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1.
Effect of compressive strength on the performance of the NEMO-LIM model in Arctic Sea ice simulation
Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s. The prediction of sea ice is highly important, but accurate simulation of sea ice variations remains highly challenging. For improving model performance, sensitivity experiments were conducted using the coupled ocean and sea ice model (NEMO-LIM), and the simulation results were compared against satellite observations. Moreover, the contribution ratios of dynamic and thermodynamic processes to sea ice variations were analyzed. The results show that the performance of the model in reconstructing the spatial distribution of Arctic sea ice is highly sensitive to ice strength decay constant (Crhg). By reducing the Crhg constant, the sea ice compressive strength increases, leading to improved simulated sea ice states. The contribution of thermodynamic processes to sea ice melting was reduced due to less deformation and fracture of sea ice with increased compressive strength. Meanwhile, dynamic processes constrained more sea ice to the central Arctic Ocean and contributed to the increases in ice concentration, reducing the simulation bias in the central Arctic Ocean in summer. The root mean square error (RMSE) between modeled and the CryoSat-2/SMOS satellite observed ice thickness was reduced in the compressive strength-enhanced model solution. The ice thickness, especially of multiyear thick ice, was also reduced and matched with the satellite observation better in the freezing season. These provide an essential foundation on exploring the response of the marine ecosystem and biogeochemical cycling to sea ice changes.
相似文献2.
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... 相似文献
3.
Arctic sea ice in the polar region provides a cold habitat for microbial community. Arctic sea ice microorganisms are revealed to be of considerable importance in basic research and potential in biotechnological application. This paper investigated the culture condition and extraceIlular hydrolase of 14 strains of different Arctic sea ice bacteria. The results showed that optimal growth temperature of strains is 15 ℃ or 20 ℃. The optimal pH is about 8.0. They hardly grow at acid condition. 3 % NaCl is necessary for better growth. These strains have different abilities in producing amylase, protease, eellulase and lipase. Pseudoalteronomas sp. Bsi429 and Pseudoalteronomas sp. Bsi539 produced both cellulose, protease and lipase. These results provide a basis for further developing and exploiting the cold adapted marine enzyme resources. 相似文献
4.
CryoSat-2卫星海冰区域波形识别及海冰干舷高确定 总被引：1，自引：0，他引：1
利用40%阈值法对CryoSat-2卫星波形数据进行重跟踪,将波形特征参数和海冰浓度相结合,对海冰和Lead(浮冰之间的开阔水域)进行有效识别。利用沿轨前后搜索算法计算海冰干舷高,并引用AWI结果,绘制2011~2013年北冰洋多年冰区域和一年冰区域平均海冰干舷高变化趋势图。比较本文结果与AWI结果的各年同期数据,验证本文结果的可靠性。 相似文献
5.
1 Introduction Itiswellknownthatseaiceinthepolarregionplaysanimportantroleintheglobal climatechangesasapartofclimatesystem(Carleton1989;YuanandMartinson2000, 2001;ChengandBian2002;LiuandMartinson2002;LiuandZhang2004;Gigorand Wallace2002etal).Infact,numerousmodelingstudiessuggestanimportantinfluence throughtheseaicefieldsalone(Grumbine1994,Meehl1990,Rindetal.1995).Inor dertounderstandthevariabilityofArcticandAntarcticseaicealongwiththepossiblecon nectionswithclimaticanomaliesindetail… 相似文献
6.
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… 相似文献
7.
Motoyoshi Ikeda 《极地研究(英文版)》2008,19(2):212-217
The sea ice cover in the Arctic Ocean has been reducing and hit the low record in the summer of 2007. The anomaly was extremely large in the Pacific sector. The sea level height in the Bering Sea vs. the Greenland Sea has been analyzed and compared with the current meter data through the Bering Strait. A recent peak existed as a consequence of atmospheric circulation and is considered to contribute to inflow of the Pacific Water into the Arctic Basin. The timing of the Pacific Water inflow matched with the sea ice reduction in the Pacific sector and suggests a significant increase in heat flux. This component should be included in the model prediction for answering the question when the Arctic sea ice becomes a seasonal ice cover. 相似文献
8.
Xieyu Fan Haibo Bi Yunhe Wang Min Fu Xuan Zhou Xiuli Xu Haijun Huang 《中国海洋大学学报(英文版)》2017,16(6):1061-1071
Sea ice is a quite sensitive indicator in response to regional and global climate changes. Based on monthly mean PanArctic Ice Ocean Modeling and Assimilation System(PIOMAS) sea ice thickness fields, we computed the conductive heat flux(CHF) in the Arctic Ocean in the four winter months(November–February) for a long period of 36 years(1979–2014). The calculated results for each month manifest the increasing extension of the domain with high CHF values since 1979 till 2014. In 2014, regions of roughly 90% of the central Arctic Ocean have been dominated by the CHF values larger than 18 Wm~(-2)(November–December) and 12 Wm~(-2)(January–February), especially significant in the shelf seas around the Arctic Ocean. Moreover, the population distribution frequency(PDF) patterns of the CHF with time show gradually peak shifting toward increased CHF values. The spatiotemporal patterns in terms of the trends in sea ice thickness and other three geophysical parameters, surface air temperature(SAT), sea ice thickness(SIT), and CHF, are well coupled. This suggests that the thinner sea ice cover preconditions for the more oceanic heat loss into atmosphere(as suggested by increased CHF values), which probably contributes to warmer atmosphere which in turn in the long run will cause thinner ice cover. This represents a positive feedback mechanism of which the overall effects would amplify the Arctic climate changes. 相似文献
9.
Status of the Recent Declining of Arctic Sea Ice Studies 总被引：2，自引：0，他引：2
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. 相似文献
10.
