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1.
基于卫星高度计的北极海冰厚度变化研究   总被引:5,自引:3,他引:2  
A modified algorithm taking into account the first year(FY) and multiyear(MY) ice densities is used to derive a sea ice thickness from freeboard measurements acquired by satellite altimetry ICESat(2003–2008). Estimates agree with various independent in situ measurements within 0.21 m. Both the fall and winter campaigns see a dramatic extent retreat of thicker MY ice that survives at least one summer melting season. There were strong seasonal and interannual variabilities with regard to the mean thickness. Seasonal increases of 0.53 m for FY the ice and 0.29 m for the MY ice between the autumn and the winter ICESat campaigns, roughly 4–5 month separation, were found. Interannually, the significant MY ice thickness declines over the consecutive four ICESat winter campaigns(2005–2008) leads to a pronounced thickness drop of 0.8 m in MY sea ice zones. No clear trend was identified from the averaged thickness of thinner, FY ice that emerges in autumn and winter and melts in summer. Uncertainty estimates for our calculated thickness, caused by the standard deviations of multiple input parameters including freeboard, ice density, snow density, snow depth, show large errors more than 0.5 m in thicker MY ice zones and relatively small standard deviations under 0.5 m elsewhere. Moreover, a sensitivity analysis is implemented to determine the separate impact on the thickness estimate in the dependence of an individual input variable as mentioned above. The results show systematic bias of the estimated ice thickness appears to be mainly caused by the variations of freeboard as well as the ice density whereas the snow density and depth brings about relatively insignificant errors.  相似文献   

2.
基于2017年4月、2018年4月和2019年4月的CryoSat-2 L1B数据,比较分析了UCL13、DTU10、DTU13、DTU15和DTU18 5种不同平均海表面高度(MSS)模型及其反演的北极海冰干舷的多时空尺度差异。以UCL13为基准,对比分析不同MSS模型的差异和所反演的海冰干舷的差异,实验结果表明,不同MSS模型之间的平均绝对偏差范围为0.19~0.26 m,标准差范围为0.55~0.57 m,其中DTU18与UCL13的差异最小。以UCL13为基准,其他4种MSS模型反演的海冰干舷的平均绝对偏差为0.50~0.79 cm,标准差范围为1.17~1.74 cm。通过与冰桥计划(Operation IceBridge,OIB)机载数据相比,5种MSS模型反演的海冰干舷的相关系数范围为0.70~0.71,均方根误差范围为7.7~7.8 cm。故不同MSS模型之间的偏差对整个北极地区的海冰干舷反演的影响较小,偏差以相同的方式影响冰间水道和浮冰高度测量,因此相互抵消,但在冰间水道分布稀疏的区域,如加拿大群岛北部和拉普捷夫海区域,不同MSS模型反演的海冰干舷差异较大。  相似文献   

3.
The general properties of sea ice and overlying snow in the southern Sea of Okhotsk were examined during early February of 2003 to 2005 with the P/V “Soya”. Thin section analysis of crystal structure revealed that frazil ice (48% of total core length) was more prevalent than columnar ice (39%) and that stratigraphic layering was prominent with a mean layer thickness of 12 cm, indicating that dynamic processes are essential to ice growth. The mean thickness of ice blocks and visual observations suggest that ridging dominates the deformation process above thicknesses of 30 to 40 cm. As for snow, it was found that faceted crystals and depth hoar are dominant (78%), as which is also common in the Antarctic sea ice, and is indicative of the strong vertical temperature gradients within the snow. Stable isotope measurements (δ18O) indicate that snow ice occupies 9% of total core length and that the mass fraction of meteoric ice accounts for 1 to 2% of total ice volume, which is lower than the Antarctic sea ice. Associated with this, the effective fractionation coefficient during the freezing of seawater was also derived. Snow ice was characterized by lower density, higher salinity, and nearly twice the gas content of ice of seawater origin. In addition, it is shown that the surface brine volume fraction and freeboard are well correlated with ice thickness, indicating some promise for remote sensing approaches to the estimation of ice thickness.  相似文献   

