MODIS海冰数据监测中山站附近海冰的季节性变化

本文利用中分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer,即MODIS)的海冰数据,监测中山站附近区域海冰的季节性(尤其是夏季)的消融与冻结情况及海冰表面温度的变化。文中先对MODIS的海冰数据进行影像分层、数据合成,分时间段计算海冰范围,然后提取海冰表面温度信息,最后对获取的数据进行分析。研究结果表明,中山站附近区域在每年10月至翌年2月中上旬为海冰消融期;2月中下旬至4月为海冰冻结非密封期;5月至9月为海冰冻结密封期。海冰范围2月份最小;海冰表面温度1月份最低,8月份最高。     

北极拉普捷夫海海冰多年变化研究

拉普捷夫海是北冰洋的边缘海和冰源地,对北冰洋的海冰变化有重要影响。通过分析AMSR-E海冰密集度数据以及NECP-DOE的风场、温度场数据,结果表明拉普捷夫海海冰在2002—2011年经历了如下过程：重冰年(2002—2004)—过渡性质年份(2005—2006) —轻冰年(2007、2009—2011),即冰情由重向轻转变。研究结果也表明拉普捷夫海的冰情轻重与融冰期长短有较好的相关性,融冰期持续时间越短,冰情越重。4个参数,包括海冰距平指数、最小海冰覆盖率、积温、风驱动指数描述了拉普捷夫海的海冰多年变化过程。海冰距平指数是时间（3—11月）平均下的海冰覆盖率距平值,定量给出了各年冰情的轻重;最小海冰覆盖率是夏季海冰的极限情况,变化范围在0.45%—48.73%,发生时间为8月底至10月上旬。积温是上一个冬季气温积累对当年冰情的影响,结果表明积温是影响当年冰情轻重的主要因素。2008年的上一个冬季经历了异常低温,造成当年的异常重冰年。风驱动指数给出了风场对海冰覆盖率变化的短期影响,与同时期其他年份相比,2006年4月、2007年9月均出现了异常强北风,一定程度上造成了2006年融冰开始时间延后、2007年夏季最小海冰覆盖率的明显偏大。     

侧边界融化对北极海冰影响的数值模拟

对NCAR CSIM5 海冰模式中海冰侧边界融化参数化方案进行了详细阐述,并利用CSIM5模式模拟了侧边界融化对北极海冰厚度和海冰面积变化的影响,试验结果表明：（1）侧边界融化热力过程会增大海冰厚度和海冰面积的消融,海冰厚度消融最明显的区域分布在西伯利亚海和格陵兰海,海冰面积消融最明显区域分布海冰边缘地区;（2）侧边界融化过程对夏季海冰厚度影响比冬季更为明显,而对冬季海冰面积的影响要比夏季更为明显;（3）侧边界融化方案能更好地模拟出海冰面积的季节性变化;（4）海水表面温度（SST）是影响海冰侧边界融化过程的重要因子,侧边界融化率的大值区分布在SST零度线附近的狭窄区域。     

南极罗斯海2012年夏季海冰特征分析

利用卫星海冰密集度资料和船基海冰走航观测数据分析了2012年12月至2013年3月南极罗斯海海冰密集度、厚度和浮冰尺寸等参数的时空变化特征。12月下旬罗斯海西侧浮冰区南北向宽约1 000 km,沿雪龙船航线平均密集度在5成以上,平均海冰厚度为100 cm,平均冰上积雪厚度为16 cm,高密集度区域主要为尺寸较小的块浮冰(2—20 m)和小浮冰(20—100 m),低密集度区域主要为大尺寸浮冰(500—2 000 m)。1月和2月罗斯海大部分海域无海冰覆盖,3月海冰迅速冻结,下旬即覆盖整个罗斯海。SSMIS和AMSR2两种卫星遥感数据均能较好反映航线上的真实海冰密集度状况,AMSR2产品与观测符合更好。与1978—2012的气候平均值相比,观测区在2012年夏季冰情偏重。本文的分析结果可帮助我们了解罗斯海海冰的时空特征,为中国后续罗斯海科考提供参考。     

