.     

Measurements of sea ice thickness and its subice morphology analysis using ice-penetration radar in the Arctic Ocean

1　IntroductionSeaice ,asanimportantcomponentoftheArcticclimatesystem ,hasdrawnsignifi cantscientificinterest.Seaicethicknessanditsmorphologyhavedramaticimpactsono cean atmosphere iceinteractions(Wadhams 1 994;Barryetal.1 993 ;Dickson 1 999;PadhamsandNorman 2 0 0 0 ) ,whichdirectlyaffecttheexchangeprocessandspeedofheatandmassbetweentheoceanandtheatmosphere ,dominatethephysicalmechanicsfea turesofseaice ,andaffecttheseaicemovement&deformationaswellasicefreezing&meltingprocess(Hollandetal.1 99…     

Mechanism of sea ice formation based on comprehensive observation data in Liaodong Bay,China

Sea ice disaster is one of the principal natural hazards that affect some coastal areas of China, and the formation of ice cover in a wave field has important characteristics. However, analysis of the mechanism in which waves affect the thermodynamic process of sea ice is lacking, and the influence of waves is not taken into consideration in numerical models of sea ice, largely because of a lack of simultaneous observations of waves and sea ice. Using observational data of the sea ice cycle in the coastal waters of Liaodong Bay(China), we analyzed the characteristics of hydrology, meteorology, and sea ice thickness during the formation of sea ice, and explored the changes in the interrelationships among heat fluxes, waves, and sea ice under actual sea conditions. The results could provide a decision-making support as a reference to the establishment and improvement of China's early warning system to sea ice disasters, and the protection of ice drilling operations and production platform safety.     

Response of the Dominant Modes of Atmospheric Circulation in the Northern Hemisphere to a Projected Arctic Sea Ice Loss in 2007

This study revisits the Arctic sea ice extent(SIE) for the extended period of 1979-2015 based on satellite measurements and finds that the Arctic SIE experienced three different periods: a moderate sea ice decline period for 1979-1996, an accelerated sea ice decline period from 1997 to 2006, and large interannual variation period after 2007, when Arctic sea ice reached its tipping point reported by Livina and Lenton(2013). To address the response of atmospheric circulation to the lowest sea ice conditions with a large interannual variation, we investigated the dominant modes for large atmospheric circulation responses to the projected 2007 Arctic sea ice loss using an atmospheric general circulation model(ECHAM5). The response was obtained from two 50-yr simulations: one with a repeating seasonal cycle of specified sea ice concentration for the period of 1979-1996 and one with that of sea ice conditions in 2007. The results suggest more occurrences of a negative Arctic Oscillation(AO) response to the 2007 Arctic sea ice conditions, accompanied by an North Atlantic Oscillation(NAO)-type atmospheric circulation response under the largest sea ice loss, and more occurrences of the positive Arctic Dipole(AD) mode under the 2007 sea ice conditions, with an across-Arctic wave train pattern response to the largest sea ice loss in the Arctic. This study offers a new perspective for addressing the response of atmospheric circulation to sea ice changes after the Arctic reached the tipping point in 2007.     

Sea Salt Sodium Record in a Shallow Ice Core from East Antarctica as a Potential Proxy of the Antarctic Sea Ice Extent in Southern Indian Ocean

Antarctic sea ice has experienced an increasing trend in recent decades, especially in the Ross Sea and Indian Ocean sectors. Sea ice variability affects greatly the maritime airmass transport from high latitude to Antarctic continent. Here we present a new ice core record of sea salt sodium(ssNa+) concentration at annual-resolution in the Princess Elizabeth Land spanning from 1990 to 2016, showing that this marker could be used as a potential proxy for reconstructing the sea ice extent(SIE) in the Southern Indian Ocean(SIO) given their significant correlation(R =-0.6, P 0.01) over the past 27 years. The correlation and composite analyses results show that the ssNa~+ at the 202 km inland from Zhongshan Station and the SIE changes in SIO are closely related to the Indian Ocean Dipole(IOD) and Southern Annular Mode(SAM). The northward wind in central SIO occurs during positive IOD and the strengthened westerlies occurs during positive SAM, both of which favor increased sea ice in SIO and lead to the decreased ssNa~+ concentration at the coastal site.     

Seasonal changes in sea ice conditions along the Northeast Passage in 2007 and 2012

Remote sensing data from passive microwave and satellite-based altimeters, associated with the data measured underway, were used to characterize seasonal and spatial changes in sea ice conditions along...     

Arctic multiyear sea ice variability observed from satellites: a review

In comparison with seasonal sea ice(first-year ice,FY ice),multiyear(MY) sea ice is thicker and has more opportunity to survive through the summer melting seasons.Therefore,the variability of wintertime MY ice plays a vital role in modulating the variations in the Arctic sea ice minimum extent during the following summer.As a response,the ice-ocean-atmosphere interactions may be significantly affected by the variations in the MY ice cover.Satellite observations are characterized by their capability to capture the spatiotemporal changes of Arctic sea ice.During the recent decades,many active and passive sensors onboard a variety of satellites(QuikSCAT,ASCAT,SSMIS,ICESat,CryoSat-2,etc.) have been used to monitor the dramatic loss of Arctic MY ice.The main objective of this study is to outline the advances and remaining challenges in monitoring the MY ice changes through the utilization of multiple satellite observations.We summarize the primary satellite data sources that are used to identify MY ice.The methodology to classify MY ice and derive MY ice concentration is reviewed.The interannual variability and trends in the MY ice time series in terms of coverage,thickness,volume,and age composition are evaluated.The potential causes associated with the observed Arctic MY ice loss are outlined,which are primarily related to the export and melting mechanisms.In addition,the causes to the MY ice depletion from the perspective of the oceanic water inflow from Pacific and Atlantic Oceans and the water vapor intrusion,as well as the roles of synoptic weather,are analyzed.The remaining challenges and possible upcoming research subjects in detecting the rapidly changing Arctic MY ice using the combined application of multisource remote sensing techniques are discussed.Moreover,some suggestions for the future application of satellite observations on the investigations of MY ice cover changes are proposed.     

Impact of the El Nino on the Variability of the Antarctic Sea Ice Extent

1　IntroductionManymeteorologistsandoceanographerspaidmuchattentiontothestudyofthemechanismofENSOformanyyears,suchasBjerknes(1 966) ,Wyrtki(1 975) ,McCreary(1 983 ) ,Philander(1 984) ,ZhangandChao(1 993 )andMcCPhaden(1 998)havemadegreatdevelopmentinthestudyofENSO .Especiallyinthe 1 990’s,withtheincreasingofthedatainthedeepocean ,thesomeonearguedthattheENSOepisodehadcloserelation shipwiththeeasterntransportationoftheanomalousseasurfacetemperatureinthewestPacific(LiandMu 1 999;Huang 2…