4.
基于CryoSat-2卫星测高数据的北极海冰体积估算方法   总被引:1,自引:1,他引:0  
近30年来,北极海冰正发生着剧烈的变化。海冰体积是量化海冰变化的重要指标之一。本文以2015年CryoSat-2卫星测高数据和OSI SAF海冰类型产品为基础。提取了浮冰出水高度、积雪深度、海冰密集度、海冰类型等属性信息,通过数据内插、投影变换、栅格转换、空间重采样等工作将海冰属性信息统一为25 km×25 km分辨率的栅格数据集。根据流体静力学平衡原理,逐个估算栅格像元对应的海冰厚度值,将其与对应的海冰面积相乘,估算了北极海冰密集度大于75%海域的海冰体积,并分析了海冰厚度和体积的月变化和季节变化特征。用NASA IceBridge海冰厚度产品对反演的海冰厚度进行验证。结果表明二者相关系数为0.72,有较高的一致性。北极海冰平均厚度春季最大,夏季最小,分别约为2.99 m和1.77 m,最厚的海冰集中在格陵兰沿岸北部和埃尔斯米尔半岛以北海域。多年冰平均厚度大于一年冰。冬季海冰体积最大,约为23.30×103 km3,经过夏季的融化,减少了近70%。一年冰体积季节波动较大,而多年冰体积相对稳定,季节变化不明显。  相似文献   

5.
The physical structures of snow and sea ice in the Arctic section of 150°-180°W were observed on the basis of snow-pit, ice-core, and drill-hole measurements from late July to late August 2010. Almost all the investigated floes were first-year ice, except for one located north of Alaska, which was probably multi-year ice transported from north of the Canadian Arctic Archipelago during early summer. The snow covers over all the investigated floes were in the melting phase, with temperatures approaching 0℃ and densities of 295-398 kg/m3 . The snow covers can be divided into two to five layers of different textures, with most cases having a top layer of fresh snow, a round-grain layer in the middle, and slush and/or thin icing layers at the bottom. The first-year sea ice contained about 7%-17% granular ice at the top. There was no granular ice in the lower layers. The interior melting and desalination of sea ice introduced strong stratifications of temperature, salinity, density, and gas and brine volume fractions. The sea ice temperature exhibited linear cooling with depth, while the salinity and the density increased linearly with normalized depth from 0.2 to 0.9 and from 0 to 0.65, respectively. The top layer, especially the freeboard layer, had the lowest salinity and density, and consequently the largest gas content and the smallest brine content. Both the salinity and density in the ice basal layer were highly scattered due to large differences in ice porosity among the samples. The bulk average sea ice temperature, salinity, density, and gas and brine volume fractions were-0.8℃, 1.8, 837 kg/m3 , 9.3% and 10.4%, respectively. The snow cover, sea ice bottom, and sea ice interior show evidences of melting during mid-August in the investigated floe located at about 87°N, 175°W.  相似文献   

6.
A high resolution one-dimensional thermodynamic snow and ice(HIGHTSI) model was used to model the annual cycle of landfast ice mass and heat balance near Zhongshan Station, East Antarctica. The model was forced and initialized by meteorological and sea ice in situ observations from April 2015 to April 2016. HIGHTSI produced a reasonable snow and ice evolution in the validation experiments, with a negligible mean ice thickness bias of(0.003±0.06) m compared to in situ observations. To further examine the impact of different snow conditions on annual evolution of first-year ice(FYI), four sensitivity experiments with different precipitation schemes(0, half, normal, and double) were performed. The results showed that compared to the snow-free case,the insulation effect of snow cover decreased bottom freezing in the winter, leading to 15%–26% reduction of maximum ice thickness. Thick snow cover caused negative freeboard and flooding, and then snow ice formation,which contributed 12%–49% to the maximum ice thickness. In early summer, snow cover delayed the onset of ice melting for about one month, while the melting of snow cover led to the formation of superimposed ice,accounting for 5%–10% of the ice thickness. Internal ice melting was a significant contributor in summer whether snow cover existed or not, accounting for 35%–56% of the total summer ice loss. The multi-year ice(MYI)simulations suggested that when snow-covered ice persisted from FYI to the 10 th MYI, winter congelation ice percentage decreased from 80% to 44%(snow ice and superimposed ice increased), while the contribution of internal ice melting in the summer decreased from 45% to 5%(bottom ice melting dominated).  相似文献   

