一个北极区域冰海耦合模式的设置与应用

介绍了一个北极区域冰-海耦合数值模式的设置与应用。海洋模式基于MIT海洋环流数值模式,海冰动力学过程由Hibler的粘-塑模型发展而来。海冰的热力过程基于Winton提出的三层热力学模型。给出了耦合模式的基本框架,重点介绍了区域冰-海耦合系统中较为重要的程序包,如正交网格生成技术,中尺度涡的参数化,冰-海耦合及开边界处理等。以NCEP再分析资料为大气强迫场,模拟研究了北极夏季海冰范围异常的变化特征(1992—2007),模拟得到的海冰面积变化趋势与SSM/I观测资料进行了对比,两者相关系数达到0.88,模式基本反映了海冰的年际变化特征。以2007年为例,对比分析了9月份海冰密集度分布特征,模式结果得到的海冰范围略大于观测,但基本反映了2007年夏季海冰范围的衰减形态。     

2010年夏季北极海冰数值预报试验

为保障我国第四次北极科学考察的顺利开展,于2010年6～8月开展了北极海冰预报预测服务。预报试验基于MITgcm （麻省理工学院通用环流模式）,以NCEP GFS（美国国家环境预测中心全球预报系统）资料为大气强迫,初始化分别使用美国冰雪中心SSM/I（专用微波成像仪）或德国不莱梅大学AMSR-E（地球观测系统先进微波扫描辐射计）北极海冰密集度卫星资料。对2010年6～8月预报结果的初步评估表明,预报结果同卫星观测资料比较一致。在发生快速海冰变化的太平洋扇区,预报结果优于惯性预报,表明模式具有较好的局地海冰数值预报能力。     

海冰流变学方案对比模拟试验

利用美国麻省理工学院开发的数值模式MITgcm设计了区域冰·洋耦合数值模拟试验,开展了海冰动力学过程中两种流变学方案(黏性-塑性流变学和弹性-黏性-塑性流变学)的对比研究.结果表明,两种方案模拟的海冰内部应力张量分量σ<,11>和σ<,22>总体分布形式相近.冬季,大值区主要位于加拿大北极群岛和格陵兰岛北侧以及格陵兰岛...     

中国第二次北极科学考察海冰物理数据的解释

2003年7-9月间,为了探讨北冰洋海冰变化同气候的关系,中国第二次北极科学考察对海冰物理及其相关的物理海洋、大气边界层进行系列合作观测。观测的冰形态、海洋和气象要素将用于确定调查期间大气海冰海洋之间的热力和动力交换。本次考察获得的冰物理性质方面的原始观测数据将在中国南北极考察网公布。为了方便各方人员使用这些数据,本文给出这套资料的描述和解释。     

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。     

北极加拿大海盆2003年和2008年上层海洋热含量的差异分析

主要利用2003年和2008年两次夏季北极科学考察的CTD数据处理了加拿大海盆上层海洋的热含量(这里上层海洋指的是200m以上的海洋),定量分析了热含量随深度的变化,并比较分析了这两年在夏季海冰融化期间热含量的垂向差异变化,以及影响热含量变化的因素,给出了上层海洋热含量在加拿大海盆的空间分布。2008年与2003年相比最显著的变化是在加拿大海盆开阔水域的增加,这将导致太阳辐射能进入海洋中的能量增加,同时海冰的大量融化带来了大量淡水,这些变化改变了上层海洋的温盐性质。海冰大量融化主要产生两个效应：一是上层海洋的普遍增暖,二是太平洋入流水体的下移。文中还分析了近年来在加拿大海盆中变化显著的次表层暖水现象,由于次表层暖水蕴含着不小的热含量,其在上层海洋热量平衡中的作用不容忽视。     

Ice-rafted detritus events in the Arctic during the last glacial interval, and the timing of the Innuitian and Laurentide ice sheet calving events

