Arctic sea ice volume export through the Fram Strait: variation and its effect factors

Arctic sea ice export is important for the redistribution of freshwater and sea ice mass.Here,we use the sea ice thickness,sea ice velocity,and sea ice concentration(SIC)to estimate the exported sea ice volume through the Fram Strait from 2011 to 2018.We further analyse the contributions of the sea ice thickness,velocity and concentration to sea ice volume export.Then,the relationships between atmospheric circulation indices(Arctic Oscillation(AO),North Atlantic Oscillation(NAO),and Arctic Dipole(AD))and the sea ice volume export are discussed.Finally,we analyse the impact of wind-driven oceanic circulation indices(Ekman transport(ET))on the sea ice volume export.The sea ice volume export rapidly increases in winter and decreases in spring.The exported sea ice volume in winter is likely to exceed that in spring in the future.Among sea ice thickness,velocity and SIC,the greatest contribution to sea ice export comes from the ice velocity.The exported sea ice volume through the zonal gate of the Fram Strait(which contributes 97%to the total sea ice volume export of the Fram Strait)is much higher than that through the meridional gate(3%)because the sea ice flowing out of the zonal gate has the characteristics of a high thickness(mainly thicker than 1 m),a high velocity(mainly faster than 0.06 m/s)and a high concentration(mainly higher than 80%).The AD and ET explain 53.86%and 38.37%of the variation in sea ice volume export,respectively.

Arctic sea ice volume export through the Fram Strait from combined satellite and model data:1979–2012

By combing satellite-derived ice motion and concentration with ice thickness fields from a popular model PIOMAS we obtain the estimates of ice volume flux passing the Fram Strait over the 1979–2012 period. Since current satellite and field observations for sea ice thickness are limited in time and space, the use of PIOMAS is expected to fill the gap by providing temporally continued ice thickness fields. Calculated monthly volume flux exhibits a prominent annual cycle with the peak record in March（roughly 145 km3/month） and the trough in August（10 km^3/month）. Annual ice volume flux（1 132 km^3） is primarily attributable to winter（October through May） outflow（approximately 92%）. Uncertainty in annual ice volume export is estimated to be 55 km^3（or 5.7%）. Our results also verified the extremely large volume flux appearing between late 1980 s and mid-1990 s. Nevertheless, no clear trend was found in our volume flux results. Ice motion is the primary factor in the determination of behavior of volume flux. Ice thickness presented a general decline trend may partly enhance or weaken the volume flux trend. Ice concentration exerted the least influences on modulating trends and variability in volume flux. Moreover, the linkage between winter ice volume flux and three established Arctic atmospheric schemes were examined. Compared to NAO, the DA and EOF3 mechanism explains a larger part of variations of ice volume flux across the strait.

Impact of polar lows on synoptic scale variability of Atlantic inflow in the Fram Strait

The Atlantic inflow in the Fram Strait（78°50′N） has synoptic scale variability based on an array of moorings over the period of 1998–2010. The synoptic scale variability of Atlantic inflow, whose significant cycle is 3–16 d, occurs mainly in winter and spring（from January to April） and is related with polar lows in the Barents Sea. On the synoptic scale, the enhancement（weakening） of Atlantic inflow in the Fram Strait is accompanied by less（more）polar lows in the Barents Sea. Wind stress curl induced by polar lows in the Barents Sea causes Ekman-transport,leads to decrease of sea surface height in the Barents Sea, due to geostrophic adjustment, further induces a cyclonic circulation anomaly around the Barents Sea, and causes the weakening of the Atlantic inflow in the Fram Strait. Our results highlight the importance of polar lows in forcing the Atlantic inflow in the Fram Strait and can help us to further understand the effect of Atlantic warm water on the change of the Arctic Ocean.

Considerable increase in bowhead,blue,humpback and fin whales numbers in the Greenland Sea and Fram Strait between 1979 and 2014

In the frame of our long-term study of cetacean abundance and distribution in polar marine ecosystems begun in 1979, a drastic increase in the bowbead Balaena mysticetus North Atlantic ＂stock＂ was observed from 2005 on, by a factor 30 and more： from 0.0002 per count between 1979 and 2003 （one individual, n=5430 cotmts） to 0.06 per count from 2005 to 2014 （34 individuals, n=6000 counts）; the most significant part of the increase occurred from 2007 on. Other large whale species （Mysticeti） showed a similar pattern, mainly blue Balaenoptera musculus, humpback Megaptera novaeangliae and fin whales Balaenoptera physalus. This large and abrupt increase cannot logically be due to population growth, nor to survival of a hidden ＂relic＂ population, nor to a changing geographical distribution within the European Arctic, taking into account the importance of the coverage during this study. Our interpretation is that individuals passed through the Northwest and/or Northeast Passages from the larger Pacific stock into the almost depleted North Atlantic populations coinciding with a period of very low ice coverage -- at the time the lowest ever recorded. In contrast, no clear evolution was detected neither for sperm whale Physeter macrocephalus nor for Minke whale Balaenoptera acusrostrata.

Recent satellite-derived sea ice volume flux through the Fram Strait： 2011–2015

The Fram Strait（FS） is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a（2011–2015） sea ice thickness record retrieved from Cryo Sat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux（WAVF） based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center（NSIDC） and the Institut Francais de Recherche pour d＇Exploitation de la Mer（IFREMER）, amounts to 1 029 km^3（NSIDC） and1 463 km^3（IFREMER）, respectively. For this period, a mean monthly volume flux（area flux） difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km^3 per month（–18×10~6 km^2 per month）.Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen（UB）, and the two products agree relatively well with a mean monthly bias of（5.7±45.9） km^3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990 s. Compared with P1（1990/1991–1993/1994） and P2（2003/2004–2007/2008）, the WAVF estimates indicate a decline of more than 600 km^3 in P3（2011/2012–2014/2015）. Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations.