7.
Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition(CHINARE) buoy data.Two polar hydrometeorological drifters,known as Zeno? ice stations,were deployed during CHINARE 2003.A new type of high-resolution Snow and Ice Mass Balance Arrays,known as SIMBA buoys,were deployed during CHINARE 2014.Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain.A simple approach was applied to estimate the average snow thickness on the basis of Zeno~ temperature data.Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys.A one-dimensional snow and ice thermodynamic model(HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories.The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts(ECMWF).The Zeno~ buoys drifted in a confined area during 2003–2004.The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno~ buoy data.The SIMBA buoys drifted from 81.1°N,157.4°W to 73.5°N,134.9°W in 15 months during2014–2015.The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of2.45 m before the onset of snow melt in May 2015;the last observation was approximately 1 m in late November2015.The ice thickness based on HIGHTSI agreed with SIMBA measurements,in particular when the seasonal variation of oceanic heat flux was taken into account,but the modelled snow thickness differed from the observed one.Sea ice thickness derived from SIMBA data was reasonably good in cold conditions,but challenges remain in both snow and ice thickness in summer.  相似文献   

8.
A comprehensive analysis of sea ice and its snow cover during the summer in the Arctic Pacific sector was conducted using the observations recorded during the 7th Chinese National Arctic Research Expedition(CHIANRE-2016) and the satellite-derived parameters of the melt pond fraction(MPF) and snow grain size(SGS)from MODIS data. The results show that there were many low-concentration ice areas in the south of 78°N, while the ice concentration and thickness increased significantly with the latitude above the north of 78°N during CHIANRE-2016. The average MPF presented a trend of increasing in June and then decreasing in early September for 2016. The average snow depth on sea ice increased with latitude in the Arctic Pacific sector. We found a widely developed depth hoar layer in the snow stratigraphic profiles. The average SGS generally increased from June to early August and then decreased from August to September in 2016, and two valley values appeared during this period due to snowfall incidents.  相似文献   

9.
An attempt has been made to derive sea ice freeboard from Ka-band Altimeter (SARAL/AltiKa) over Arctic region for 15 March–15 April 2013 (spring) and 15 September–15 October 2013 (autumn). A waveform template matching technique is employed for classification of leads and floe pixels. The estimated sea ice freeboards were found in close agreement with “Operation IceBridge quick look” freeboards (RMSD = 0.30 m). The differences between the two freeboards were largely due to snow layer over sea ice (R = 0.8). The estimated freeboards were of the order of 0.08–0.15 m during the two seasons.  相似文献   

10.
2018年北极太平洋区域夏季海冰物理及光学性质的研究   总被引:2,自引:1,他引:1  
The reduction in Arctic sea ice in summer has been reported to have a significant impact on the global climate. In this study, Arctic sea ice/snow at the end of the melting season in 2018 was investigated during CHINARE-2018, in terms of its temperature, salinity, density and textural structure, the snow density, water content and albedo, as well as morphology and albedo of the refreezing melt pond. The interior melting of sea ice caused a strong stratification of temperature, salinity and density. The temperature of sea ice ranged from –0.8℃ to 0℃, and exhibited linear cooling with depth. The average salinity and density of sea ice were approximately 1.3 psu and 825 kg/m~3, respectively, and increased slightly with depth. The first-year sea ice was dominated by columnar grained ice. Snow cover over all the investigated floes was in the melt phase, and the average water content and density were 0.74% and 241 kg/m~3, respectively. The thickness of the thin ice lid ranged from 2.2 cm to 7.0 cm, and the depth of the pond ranged from 1.8 cm to 26.8 cm. The integrated albedo of the refreezing melt pond was in the range of 0.28–0.57. Because of the thin ice lid, the albedo of the melt pond improved to twice as high as that of the mature melt pond. These results provide a reference for the current state of Arctic sea ice and the mechanism of its reduction.  相似文献   

11.
海冰表面和底层形态的特征相关性分析对海冰分类、气候研究以及海冰厚度估计等方面具有重要作用.目前,海冰底层形态的研究较少,且缺乏海冰表面和底层形态的相关性研究.针对这一问题,本文利用加拿大渔业和海洋局提供的积雪表面粗糙度高度(定义为海冰或积雪表面相对于周围平整表面的高度)、海冰底层轮廓、积雪深度以及海冰厚度数据,采用均方...  相似文献   