Ice-rafted detritus (IRD) layers in the Arctic Ocean not only indicate the source of this detrital sediment, but give insights into the ice drift and ice sheet history. Detrital sand-sized Fe oxide mineral grains that are matched to precise sources using the microprobe chemical fingerprint of each grain, along with elevated coarse IRD abundance and radiocarbon ages, are used to define IRD peaks from the Innuitian and Arctic portions of the Laurentide ice sheets. Because grains from these two areas can be entrained by sea ice from the shelves just offshore of the calving areas, peaks in these grains must be correlated to coarse IRD to identify iceberg calving events, and to distinguish them from sea-ice rafting. The sequence of IRD peaks deposited by icebergs from these two ice sheets indicate that both ice sheets calved bergs at accelerated numbers, six or seven times, from 11 to 36 Kya. The relatively short times between most of these IRD events suggest that the ice sheets did not completely collapse with each IRD event, except the last event. Although there is some indication that one ice sheet may have begun calving bergs before the other, the resolution of the Arctic cores does not allow definitive determination of this. This emphasizes the need for higher resolution cores from the central Arctic, as well as from near the terminus of large Pleistocene ice sheets. Sea-ice rafting occurs throughout the last glacial stage, even during some glacial IRD events, as indicated by Fe grains from non-glacial sources.     

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.     

Climate states and variability of Arctic ice and water dynamics during 1946–1997

Recently observed changes in the Arctic have highlighted the need for a better understanding of Arctic dynamics. This research addresses that need and is also motivated by the recent finding of two regimes of Arctic ice - ocean wind-driven circulation. In this paper, we demonstrate that during 1946-1997 the Arctic environmental parameters have oscillated with a period of 10-15 years. Our results reveal significant differences among atmosphere, ice, and ocean processes during the anticyclonic and cyclonic regimes in the Arctic Ocean and its marginal seas. The oscillating behaviour of the Arctic Ocean we call the Arctic Ocean Oscillation (AOO). Based on existing data and results of numerical experiments, we conclude that during the anticyclonic circulation regime the prevailing processes lead to increases in atmospheric pressure, in ice concentration and ice thickness, river runoff, and surface water salinity - as well as to decreases in air temperature, wind speed, number of storms, precipitation, permafrost temperatures, coastal sea level, and surface water temperature. During the cyclonic circulation regime the prevailing processes lead to increased air and water temperatures, wind speed, number of storms,open water periods, and to decreases in ice thickness and ice concentration, river runoff, atmospheric pressure, and water salinity. The two-climate regime theory may help answer questions related to observed decadal variability of the Arctic Ocean and to reconcile the different conclusions among scientists who have analysed Arctic data obtained during different climate states.     

北冰洋浮冰和开阔海面上的能量平衡特征

利用中国首次北极考察队于 1 999年 8月 1 9日～ 2 4日在北冰洋浮冰区获得的大气近地层垂直廓线和辐射等资料 ,依据相似理论方法 ,对比分析了北冰洋无冰海面和冰面上热平衡参数的变化特征。结果表明 ,海面与大气和冰面与大气之间相互作用的边界层物理过程差异十分明显。冰面吸收的净辐射仅为海面的 6%左右 ,主要消耗于感热输送和冰面融化过程 ,不足部分由水汽在冰面上凝结释放的潜热和冰中的热通量来补充。海面吸收的净辐射主要消耗于潜热输送过程 ,占净辐射的 50 % ,其余热量传向水体深层和用于感热输送 ,分别占净辐射的 2 6%和 2 4 %。由此可见 ,在北冰洋夏季 ,无冰海面有大量的水汽向大气输送 ,这对研究北冰洋地区大气边界层的季节变化过程是至关重要的     

A coupled multi-category sea ice model and POM for Baffin Bay and the Labrador Sea

An overview of the seasonal variation of sea-ice cover in Baffin Bay and the Labrador Sea is given.A coupled ice-ocean model,CECOM,has been developed to study the seasonal variation and associated ice-ocean processes.The sea-ice component of the model is a multi-category ice model in which mean concentration and thickness are expressed in terms of a thickness distribution function.Ten categories of ice thickness are specified in the model.Sea ice is coupled dynamically and thermo-dynamically to the Princeton Ocean Model.Selected results from the model including the seasonal variation of sea ice in Baffin Bay,the North Water polynya and ice growth and melt over the Labrador Shelf are presented.     