南大洋大气氧化亚氮分布特征

在执行中国第21次南极科学考察任务期间,于2004年11月15日至2005年2月2日在南大洋(澳大利亚以南以及中山站和长城站之间环绕南极海域)航线上采集大气氧化亚氮样品,并带回陆地实验室分析。结果显示,大气氧化亚氮浓度由澳大利亚至中山站航段的(309.6±1.6)nL/L上升至环绕南极冰边缘海区航段的(320.0±1.2)nL/L。这种南大洋大气中氧化亚氮浓度随纬度升高而升高的特征,可能与洋流作用,季节性海冰融化、生物作用以及近岸等的影响因素有关。     

夏季北冰洋浮冰-水道热力学特征现场观测研究

中国第3次北极科学考察期间首次开展了浮冰-水道热力平衡的现场观测。观测结果表明,观测期间气温低于0°C,调查区域正从消融期向生长期过渡,至8月23日水道逐渐封冻。之后表面薄冰的反照率为0.46(±0.03),水道内水温垂向梯度逐渐减小,水道内和冰底的水温逐渐下降。至8月底,浮冰底部的生消达到平衡;侧部仍处于融冰期,对应的平均融解潜热通量为19(±6) W/m2;对观测区的海冰而言,至8月下旬,相对于底部和表面的生消,侧部融化对其物质平衡贡献较大。     

SIS海冰模式中两种盐度参数化方案的差异

详细介绍了Sea Ice Simulator(SIS)海冰模式中引进两种盐度参数化方案即等盐度方案和盐度廓线方案对海冰模拟所存在的差异。利用盐度廓线方案导出的表征盐度与海冰温度间关系的方程比等盐度方案多出一项,将该项定义为盐度差异项。盐度差异项对海冰厚度的热力作用表现为:在海冰厚度增长季节(11月到次年5月),盐度差异项通过升高海冰内部温度,抑制海冰增长;在消融的第一阶段(6—8月),盐度差异项通过升高海冰内部温度加快海冰消融;在消融的第二阶段(9—10月),盐度差异项通过降低海冰内部的温度抑制海冰消融。但尺度分析表明,盐度差异项要比方程中对海冰温度作用最大项小1—2个量级,如果采用一级近似,可以略去盐度差异项,因此盐度差异项对与海冰增长和消融影响很小。同时利用GFDL中心研制的冰-洋耦合模式Modular Ocean Model(MOM4),分别采用两种盐度参数化方案模拟北极海冰厚度和海冰密集度的季节性变化,模拟结果也表明两种方案模拟得到的海冰厚度和海冰密集度的季节性变化相差甚小。     

基于多时序遥感数据的中山站附近地区海冰监测及雪龙船航迹特点分析

极地海冰是全球气候系统的重要组成部分,具有一定的季节和年际变化,它对极地科学考察有着重要影响。本文利用MODIS L1B级数据,经监督分类提取冰雪二值图并计算海冰面积,分析2000—2014年中山站附近地区的海冰的季节性和年际变化;结合Landsat影像及雪龙船航迹数据,分析2007—2012年雪龙船到达中山站的航迹特点,为极地科学考察提供参考。研究结果表明,2000—2014年中山站附近地区海冰年际变化规律大体一致,且在每年8月至次年3月有明显的季节性变化规律——海冰面积在9月底10月初达到最大值,在2月中下旬达到最小值;雪龙船到达中山站时间为该地区海冰融化的初期,其航迹特点与海冰分布密切相关。     

东南极中山站附近湖冰与固定冰热力学过程比较

2006年对东南极中山站附近湖冰和固定冰的热力学过程进行了系统观测.基于观测数据比较湖冰和固定冰热力学生消过程;分析湖冰和固定冰温度对气温变化的响应规律;计算不同深度层湖冰和固定冰的垂向热传导通量.结果表明:观测的湖泊和海岸区均在2月底至3月初形成连续冰层;湖冰9月底至10月初达到最大冰厚,早于固定冰1-2个月,湖冰最...     