A model study is conducted to examine the role of Pacific water in the dramatic retreat of arctic sea ice during summer 2007. The model generally agrees with the observations in showing considerable seasonal and interannual variability of the Pacific water inflow at Bering Strait in response to changes in atmospheric circulation. During summer 2007 anomalously strong southerly winds over the PaCific sector of the Arctic Ocean strengthen the ocean circulation and bring more Pacific water into the Arctic than the recent （2000-2006） average. The simulated summer （3 months ） 2007 mean Pacific water inflow at Bering Strait is 1.2 Sv, which is the highest in the past three decades of the simulation and is 20% higher than the recent average. Particularly, the Pacific water inflow in September 2007 is about 0.5 Sv or 50% above the 2000-2006 average. The strengthened warm Pacific water inflow carries an additional 1.0 x 1020 Joules of heat into the Arctic, enough to melt an additional 0.5 m of ice over the whole Chukchi Sea. In the model the extra summer oceanic heat brought in by the Pacific water mainly stays in the Chukchi and Beaufort region, contributing to the warming of surface waters in that region. The heat is in constant contact with the ice cover in the region in July through September. Thus the Pacific water plays a role in ice melting in the Chukchi and Beaufort region all summer long in 2007, likely contributing to up to O. 5 m per month additional ice melting in some area of that region. 相似文献
11.
The vertical structure of Planetary boundary layer over Arctic floating ice is presented by using about 50 atmospheric profiles and relevant data sounded at an ice station over Arctic Ocean from 22 August to 3 September,2003.It shows that the height of the convective boundary layer in day is greater than that of the stability boundary layer in night.The boundary layer can be described as vertical structures of stability,instability and multipling The interaction between relative warm and wet down draft air from up level and cool air of surface layer is significant,which causes stronger wind shear,temperature and humidity inversion with typical wind shear of 10 m/s/100 m,intensity of temperature inversion of 8 ℃/100 m.While the larger pack ice is broken by such process,new ice free area in the high latitudes of arctic ocean.The interactions between air/ice/water are enhanced.The fact helps to understanding characteristics of atmospheric boundary layer and its effect in Arctic floating ice region. 相似文献
12.
Bacterial diversity in sea ice brine samples which collected from four stations located at the Canada Basin, Arctic Ocean was analyzed by PCR-DGGE. Twenty-three 16S rDNA sequences of bacteria obtained from DGGE bands were cloned and sequenced. Phylogenetic analysis clustered these sequences within γ-proteobacteria, Cytophaga-Flexlbacter-Bacteroides （CFB） group, Firmicutes and Actinobacteria. The phylotype of Pseudoalteromonas in the γ-proteobacteria was predominant and members of the CFB group and γ-proteobacteria were highly abundant in studied sea ice brine samples. 相似文献
13.
本文应用统计方法分析陆雪和海冰与东亚夏季风的关系。分析结果表明:前期海冰和陆雪,对夏季风强度有影响,而与夏季风同时的海冰和陆雪的异常,却与夏季风相关甚小,这是由于大气状况的变化与下垫面的能量储放有关。本文初步探讨北极海冰对东亚夏季风影响的可能途径,认为海冰通过大西洋海温、大西洋副热带高压及青藏高压,由夏季对流层上层的东西热力环流圈和季风环流圈,对东亚夏季风起一定影响。 相似文献
14.
北极海冰范围时空变化及其与海温气温间的数值分析 总被引：1，自引：0，他引：1
本文利用美国国家冰雪中心提供的1989-2014年海冰范围资料,分析了北极海冰范围的年际变化和季节变化规律。分析发现,北极海冰范围呈减少趋势,每年减小
15.
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. 相似文献
16.
Abundance,biomass and composition of the ice algal and phytoplank-ton communities were investigated in the southeastern Laptev Sea in spring 1999.Diatoms dominated the algal communities and pennate diatoms dominated the dia-tom population.12 dominant algal species occurred within sea ice and underlyingwater column,including Fragilariopsis oceanica,F.cylindrus,Nitzschiafrigida,N.promare,Achnanthes taeniata,Nitzschia neofrigida,Naviculapelagica,N.vanhoef fenii,N.septentrionalis,Melosira arctica,Clindrothecaclosterium and Pyrarnimonas sp.The algal abundance of bottom 10 cm sea icevaried between 14.6 and 1562.2×10~4 ceils l~(-1)with an average of 639.0×10~4cells l~(-1),and the algal biomass ranged from 7.89 to 2093.5μg C l~(-1)with an av-erage of 886.9μg C l~(-1),which were generally one order of magnitude higherthan those of sub-bottom ice and two orders of magnitude higher than those ofunderlying surface water.The integrated algal abundance and biomass of lower-most 20 cm ice column were averagely 7.7 and 12.2 times as those of upper 20 mwater column,respectively,suggesting that the ice algae might play an importantrole in maintaining the coastal marine ecosystem before the thawing of sea ice.Icealgae influenced the phytoplankton community of the underlying water column.However,the“seeding”of ice algae for phytoplankton bloom was negligible be-cause of the iow phytoplankton biomass within the underlying water column. 相似文献
17.
Satellite-observed trends in the Arctic sea ice concentration for the period 1979–2016 总被引：1，自引：0，他引：1
Wang Yunhe Bi Haibo Huang Haijun Liu Yanxia Liu Yilin Liang Xi Fu Min Zhang Zehua 《中国海洋湖沼学报》2019,37(1):18-37
Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ). 相似文献
18.
Clara Deal 《极地研究(英文版)》2008,19(2):218-229
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 microzooplankton ： ZS, ZL, ZP） , three nutrients （ nitrate ＋ nitrite, ammonium, silicon ： NO3 , NH4, 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. 相似文献
19.
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 相似文献
20.
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。 相似文献