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海冰上积雪的分布是影响海冰与大气能量交换以及气候变化的重要因素。当前的CMIP6气候模式（如CESM2和NESM3）采用定常的积雪密度,而专注于模拟雪厚度和密度变化的模式（如SnowModel-LG）则采用经验的变化雪密度公式。对比CryoSat-2卫星观测的积雪厚度发现,从积雪厚度的空间分布与平均值难以判断出变化雪密度对北冰洋积雪厚度模拟产生何种影响,对于变化雪密度模拟积雪厚度的改进及机制有待进一步研究。本文采用随气温、风速等因子变化的雪密度经验公式模型,并利用SNOTEL单站的长时间序列观测资料,对不同影响因子设计如下敏感性实验:A. 考虑所有气象因子的变化雪密度模型;B. 常数雪密度模型;C. 在A中不考虑风对密实化的影响;D. 在A中不考虑气温对密实化的影响。实验A、B、C和D诊断计算的2018年11月1日至2019年5月10日积雪厚度的均方根误差分别为4.2 cm、4.8 cm、25.9 cm和4.2 cm。结果表明,变化雪密度方案A模拟的积雪密度、厚度在平均值上与常数雪密度的结果接近,但其模拟的积雪厚度均方根误差最小,并且能够模拟出积雪厚度在几天到十几天时间尺度上的高频变化,同时减小了这种高频变化对应时段雪厚模拟结果的相对误差,二者具有一定的相关性。此外,还发现气温变化对积雪密实化的影响远小于风。 相似文献
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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
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基于温度链浮标获取南极普里兹湾积雪和固定冰厚度的研究 总被引：2，自引：2，他引：0
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
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工作在Ku波段的Cryo Sat-2和Sentinel-3A合成孔径雷达高度计是当前最先进的高度计。由于雷达回波信号的实际时间跟踪点较预设的时间跟踪点总发生偏移,而且Ku波段波长短,进行海冰探测时易受雪层干扰,造成雷达信号主散射面由海冰表面上移至雪层内,这两个因素都影响着海冰干舷高度的反演精度。针对这些问题,本文首先确定了Cryo Sat-2与Sentinel-3A雷达高度计反演北极海冰干舷高度的最优波形重跟踪阈值组合,然后分析了这两个Ku波段雷达信号的雪层穿透系数,发现Ku波段高度计的主散射面受雪层的影响显著,会高估海冰干舷高度。基于此,文中提出了一种改进的积雪校正方法,并以机载Operation Ice Bridge(OIB)为验证数据,将本文提出的方法与通用积雪校正法和欧洲空间局(European Space Agency,ESA)海冰干舷高度产品进行了对比验证。实验结果表明,本文提出的方法能够有效估计Ku波段电磁波穿透海冰表面积雪深度的比例系数,显著校正了通用积雪校正方法存在的高估海冰干舷高度的问题,提高了海冰干舷高度的估算精度。 相似文献
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2007年11月-2008年2月在北极阿蒙森湾进行了冰上积雪的光学衰减性质的观测实验。该实验是在极夜条件下,通过人造光源研究波长313～875nm范围内的光在雪中传播的衰减性质。实验结果验证了可见光在冰上积雪传播过程中,其辐射强度随积雪厚的增长呈指数迅速衰减的规律特征,而且光在积雪中的衰减率远大于海冰中的衰减。根据不同雪厚的光学观测结果,计算出不同波长的可见光在雪中传播的衰减系数。结果表明,465～625 nm范围内的光在雪中衰减系数最小,并且随波长变化基本为常量,其平均值为20 m~(-1)。当波长在此范围之外,可见光的衰减系数迅速升高,衰减系数最高甚至超过30 m~(-1)。此外,根据观测初步分析了雪的密度变化对光在雪中的衰减系数的影响,结果表明,积雪密度的变化对不同波长光的衰减系数影响不同。入射光的波长越大,光的衰减系数受积雪密度变化的影响越大。本文还估算了积雪密度变化造成的光的衰减系数的误差率。 相似文献
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北极地区天气复杂多变极其敏感,是全球气候的风向标,同时,北极地区冰雪的变化对全球水循环系统也有极大的影响。北极海冰表面积雪由于其自身的隔热性和电导性,对北极地区的海冰、气候和水循环等又有着极其重要的影响。遥感测量是监测北极冰雪参数的重要途径,但现有业务化积雪产品的时间和空间覆盖范围有限,美国冰雪中心提供的AMSR-E业务化数据产品中仅提供了2002-2011年间北冰洋一年冰表面的积雪产品。本文将SMOS/MIRAS(Soil Moisture and Ocean Salinity Mission/Microwave Imaging Radiometer using Aperture Synthesis)观测的亮温数据与Ice Bridge航测积雪厚度数据进行了对比,分析北极多年冰表面积雪厚度与L波段1.4 GHz亮温之间的相关性,从而探讨SMOS数据反演积雪的可行性。根据Ice Bridge项目中北极航次时间,文中选取2011-2015年每年3至4月遥感及航测数据进行时空匹配,空间范围为60°N以北地区。通过两者相关性分析,得到在0~50 cm范围内,随着雪厚增加,亮温也呈增长趋势。两者之间的正相关关系为利用1.4 GHz亮温数据反演北极多年冰表面积雪厚度提供了可能,对进一步完善现有的积雪产品也具有一定的意义。 相似文献
