The sudden ocean warming and its potential influences on earlyfrozen landfast ice in the Prydz Bay, East Antarctica

The ocean conditions beneath the ice cover play a key role in understanding the sea ice mass balance in the polar regions.An integrated high-frequency ice-ocean observation system,including Acoustic Doppler Velocimeter,Conductivity-Temperature-Depth Sensor,and Sea Ice Mass Balance Array(SIMBA),was deployed in the landfast ice region close to the Chinese Zhongshan Station in Antarctica.A sudden ocean warming of 0.14℃(p<0.01)was observed beneath early-frozen landfast ice,from(−1.60±0.03)℃during April 16-19 to(−1.46±0.07)℃during April 20-23,2021,which is the only significant warming event in the nearly 8-month records.The sudden ocean warming brought a double rise in oceanic heat flux,from(21.7±11.1)W/m^(2) during April 16-19 to(44.8±21.3)W/m^(2) during April 20-23,2021,which shifted the original growth phase at the ice bottom,leading to a 2 cm melting,as shown from SIMBA and borehole observations.Simultaneously,the slowdown of ice bottom freezing decreased salt rejection,and the daily trend of observed ocean salinity changed from+0.02 d^(-1) during April 16-19,2021 to+0.003 d^(-1) during April 20-23,2021.The potential reasons are increased air temperature due to the transit cyclones and the weakened vertical ocean mixing due to the tide phase transformation from semi-diurnal to diurnal.The high-frequency observations within the ice-ocean boundary layer enhance the comprehensive investigation of the ocean’s influence on ice evolution at a daily scale.

Spatial and temporal evolution of landfast ice near Zhongshan Station, East Antarctica, over an annual cycle in 2011/2012

Annual observations of first-year ice(FYI) and second-year ice(SYI) near Zhongshan Station, East Antarctica,were conducted for the first time from December 2011 to December 2012. Melt ponds appeared from early December 2011. Landfast ice partly broke in late January, 2012 after a strong cyclone. Open water was refrozen to form new ice cover in mid-February, and then FYI and SYI co-existed in March with a growth rate of 0.8 cm/d for FYI and a melting rate of 2.7 cm/d for SYI. This difference was due to the oceanic heat flux and the thickness of ice,with weaker heat flux through thicker ice. From May onward, FYI and SYI showed a similar growth by 0.5 cm/d.Their maximum thickness reached 160.5 cm and 167.0 cm, respectively, in late October. Drillings showed variations of FYI thickness to be generally less than 1.0 cm, but variations were up to 33.0 cm for SYI in March,suggesting that the SYI bottom was particularly uneven. Snow distribution was strongly affected by wind and surface roughness, leading to large thickness differences in the different sites. Snow and ice thickness in Nella Fjord had a similar "east thicker, west thinner" spatial distribution. Easterly prevailing wind and local topography led to this snow pattern. Superimposed ice induced by snow cover melting in summer thickened multi-year ice,causing it to be thicker than the snow-free SYI. The estimated monthly oceanic heat flux was ～30.0 W/m2 in March–May, reducing to ～10.0 W/m2 during July–October, and increasing to ～15.0 W/m2 in November. The seasonal change and mean value of 15.6 W/m2 was similar to the findings of previous research. The results can be used to further our understanding of landfast ice for climate change study and Chinese Antarctic Expedition services.

Model simulations of the annual cycle of the landfast ice thickness in the East Siberian Sea

The annual cycle of the thickness and temperature of landfast sea ice in the East Siberian Sea has been examined using a one-dimensional thermodynamic model. The model was calibrated for the year August 2012-July 2013, forced using the data of the Russian weather station Kotel＇ny Island and ECMWF reanalyses. Thermal growth and decay of ice were reproduced well, and the maximum annual ice thickness and breakup day became 1.64 m and the end of July. Oceanic heat flux was 2 W.m^-2 in winter and raised to 25 W.m^-2 in summer, albedo was 0.3-0.8 depending on the surface type （snow/ice and wet/dry）. The model outcome showed sensitivity to the albedo, air temperature and oceanic heat flux. The modelled snow cover was less than 10 cm having a small influence on the ice thickness. In situ sea ice thickness in the East Siberian Sea is rarely available in publications. This study provides a method for quantitative ice thickness estimation by modelling. The result can be used as a proxy to understand the sea ice conditions on the Eurasian Arctic coast, which is important for shipping and high-resolution Arctic climate modelling.

Physics of Arctic landfast sea ice and implications on the cryosphere: an overview

Landfast sea ice(LFSI)is a criticalcomponent of the Arctic sea ice cover,and is changing as a result of Arctic amplification of climate change.Located in coastal areas,LFSI is of great significance to the physical and ecological systems of the Arctic shelf and in local indigenous communities.We present an overview of the physics of Arctic LFSI and the associated implications on the cryosphere.LFSI is kept in place by four fastenmechanisms.The evolution of LFSI is mostly determined by thermodynamic processes,and can therefore be usedas an indicator of local climate change.We also present the dynamic processes that are active prior to the formation of LFSI,and those that are involved in LFSI freeze-up and breakup.Season length,thickness and extent of Arctic LFSI are decreasing andshowing different trends in different seas,and therefore,causing environmental and climatic impacts.An improved coordination of Arctic LFSI observation is needed with a unified and systematic observation network supported by cooperation between scientists and indigenous communities,as well as a better application of remote sensing data to acquire detailed LFSI cryosphere physical parameters,hence revolving both its annual cycle and long-term changes.Integrated investigations combining in situ measurements,satellite remote sensing and numerical modeling are needed to improve our understanding of the physical mechanisms of LFSI seasonal changes and their impacts on the environment and climate.