2000-2016年青海湖湖冰物候特征变化

湖冰物候特征是气候变化的灵敏指示器。基于2000-2016年青海湖边界矢量数据,结合Terra MODIS和Landsat TM/ETM+遥感影像及气象数据,利用RS和GIS技术综合分析青海湖湖冰物候特征变化及其对气候变化的响应。结果表明：① 青海湖开始冻结、完全冻结、开始消融和完全消融的时间分别为12月中旬、1月上旬、3月中下旬和3月下旬至4月上旬,平均封冻期和平均完全封冻期为88 d和77 d,平均湖冰存在期和平均消融期为108 d和10 d。② 近16年间青海湖湖冰物候特征各时间节点变化呈现较大的差异性。湖泊开始冻结日期相对变化较小,完全冻结日期呈先提前后推迟的波动趋势,开始消融日期呈先推迟后提前的波动趋势,完全消融日期在2012-2016年呈明显提前趋势。青海湖封冻期在2000-2005年和2010-2016年呈缩短趋势,但减少速率慢于青藏高原腹地的湖泊。③ 青海湖冻结和消融的空间模式相同,即湖冰形成较早的区域则消融较早,且前者持续时间（18~31 d）整体上大于后者（7~20 d）,二者相差约10 d。④ 冬半年负积温大小是影响青海湖封冻期的关键要素,但风速和降水对青海湖湖冰的形成和消融亦发挥着重要作用。     

Summer fast ice evolution off Zhongshan Station,Antarctica

Based on the field data acquired in the program of fast ice observation off Zhongshan Station,Prydz Bay,East Antarctica during the austral summer 2005/ 2006,physical properties evolution of fast ice during the ice ablation season is ana- lyzed in detail.Results show that the annual maximum ice thickness in 2005 occurred in later November,and then ice started to melt,and the ablation duration was 62 days;sea water under the ice became warmer synchronously;corresponding to the warming sea ice temperature,a"relative cold mid-layer"appeared in sea ice;the fast ice marginal line recoiled back to the shore observably,and the recoil distance was 20.9 km from 18 December 2005 through 14 January 2006.In addition,based on the data of sea ice thickness survey along the investigation course of MV Xuelong on December 18 of 2005,the ice thickness distribution paten in the marginal ice zone have been described:sea ice thickness increased,but the diversity of floe ice thick- ness decreased from open water to fast ice zone distinctly.     

Summer sea ice characteristics of the Chukchi Sea

During August 1999, we investigated sea ice characteristics; its distribution, surface feature, thickness, ice floe movement, and the temperature field around inter-borders of air/ice/seawater in the Chukchi Sea. Thirteen ice cores were drilled at 11 floe stations in the area of 72°24′ 77°18′N, 153°34′ 163°28′W and the ice core structure was observed. From field observation, three melting processes of ice were observed; surface layer melting, surface and bottom layers melting, and all of ice melting. The observation of temperature fields around sea ice floes showed that the bottom melting under the ice floes were important process. As ice floes and open water areas were alternately distributed in summer Arctic Ocean; the water under ice was colder than the open water by 0.4 2.8℃. The sun radiation heated seawater in open sea areas so that the warmer water went to the bottom when the ice floes move to those areas. This causes ice melting to start at the bottom of the ice floes. This process can balance effectively the temperature fluctuating in the sea in summer. From the crystalline structure of sea ice observed from the cores, it was concluded that the ice was composed of ice crystals and brine-ice films. During the sea ice melting, the brine-ice films between ice crystals melted firstly; then the ice crystals were encircled by brine films; the sea ice became the mixture of ice and liquid brine. At the end of melting, the ice crystals would be separated each other, the bond between ice crystals weakens and this leads to the collapse of the ice sheet.     