12.
极地积雪和海冰厚度是气候变化的重要指标,也是船舶在冰区航行需要掌握的主要参数。2014和2015年在南极普里兹湾中山站附近布放了一种新式的温度链浮标,该浮标每天进行4次常规温度观测和1次加热升温观测,用于实时获取积雪和海冰剖面温度及厚度数据的研究。通过分析剖面温度曲线和升温曲线反映出的大气、积雪、海冰和海水4种介质的热传导特性差异,可利用人工识别的方法(人工经验法)获得大气/积雪、积雪/海冰和海冰/海水界面的位置。根据统计不同介质在升温响应和垂直温度梯度等方面的特性,找到合理阈值,可通过编写程序自动判断各界面的位置(自动程序法)。本文利用这两种方法来判断不同物质界面位置从而计算得到积雪和海冰厚度。与现场人工观测的海冰厚度相比,人工经验法的平均偏差和均方根偏差分别为2.1 cm和6.4 cm(2014年)以及4.3 cm和6.5 cm(2015年),自动程序法的平均偏差和均方根偏差分别为-6.8 cm和6.4 cm(2014年)以及4.5 cm和 6.6 cm(2015年);对于积雪,人工经验法与现场人工观测的平均偏差和均方根偏差分别为0.5 cm和 8.5 cm,而自动程序法的平均偏差和均方根偏差分别为4.7 cm和10.8 cm。自动程序法误差较人工经验法偏大,但考虑到整体冰厚和现场观测的误差,两种方法的结果均是可信的,精度是可以接受的。利用新式的温度链浮标实时获取南极普里兹湾积雪和海冰厚度是可行的。  相似文献   

13.
A numerical 1‐dimensional fine grid sea ice thermodynamic model is constructed accounting specially for: (1) slush formation via flooding and percolation of rain‐ and snow meltwater, (2) the consequent snow ice formation via slush freezing, and (3) the effects of snow compaction on heat diffusion in snow cover. The model simulations from ice winter period 1979–90 are viewed against corresponding observations at the Kemi fast ice station (65 °39.8' N, 24° 31.4' E). The 11‐year averaged model results show good overall consistency with corresponding total ice thickness observations. The model slightly overestimates the snow ice thickness and underestimates the snow thickness in February and March, which is mainly addressed to the model assumption of isostatic balance (i.e., slush formation via flooding), which was probably not fully satisfied at the coastal Kemi fast ice station. Supposing that this assumption is nevertheless generally valid away from the very coastal fast ice zone, an estimate for sea ice sensitivity to changes in winter precipitation rate is produced. Increased precipitation leads to an increase only in snow ice thickness with little change in total ice thickness, while a reduction in precipitation of more than {213}50% causes a significant increase in total ice thickness. The difference in modeled total ice thickness for the case of artificially neglecting snow ice physics is about 25%, which indicates the importance of including snow ice physics in a sea ice model dealing with the seasonal sea ice zone.  相似文献   

14.
林龙  赵进平 《海洋学报》2018,40(11):23-32
雪热传导系数是海冰质量平衡过程中的重要物理参数,决定了穿透海冰的热传导通量。北冰洋海冰质量平衡浮标观测获得多年冰上冬季温度链剖面可以明显地区分冰雪界面。本文考虑到冰雪界面处温度随时间变化,再根据冰雪界面热传导通量连续假定,提出了新的雪热传导系数计算方法。受不同环境因素影响,多年冰上各个浮标的雪热传导系数在0.23~0.41 W/(m·K)之间,均值为(0.32±0.08) W/(m·K)。北冰洋多年冰上冬季穿过海冰的热传导通量最大发生在11月至翌年3月,约14~16 W/m2。结冰季节,来自海冰自身降温的热量对穿过海冰向大气传输的热量贡献逐月减少,从9月100%减小到12月的35%,翌年的1月至3月稳定在10%左右。夏季,短波辐射通能量通过热传导自上而下加热海冰,海冰上层温度高于下层,热量传播方向与冬季反向,往海冰内部传递。直到9月短波辐射完全消失,气温下降,热量再次转变为自下往上传递。从冰底热传导来看,夏季出现海冰向冰水界面传递热量现象。由于雪较好的绝热性,冰上覆雪极大地削弱了海冰上层热传导通量,从而减缓了秋冬季节的结冰速度。尽管受雪厚影响,多年冰上层热传导通量与气温依旧具有很好的线性关系,气温每降低1℃,热传导通量增加约0.59 W/m2。  相似文献   