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2016年4月至11月在南极中山站普里兹湾布设了A1、A2、A3 3套冰雪情检测传感器。传感器每隔1 h采集一次数据,实时获取了被测点空气、积雪、海冰和海水的剖面温度数据。通过对不同介质剖面温度的分析,系统可以有效反映出海冰、积雪在气温影响下的温度变化差异,即空气、积雪、海冰和海水的热传导特性差异。通过寻找合理的温度阈值,编写MATLAB程序分别对积雪、海冰上下界面位置进行了自动判断,从而得到整个观测期间海冰厚度和积雪深度的变化过程。并与人工观测进行比较,结果表明:从传感器安装时间开始,海冰持续增长,10月开始海冰增长速度放慢,直至10月末达到最大海冰厚度170 cm左右。A1、A2、A3传感器采集的冰厚值与人工观测值之间平均误差分别为5.1 cm(A1)、3.4 cm(A2)、3.6 cm(A3);积雪深度的平均误差分别为3.2 cm(A1)、3.5 cm(A2)、2.7 cm(A3),传感器测得的积雪、海冰厚度结果可以较好的反映出被测地点冰雪情的演变过程,是一种可以应用于条件恶劣地区的冰雪环境有效检测手段。 相似文献
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利用地面自动气象站资料、人工加密积雪深度逐时观测资料和ERA5再分析资料,对山东2021年11月6—8日极端雨雪过程积雪特征进行分析。结果表明：(1)降水量突破同期历史极值导致此次雨雪过程成为极端天气事件,积雪深度是预报难点。(2)暴雪和积雪集中分布在山东的中北部地区,有量积雪的范围与降雪量R≥5 mm的分布范围基本一致。积雪深度具有明显的时间变化特征。(3)在山东典型回流暴雪天气形势下,有利的水汽、动力条件和冷空气降温作用,造成山东出现极端雨雪。低层的强冷平流降温导致降水发生相态转换,山东中北部出现暴雪及严重积雪。(4)积雪区降雪含水比差异大,平均降雪含水比为0.53 cm·mm-1,比历史平均值偏低。积雪深度与高空温度、相对湿度和垂直速度的配置有关,低的温度有利于降雪和积雪。地理位置、鲁中山地地形和地面风速对积雪深度有影响,海陆差异较纬度差异影响大,海拔高度影响较小。(5)欧洲中期天气预报中心业务预报模式积雪产品对山东积雪有较好的预报能力,时效近、误差小,但存在预报总体偏弱、北部偏小和中南部偏大的特点。 相似文献
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海冰运动是影响北极海冰平流输运和物质平衡空间重新分布的重要因素。本研究基于2018年9月至2019年8月期间北冰洋66个冰基浮标位置记录数据,结合大气再分析数据,计算得到了海冰运动速度、冰速与风速的比值和海冰运动惯性强度,以刻画北极海冰运动学特征参数在一个冰季的时空变化,并讨论了不同区域冰速与风速比与海冰密集度的关联性。海冰漂移速度在波弗特–楚科奇海、东北极中央区和西北极中央区呈秋冬降低春夏升高的季节变化特征。格陵兰海月均海冰漂移速度（（0.32±0.06）m/s）最大,其次是弗拉姆海峡（（0.17±0.07）m/s）和波弗特–楚科奇海（（0.14±0.05）m/s）,而东北极中央区（（0.09±0.02）m/s）和西北极中央区（（0.07±0.03）m/s）较低。在月尺度上,冰漂移速度与风速的比值主要受海冰漂移速度支配。弗拉姆海峡和格陵兰海受较强的表层海流影响,冰速与风速比值较大,西北极中央区、东北极中央区和波弗特–楚科奇海的冰速与风速比值随着海冰密集度的增加趋近,并分布在0～0.02之间。所有浮标的月平均惯性运动指数为0.158±0.144,秋冬季过渡期间,海冰对风的响应以及海冰运... 相似文献
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基于中国北极考察布放浮标观测和数值模拟的海冰和积雪厚度变化分析 总被引：1，自引：0，他引：1
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
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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
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Jiechen Zhao Tao Yang Qi Shu Hui Shen Zhongxiang Tian Guanghua Hao Biao Zhao 《海洋学报(英文版)》2021,40(7):129-141
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
14.
Tuomo M. Saloranta 《地球，A辑:动力气象学与海洋学》2000,52(1):93-108
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
15.
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
16.
Takenobu Toyota Shinya Takatsuji Kazutaka Tateyama Kazuhiro Naoki Kay I. Ohshima 《Journal of Oceanography》2007,63(3):393-411
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
17.
The effect of the internal friction of snow covering floating ice on small-amplitude waves generated by a periodic-in-time source in a basin with a density jump is considered. The dependences of amplitude-phase characteristics of the wave disturbances induced by surface and internal waves on the snow viscosity coefficient, the oscillation frequency, and the depth of the source are studied.Translated by V. Puchkin. 相似文献