海冰在海气交换中的作用及其与海雾的关系

本文用了 1 999年夏季中国首次北极科学考察队对海冰、大气和海洋进行的同步和准同步的综合立体观测所获取的资料 ,研究海冰在海 气相互作用中扮演的角色。发现海冰的种类、分布、冰厚等变化对海气热交换都有重要影响。在浮冰区海洋以潜热的形式向大气输送热量 ,潜热通量与浮冰密集度的大小密切有关 ,浮冰越少潜热通量越大 ,潜热通量约为2 1～ 2 3 .6W /m2 ,潜热通量大于感热通量 ;在冰盖和大浮冰块上 ,大气以感热的形式向冰雪面上输送热量。新生的浮冰区或冰间湖是海气热交换最激烈的地方 ,是气候最敏感的区域 ,是北冰洋蒸汽雾生成的重要条件。用层结大气整体动力学输送法 ,计算了一次大范围的蒸汽雾过程的海气热交换 ,海洋向大气输送的热量总功率约为 1 4 8亿千瓦 ,相当于中国发电能力的 69倍 ,相当于大西洋向北冰洋输送热量平均功率的 1 / 2 0。北冰洋的夏季能够形成各种类型的海雾 :辐射雾、蒸汽雾和平流雾 ,其重要原因就是因为海冰的存在 ,使下垫面的性质复杂化 ,海气交换复杂化。     

Coordinated changes of sea ice over the Beaufort and Chukchi seas: regional and seasonal perspectives

One outstanding feature of the recent Arctic climate is the contrast of the changes of sea ice concentration and thickness between the Beaufort Sea and the Chukchi Sea. Since the Arctic Oscillation (AO) plays a critical role in driving Arctic sea ice changes and the Beaufort and Chukchi seas have been hypothesized as a region in which sea ice anomalies originate, we employed a coupled sea ice-ocean model and carried out simulations forced by the AO signal to examine sea ice changes in these regions, focusing on seasonality. With the AO phase transition from negative to positive, anticyclonic windstress weakens broadly in both winter and summer; however, the surface air temperature response shows remarkable seasonal dependence. Positive temperature anomalies spread over the entire domain in winter, while negative anomalies occur in the shelf seas in summer, although positive anomalies remain in the deep-water portion. The simulated sea ice concentration resembles the observed concentration. The strong seasonality of sea ice concentration changes suggests that accumulation of sea ice concentration in the Beaufort Sea and reduction in the Chukchi Sea are mainly produced in summer. Changes of ice thickness are robust through the seasonal cycle. Generally, sea ice dynamics play a critical role in creating the anomalous sea ice pattern and sea ice thermodynamics partially compensate the dynamically-driven changes. However, considerable seasonal differences occur.     

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     

2010年夏季北极海冰反照率的观测研究

雪和海冰作为北极地区反照率最高的地表类型,可以将大部分入射辐射能量反射回天空,其表面反照率的变化对整个地表-大气辐射平衡系统和全球气候变化都会有重要影响。在2010年中国第4次北极科学考察期间用ASD光谱仪对北极太平洋扇区不同类型的海冰表面反照率进行了现场测量,观测时段为7月27日至8月23日,地理范围在72°18′-87°20′N和152°34′-178°22′W之间。观测结果表明积雪覆盖海冰的反照率最高,干雪覆盖时均值达到0.82,融化的湿雪覆盖时反照率会有一定程度地降低。夏季北极地区存在大量融池,融池海冰按颜色划分为白冰,蓝冰和灰冰,白冰的平均反照率为0.54,蓝冰的为0.31,灰冰的只有0.20,融池水的反照率只有0.16。融池是北极夏季反照率变化的重要原因。     