15.
2016年南极中山站固定冰冰厚观测分析   总被引:1,自引:1,他引:0  
极区海冰是全球气候系统的重要组成部分,南极的固定冰普遍存在于其沿海地区,中山站周边固定冰一般在11月中下旬达到最厚。海冰厚度是海冰的重要参数之一,2016年在南极中山站附近3个站点(S1、S2、S3站点)共布放了4套温度链浮标,包括1套SIMBA (Snow and Ice Mass Balance Array)温度链浮标和3套太原理工大学温度链浮标(TY温度链浮标),SIMBA温度链浮标每天观测4次,TY温度链浮标每小时观测1次。利用浮标观测的温度剖面以及海冰和海水间不同介质温度差异计算得到海冰厚度。在S3站点,同时布放了SIMBA温度链浮标和TY温度链浮标。温度链浮标计算冰厚和人工钻孔观测冰厚比较结果显示,S1站点TY温度链浮标计算的海冰厚度平均误差和均方根误差分别为3.3 cm和14.7 cm,S2站点和S3站点分别为6.6 cm、6.9 cm以及4.0 cm、4.8 cm。S3站点的SIMBA温度链浮标计算冰厚和人工观测冰厚的平均误差和均方根误差为8.2 cm和9.7 cm。因而S3站点TY温度链浮标计算的海冰厚度更接近人工观测的结果。进一步对Stefan定律海冰生长模型进行对比,模型计算得到的海冰生长率为0.1~0.8 cm/d,生长率快于TY温度链浮标的结果,且受积雪影响明显。相比于卫星遥感反演冰厚的误差和观测时段的限制以及有限的人工观测,2种温度链浮标未来对于中山站附近海冰的长期监测均有重要的应用价值。  相似文献   

16.
利用加拿大环极冰间水道系统研究项目,作者对2007年11月24日至2008年1月26日北极群岛阿蒙森湾海域秋冬季节一年冰的物理和光学性质进行了观测研究。结果显示,观测期间的海冰厚度整体在27~108 cm范围内变化,积雪厚度仅为0~6 cm。海冰温度、盐度和密度在冰内的分布特征为:海冰表层最低温度为–22.4℃,底层最高温度为–2.2℃,冰内温度随深度单调增大;盐度变化范围为3.30~11.70,冰内盐度剖面呈现“C”形,即表层和底层盐度较大,而中间层盐度较小;海冰的平均密度略大,为(0.91±0.03)g/cm3。通过观测人造光源在海冰中的透射辐射谱分布,发现一年冰的光谱透射辐射在490 nm和589 nm处呈明显的双峰结构,但随着海冰厚度的增加,双峰结构逐渐减弱,体现了海冰对于不同谱段辐射能衰减作用的差异。在可见光范围内,裸冰和雪覆冰的吸收率最小值出现在490 nm,在443~490 nm范围内二者的吸收率随波长增大而降低,在490~683 nm范围内二者的吸收率随波长增大而升高,但雪覆冰的吸收率在可见光范围内基本保持不变,体现了雪覆冰吸收率的光谱独立性。一年冰的谱衰减系数随波长呈“U”字形分布,紫光和红光谱段的衰减系数较大,中间谱段的衰减系数较小,589 nm波长的衰减系数最小,为1.7 m–1。将谱衰减系数在可见光范围内积分,得到一年冰的积分漫射衰减系数约为2.3 m–1,略高于多年浮冰的漫射衰减系数1.5 m–1。阿蒙森湾一年冰与加拿大海盆北部多年浮冰辐射光学性质的差异,主要源于陆源物质输入引起的海冰内含物组分的改变,而不同组分对光谱的吸收和散射性质不同,进一步导致了光学性质的整体变化。  相似文献   