北冰洋海冰/气候系统及其对全球气候的影响

结合前人对北冰洋海冰、气候系统的研究成果和 1 999年 8月在北冰洋对海冰的现场观测 ,本文综述了海冰分布、厚度的变化 ,海冰表面特征、积雪变化及北冰洋天气、气候特征和分区。讨论了北极海冰与南极海冰的差异。文章认为 ,北冰洋与周围地区气候变化趋势的不一致 ,主要是由于夏季在北冰洋海冰与开阔水域的相间分布、海冰漂移、融化吸热 ,均衡了周围大气、海洋温度的变化。     

南极乔治王岛长城湾沿岸固定冰中有色层生态观察

自1988年11月至1989年3月,对南极乔治王岛的长城湾沿岸水域中的海洋生物和环境因子进行了调查,1988年11月20日在2号站采得的冰芯中部有一层约5cm的棕色层,而1988年11月17日、20日和26日在5号站采得的冰芯样中有二层棕色层。固定冰中叶绿素a浓度范围在2.55～56.8mg/m~3之间,而且大部分含量集中在海冰的中间层中,而不象其它海区如昭和、戴维斯、凯西和麦克默多等站,大部分叶绿素a集中在海冰的底部,造成这种差别的原因、可能是由于海冰的结构和形成过程不同所致。     

东南极普里兹湾1990年1—2月大风过程与气旋和锋面活动分析

本文用澳大利亚墨尔本气象中心,苏联南极青年站地面天气图和NOAA-10,NOAA-11极轨卫星云图确定了东南极普里兹湾及其附近海域1990年1—2月份气旋中心位置;讨论了这些气旋的活动特征。分析了实测大风对应的天气系统,天气形势和卫星云图特征,指出普里兹湾沿海存在气旋、锋面以及锋面云和气旋先后相继的影响。锋面及锋面、气旋先后相继影响与500hPa上的强高压脊天气形势、强风与锋面带中纹理非常不均匀区域有密切关系。     

The diet of high-arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago

Food samples from six high-arctic seabird species were collected during spring and summer seasons between 1982 and 1990 in the Svalbard region. The material came from coastal localities on the island of Spitsbergen and the marginal ice zone in eastern Svalbard waters. Polar cod Boreogadus saida was the most frequently occurring prey in the ice-covered areas. Analysis of otoliths showed that most polar cod were one-or two-year olds. These year classes are known to associate with sea ice. Other ice-associated (sympagic) organisms, such as gammarid amphipods, were not found to be of high importance as prey for seabirds in the study area. However, the sea ice occurring in the area was mainly one year old. Such ice contains a less developed sympagic fauna than multi-year ice. The pelagic amphipod Parathemisto libellula , which is not sympagic but occurs in the water column, was also found to be an important prey in the marginal ice zone, especially for the Briinnich's guillemot Uria lomuia . The smallest of the seabird species studied, the little auk Alle alle , differed from the other five species in its diet, preying mainly upon smaller items such as copepods and young stages of amphipods, euphausiids and decapods. The diet of the various seabird species was in general more diverse in the coastal areas than in the marginal ice zone.     

The distribution and diel movements of Brünnich's Guillemot Uria lomvia in ice covered waters in the Barents Sea, February/March 1987

The distribution of Brünnich's Guillemot in ice covered waters and near the marginal ice zone in the southern part of the Barents Sea was mapped from ship and helicopter in February/March 1987. High densities of Brünnich's Guillemot (up to 1,300 ind./km²) were found in ice leads. The density of birds was especially high over shallow banks where the sea depth was 40-80 m.
A diel movement was also recorded. In the evening the birds left the leads and flew south. Next morning they returned to feed in the open leads. How far they migrated is uncertain, but possibly they flew down to the open sea or to leads close to the marginal ice zone. The migration may have been a means of avoiding to become trapped if leads closed after dark.     

A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice.Here pelagic and sea ice algal ecosystems coexist and interact with each other.Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications. This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea.The biological model includes both pelagic and sea ice algal habitats with 10 compartments:three phytoplankton(pelagic diatom,flagellates and ice algae:D,F,and Ai),three zooplankton(copepods,large zooplankton,and micro-zooplankton :ZS,ZL,ZP),three nutrients(nitrate+nitrite,ammonium,silicon: NO_3,NH_4,Si) and detritus(Det).The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model.The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model.Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.