可服务于北极航道的海冰与气象预报信息综合分析

全球气候变暖和北极海冰快速减少背景下,北极航道正在开通,提高海冰和气象预报能力是北极地区船只航行的重要保障。通过获取不同国家的北极高纬共享信息(包括观测数据、预报产品和历史分析资料),分析国际北极地区海冰和气象预报信息特点及存在的问题,能够为我国北极观测预报的常态化、业务化发展提供参考。通过对7个环北极国家、3个非北极国家以及3个信息发布平台共23家机构海冰和气象预报信息的对比,发现近年来各国北极预报水平提升,合作交流扩大,但是仍存在一些问题,如观测数据没有充分应用于预报、北极中央区的预报能力偏弱、预报信息共享度不够、信息应用时需要加以选择、仍需提升信息发布技术。通过上述分析,建议我国持续增加北极科考、国际合作、冰区安全航行预报保障技术研究等的投入,以系统提升我国的极地预报能力,为我国北极科考和极地航运事业提供更加及时有效的预报保障。     

A hindcast simulation of Arctic and Antarctic sea ice variability, 1955–2001

A hindcast simulation of the Arctic and Antarctic sea ice variability during 1955-2001 has been performed with a global, coarse resolution ice-ocean model driven by the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis daily surface air temperatures and winds. Both the mean state and variability of the ice packs over the satellite observing period are reasonably well reproduced by the model. Over the 47-year period, the simulated ice area (defined as the total ice-covered oceanic area) in each hemisphere experiences large decadal variability together with a decreasing trend of Ø1% per decade. In the Southern Hemisphere, this trend is mostly caused by an abrupt retreat of the ice cover during the second half of the 1970s and the beginning of the 1980s. The modelled ice volume also exhibits pronounced decadal variability, especially in the Northern Hemisphere. Besides these fluctuations, we detected a downward trend in Arctic ice volume of 1.8% per decade and an upward trend in Antarctic ice volume of 1.5% per decade. However, caution must be exercised when interpreting these trends because of the shortness of the simulation and the strong decadal variations. Furthermore, sensitivity experiments have revealed that the trend in Antarctic ice volume is model-dependent.     

Experiment of near surface layer parameters in ice camp over Arctic Ocean

Estimates of near surface layer parameters over 78°N drifting ice in ice camp over the Arctic ocean are made using bulk transfer methods with the data from the experiments operated by the Chinese Arctic Scientific Expedition in August 22-September 3,2003.The results show that the net radiation received by the snow surface is only 3.6 W/m2,among which the main part transported into atmosphere in term of sensible heat and latent heat,which account for 52% and 31% respectively,and less part being transported to deep ice in the conductive process.The bulk transfer coefficient of momentum is about 1.16×10-3 in the near neutral layer,which is a little smaller than that obtained over 75°N drifting ice.However,to compare with the results observed over 75°N drifting ice over the Arctic Ocean in 1999,it can be found that the thermodynamic and momentum of interactions between sea and air are significant different with latitudes,concentration and the scale of sea ice.It is very important on considering the effect of sea-air-ice interaction over the Arctic Ocean when studying climate modeling.     

Role of sea ice in air-sea exchange and its relation to sea fog

Synchronous or quasi-synchronous stereoscopic sea-ice-air comprehensive observation was conducted during the First China Arctic Expedition in summer of 1999. Based on these data, the role of sea ice in sea-air exchange was studied. The study shows that the kinds, distribution and thickness of sea ice and their variation significantly influence the air-sea heat exchange. In floating ice area, the heat momentum transferred from ocean to atmosphere is in form of latent heat; latent heat flux is closely related to floating ice concentration; if floating ice is less, the heat flux would be larger. Latent heat flux is about 21 23 6 W·m -2, which is greater than sensible heat flux. On ice field or giant floating ice, heat momentum transferred from atmosphere to sea ice or snow surface is in form of sensible heat. In the floating ice area or polynya, sea-air exchange is the most active, and also the most sensible for climate. Also this area is the most important condition for the creation of Arctic vapor fog. The heat exchange of a large-scale vapor fog process of about 500000 km 2 on Aug. 21 22,1999 was calculated; the heat momentum transferred from ocean to air was about 14 8×10 9 kW. There are various kinds of sea fog, radiation fog, vapor fog and advection fog, forming in the Arctic Ocean in summer. One important cause is the existence of sea ice and its resultant complexity of both underlying surface and sea-air exchange.     

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 modern 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.