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1.
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
2.
利用NSIDC公布的ICESat运行期间的19个任务期的观测数据, 采用重复轨迹分析方法估计近年来南极冰盖高程的时空变化。结果表明,南极大陆冰盖整体上呈现消融趋势,基于不同的GIA模型和ICESat激光测高数据的南极大陆冰盖高程变化的趋势约为 -1.17~-1 cm/a。 相似文献
3.
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
4.
利用CryoSat-2卫星测高数据反演波弗特海的海冰厚度，并利用2010~2013年10月份仰视声呐(ULS)和2011年冰桥计划（IceBridge）数据对结果进行精度评估。结果表明，测高反演的海冰吃水深度与ULS吃水深度差值的最大值和标准差分别为14 cm和4 cm；测高反演的海冰厚度与冰桥计划海冰厚度差值的平均值和标准差分别为2.7 cm和65.7 cm，优于Laxon(2013)研究结果（分别优化2.1 cm和6.6 cm）。在此基础上，研究2011~2017年波弗特海夏冬两季的海冰厚度变化，发现二者具有类似的分布特征，且冬季3月海冰覆盖范围更广，厚度更大；进一步分析2011~2017年3月份冬季海冰厚度年际变化，发现其呈整体下降趋势，且2012年最小，2014年最大。 相似文献
5.
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。 相似文献
6.
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
7.
以山西省吕梁市水峪贯地区为研究区域,基于大比例尺地形图对ICESat/GLA14数据的垂直精度进行了分析。首先,对ICESat/GLA14数据下载和处理,以1:5万地形图为基础数据,生成DEM,提取地形因子;然后,提取ICESat/GLA14数据对应的高程值、坡度、坡向、起伏度等信息;最后,对ICESat/GLA14数据与地形图数据的高程差以及高程差随这些分类后的影响因子的变化规律进行了统计分析、研究结果表明:ICESat/GLA14数据在水峪贯地区平均误差为-5.66m,绝对误差均值为21.92m,标准偏差为27.40m,均方根误差为27.98m;ICESat/GLA14数据的垂直精度随坡度和地形起伏度的增加而降低,受坡向因子影响不大,平均误差在NS轴左边为负值,NS轴右边为正值。 相似文献
8.
鉴于欧拉矢量参数在局部区域适应性较差,提出一种基于Elman神经网络的速度场逼近方法。首先利用已有欧拉矢量参数估计站点速度,将剩余残差作为Elman神经网络拟合量进行逼近;然后将Elman神经网络估计结果与欧拉矢量计算速度相叠加,获得区域速度场模型。利用山东区域速度场数据进行验证,结果表明,该方法在一定程度上能够削弱系统误差影响,提高计算精度。 相似文献
9.
采用由EDC提供的2015-01-01～2015-12-31的SLR标准点观测数据进行GLONASS卫星最终轨道（CODE提供）检核,分别按照卫星PRN号和不同测站对检核结果进行统计分析。结果表明,不同卫星的检核效果参差不齐,跟卫星的服役年限有关,较新的卫星检核结果较好,第一轨道面的卫星检核结果最好;检核结果中存在一定的系统误差,且大部分的激光测距比最终轨道反算的站星距要短;利用SLR检核2015年全年GLONASS轨道精度总体优于3.3 cm,激光观测精度总体优于1.2 cm。 相似文献
10.
目前,ICESat/GLAS是大尺度SRTM DEM精度评价的主要数据源。然而,现有的精度评价方法均忽略了2组数据的有效配准。为此,本文分析了数据配准前、后SRTM DEM整体精度差异,以及不同地形因子和土地利用类型对SRTM DEM影响程度。在此基础上,充分考虑SRTM DEM精度影响因素,分别借助多元线性回归（MLR）、后向传播神经网络（BPNN）、广义回归神经网络（GRNN）以及随机森林（RF）对SRTM DEM修正。结果分析表明：配准前,ICESat/GLAS与SRTM DEM沿x、y方向的平均水平位移分别为-17.588 m、-29.343 m,高程方向系统偏差为-2.107 m;配准后,SRTM DEM的系统误差基本消除,而且中误差降低了14.4%。配准前,坡向与SRTM DEM误差呈正弦函数关系,配准后这种关系基本消失。SRTM DEM误差均随地形起伏度、坡度、高程的增加呈增大趋势; 6种土地利用类型中,SRTM DEM在林地误差最大,未利用土地误差最小。对配准后SRTM DEM修正表明,RF效果最优,其中误差分别比MLR、BPNN、GRNN降低了3.1%、2.7%、11.3%。 相似文献
11.
Bi Haibo Liang Yu Wang Yunhe Liang Xi Zhang Zehua Du Tingqin Yu Qinglong Huang Jue Kong Mei Huang Haijun 《中国海洋湖沼学报》2020,38(4):962-984
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. 相似文献
12.
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
13.
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
14.
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. 相似文献
15.
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16.
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. 相似文献
17.
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