Anomalous extensive landfast sea ice in the vicinity of Inexpressible Island, Antarctica

On 10 December 2017,a Chinese research vessel R/V Xuelong encountered an extensive area of landfast ice offshore Inexpressible Island(Antarctica)near the location where the fifth Chinese Antarctic research station is to be built.Using multi-source satellite images and weather data,we analyzed the ice conditions during the event season and reconstructed the development of landfast ice.Two stages in late September and early October were identified as contributing to the final ice extent.These two events are highly related to local-and large-scale weather conditions.Satellite images from 2003 to 2017 showed that four in fifteen years experienced severe landfast ice conditions,suggesting that it is not a rare phenomenon.

Evaluating Parameterizations for Turbulent Fluxes over the Landfast Sea-Ice Surface in Prydz Bay, Antarctica

It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).

Modelling the annual cycle of landfast ice near Zhongshan Station,East Antarctica

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 10th 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).

Thickness simulation of landfast ice along Mawson Coast,East Antarctica based on a snow/ice high-resolution thermodynamic model

Landfast ice plays an important role in atmosphere‒ocean interactions and ecosystems in the near coast area of Antarctica.Understanding the characteristics and variations of landfast ice is crucial to the study of climates and field activities in Antarctic.In this study,a high-resolution thermodynamic snow-ice(HIGHTSI)model was applied to simulate the seasonal changes of landfast ice along the Mawson Coast,East Antarctica,through ERA-Interim reanalysis data.Four ocean heat-flux(Fw)values(10,15,20 and 25 W m−2)were used in sensitivity experiments.The results showed that it is reasonable to simulate landfast ice using the HIGHTSI model,and the simulation of landfast ice thickness matched best well with field measurements when Fw was 20 W m^(−2).Then,2-D distributions of landfast ice from 2006 to 2018 were modeled by HIGHTSI with 2-D ERA-Interim reanalysis data in a 0.125°×0.125°cell grid as external forcing.The results showed that fast ice was thicker along the coast and thinner near open water,and usually reaches its maximal thickness in October,varying from 1.2 to 2.0 m through the study area.There was no statistical trend for the thickness during the study period.

2016年南极中山站固定冰冰厚观测分析

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。

基于海冰分析图获取北极固定冰分布的方法研究

对北极沿岸地区固定冰的分析研究,将有助于更全面认识北极海冰的变化趋势,并为进一步探索北极航道的开发利用提供数据支撑。基于美国国家冰中心发布的2008-2018年逐周/逐两周海冰分析图发展了一个数据转化处理方法,准确提取了全北极逐周的固定冰分布格点数据。分析该时间序列发现,北极平均固定冰范围为(9.0±6.3)×105 km2,呈现出(-1.0±3.9)×103 km2·a-1的减小趋势;4月份固定冰范围最大,多年平均值为1.6×106 km2,处于北极冬季的1-6月份的范围均高于百万平方公里,而7-10月份为北半球夏季,几乎无固定冰存在。将MODIS图像作为基准数据对不同月份的七组结果进行对比验证,结果显示:结冰末期和融冰前期的平均偏差较小,如2012年3月12日的固定冰外缘线平均偏差为-0.8 km;而融冰末期的偏差较大,如2009年9月14日的固定冰外缘线平均偏差为-9.4 km;但所有月份的验证误差都小于格点网格的大小(25 km),因此认为该方法是可行的,得到的格点数据可以代表固定冰的真实分布情况。

南极纳拉海峡固定冰生长、结构、盐度和氧同位素组成

采用第19次中国南极科考采集的冰芯样品、数据,基于海冰的"冻结日"记录,使用海冰一维热力学模型来计算纳拉海峡固定冰的生长厚度.考虑气象条件以及冰情观测结果,将该模型的计算海冰厚度和实测厚度进行比较发现,在纳拉海峡存在着多年生长的海冰.对采集于南极洲中山站附近纳拉海峡的固定冰冰芯样品进行结构、盐度和稳定氧同位素(δ18O)分析,获取了海冰的结构和盐度剖面特征、冰芯雪冰、附加冰的含量、雪冰中的雪以及全部冰芯中雪所占的百分比.结果表明:样品冰芯具有典型的海冰特征结构,如柱状冰水平方向的C轴以及上部粒状冰层和下部柱状冰层结构特征,部分柱状冰中间存在着粒状冰夹层;盐度和δ18O剖面也显示了多年冰生长的证据.海冰的结构和氧同位素特征表明,纳拉海峡固定冰的生长主要受热力学过程控制,其结果和2000年1月至2003年2月人工冰情观测结果一致,观测中没有发现冰脊、叠置等动力过程.附加冰在冰芯中所占的比例平均为5.01%.使用不同的同位素标准来区分雪冰层,估计研究区域平均有多达16.4%～37.9%的雪冰,海冰粒状层中雪的部分约占全部冰厚度的0.8%～23.5%.

基于Sentient-1A的波罗的海沿岸固定冰形变研究

为研究沿岸固定冰的形变特征,本文基于2018年1—3月连续获取的5景Sentient-1A雷达数据,利用差分合成孔径雷达干涉测量(D-InSAR)技术对波罗的海东北部的沿岸固定冰进行了探测。阐述了重复轨道雷达差分干涉测量探测固定冰形变的基本原理及数据处理流程,并结合气象观测数据分析了固定冰形变产生的原因。研究指出:3个观测时期固定冰的最大形变量分别为0.17,0.31和0.19 m;强风驱动的浮冰撞击是造成固定冰形变的重要因素;气温达到0℃以上造成冰的融—冻循环和降雨造成冰层表面雪层变成冰粒是导致相干性降低的主要因素。