17.
Over the past decades, sea ice in the polar regions has been significantly affecting local and even hemispheric climate through a positive ice albedo feedback mechanism. The role of fast ice, as opposed to drift ice, has not been well-studied due to its relatively small coverage over the earth. In this paper, the optical properties and surface energy balance of land fast ice in spring are studied using in situ observations in Barrow, Alaska. The results show that the albedo of the fast ice varied between 0.57 and 0.85 while the transmittance increased from 1.3×10?3 to 4.1×10?3 during the observation period. Snowfall and air temperature affected the albedo and absorbance of sea ice, but the transmittance had no obvious relationship with precipitation or snow cover. Net solar shortwave radiation contributes to the surface energy balance with a positive 99.2% of the incident flux, with sensible heat flux for the remaining 0.8%. Meanwhile, the ice surface loses energy through the net longwave radiation by 18.7% of the total emission, while the latent heat flux accounts for only 0.1%. Heat conduction is also an important factor in the overall energy budget of sea ice, contributing 81.2% of the energy loss. Results of the radiative transfer model reveal that the spectral transmittance of the fast ice is determined by the thickness of snow and sea ice as well as the amount of inclusions. As major inclusions, the ice biota and particulates have a significant influence on the magnitude and distribution of the spectral transmittance. Based on the radiative transfer model, concentrations of chlorophyll and particulate in the fast ice are estimated at 5.51 mg/m2 and 95.79 g/m2, which are typical values in the spring in Barrow.  相似文献   

18.
基于Hough变换原理的海冰厚度识别方法   总被引:1,自引:1,他引:0  
作为主要海冰参数之一的海冰厚度对海冰灾害评估和极地船舶与冰区海洋工程结构设计具有重要意义。采用船侧视频图像对海冰厚度进行自动识别是提取海冰参数的重要方式。本文采用基于Hough变换的机器视觉方法对海冰翻转过程中的表面轮廓线进行识别,从而自动获取海冰厚度参数。根据海冰图像特征制定了图像边缘识别?近似线段识别?海冰轮廓线段组识别的计算流程。在线段组识别过程中,根据海冰的几何特征建立了由夹角、长度及间距参数相关联的3个识别参数所组成的判断条件。为验证方法的可靠性,将该方法用于“雪龙”号第八次北极科考的走航实测数据中,结果表明,3个识别参数均具有最优阈值。当低于最优值时提高阈值可增加有效识别率;而高于最优值时提高阈值则会导致误判率增大,采用最优阈值可使冰厚识别率达到90%以上。因此,采用基于Hough变换的冰厚识别方法可实现对海冰厚度的实时监测。  相似文献   

19.
The antarctic sea ice was investigated upon five occasions between January 4 and February 15, 2003. The investigations included: (1) estimation of sea ice distribution by ship-based observations between the middle Weddell Sea and the Prydz Bay; (2) estimation of sea ice distribution by aerial photography in the Prydz Bay; (3) direct measurements of fast ice thickness and snow cover, as well as ice core sampling in Nella Fjord; (4) estimation of melting sea ice distribution near the Zhongshan Station; and (5) observation of sea ice early freeze near the Zhongshan Station. On average, sea ice covered 14.4% of the study area. The highest sea ice concentration (80%) was observed in the Weddell Sea. First-year ice was dominant (99.7%-99.8%). Sea ice distributions in the Prydz Bay were more variable due to complex inshore topography, proximity of the Larsemann Hills, and/or grounded icebergs. The average thickness of landfast ice in NeUa Fjord was 169.5 cm. Wind-blown snow redistribution plays an important role in affecting the ice thickness in Nella Fjord. Preliminary freezing of sea ice near the Zhongshan Station follows the first two phases of the pancake cycle.  相似文献   

20.
We detect the mass balance of the Antarctica ice sheet from GRACE for the recent period July 2002 through March 2011. Land hydrology contamination was corrected through global hydrological models and glacial isostatic adjustment (GIA) of the solid Earth since last deglaciation using the IJ05 model, and then a forward model was employed to adjust to bias due to smoothing filters and GRACE's limited resolution. The results show that there are two significant turning points for ice mass losses or gains near the early 2006 and the end of 2008. The ice mass losses in West Antarctica have accelerated dramatically during 2009–2011, while in East Antarctica the rate is positive, mainly caused by snow accumulation. Over the whole studying period, ice loss rates in West Antarctica (?108 ± 36 Gt/yr) are still significantly larger than the increase in East Antarctica (+72 ± 24) Gt/yr. Thus, the total Antarctica contribution to sea level rise is slightly negative ?0.18 ± 0.02 mm/yr. The rapid change of the regional ice mass in Antarctic, in the course of only several years, suggests that the Antarctica ice sheet mass balance is more sensitive to regional climate conditions than considered before.  相似文献   

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