An assessment of the CMIP6 performance in simulating Arctic sea ice volume flux via Fram Strait

Numerical models serve as an essential tool to investigate the causes and effects of Arctic sea ice changes.Evaluating the simulation capabilities of the most recent CMIP6 models in sea ice volume flux provides references for model applications and improvements.Meanwhile,reliable long-term simulation results of the ice volume fux contribute to a deeper understanding of the sea ice response to global climate change.In this study,the sea ice volume flux through six Arctic gateways over the past four decades(1979-2014)were estimated in combination of satellite observations of sea ice concentration(SIC)and sea ice motion(SIM)as well as the Pan-Arctic Ice-Ocean Modeling and Assimilation System(PIOMAS)reanalysis sea ice thickness(SIT)data.The simulation capability of 17 CMIP6 historical models for the volume flux through Fram Strait were quantitatively assessed.Sea ice volume flux simulated from the ensemble mean of 17 CMIP6 models demonstrates better performance than that from the individual model,yet IPSL-CM6A-LR and EC-Earth3-Veg-LR outperform the ensemble mean in the annual volume flux,with Taylor scores of 0.86 and 0.50,respectively.CMIP6 models display relatively robust capability in simulating the seasonal variations of volume flux.Among them,CESM2-WACCM performs the best,with a correlation coefficient of 0.96 and a Taylor score of 0.88.Conversely,NESM3 demonstrates the largest devi-ation from the observation/reanalysis data,with the lowest Taylor score of 0.16.The variability of sea ice volume flux is primarily influenced by SIM and SIT,followed by SIC.The extreme large sea ice export through Fram Strait is linked to the occurrence of anomalously low air temperatures,which in turn promote increased SIC and SIT in the corresponding region.Moreover,the intensified activity of Arctic cyclones and Arctic dipole anomaly could boost the southward sea ice velocity through Fram Strait,which further enhance the sea ice outflow.

Sediment bacterial communities are more complex in coastal shallow straits than in oceanic deep straits

Straits are ideal models to investigate the bacterial community assembly in complex hydrological environments. However, few studies have focused on bacterial communities in them. Here, comparable bacterial communities in costal shallow Bohai Strait(BS) and oceanic deep Fram Strait(FS) were studied. The Shannon and Chao1 indices were both higher in BS than in FS. The relative abundances of the classes Deltaproteobacteria and Bacilli and the family Halieaceae were higher in BS than in FS, in contrast to the families OM1_clade and JTB255_marine_benthic_group, revealing typical characteristics of bacterial communities in coastal and oceanic regions. Cluster analysis based on the Bray-Curtis index showed that samples were clustered by depth layer in FS and BS, indicating that structures of bacterial communities would diff er with increasing water depth in straits. Additionally, the cluster relationships among samples in abundant and rare communities were both similar to those in entire communities. However, the dissimilarities among samples showed a descending order as rare communities, entire communities and abundant communities. Network analysis indicated that the BS network was obviously more complex than the FS network. Filamentous bacteria Desulfobulbaceae exhibited high degree values in BS but not in FS, indicating key roles of Desulfobulbaceae in the BS. Our study provides different and common evidences for understanding microbial ecology in coastal shallow and oceanic deep straits.

2011-2020年弗拉姆海峡夏季海冰漂移跟踪及变化分析

准确的弗拉姆海峡海冰漂移监测对于量化弗拉姆海峡的海冰输出量,减少北极海冰流失量估计的不确定性具有十分重要的意义.由于数据源和算法的限制,现有的方法在夏季海冰漂移中应用效果不佳,难以监测到准确的海冰运动.本研究发展了一种基于MODIS时序数据和A-KAZE算法的夏季逐日海冰漂移跟踪方法,并基于该方法开展了2011—2020年弗拉姆海峡夏季(4—9月)逐日的海冰漂移监测研究,分析了近10年弗拉姆海峡海冰流速的变化规律.研究选取2020年4月29日到5月5日弗拉姆海峡局部区域作为实验区对研究提出的方法进行了验证.实验结果表明,本研究提出的方法相比于经典的MCC模式匹配算法在跟踪精度上有很大提高,其中速度的均方根误差减少了2.13 km·d^(-1)(73%),角度的均方根误差减少了10°(38%).相比于常用的SIFT、SURF特征跟踪算法,本方法提取到的海冰漂移矢量在数量上更多,空间分布更广.同时,相比于使用MODIS每日合成数据,本方法使用的时序MODIS影像在实验区获取了更大的海冰漂移跟踪范围,平均每日的跟踪面积提升了862.62 km^(2)(近16倍),有效减少了云覆盖对光学数据跟踪效果的影响.此外,研究发现近10年弗拉姆海峡区域夏季海冰流速的空间分布比较一致,呈现出海峡南部流速高于北部,远离海岸流速高于近岸流速的规律.弗拉姆海峡夏季平均海冰流速在年际上不存在明显的增加或减少的趋势,但是在月尺度上总体呈现出4—7月下降,7—9月回升的趋势.本研究提出的海冰漂移跟踪方法可为夏季的海冰漂移研究提供新的思路,针对近10年弗拉姆海峡夏季海冰流速的分析结果也可应用于北极海冰快速变化等相关研究中.

北极冰海耦合模式对两种不同大气再分析资料响应的分析

本文中我们比较了Climate Forecast System Reanalysis(CFSR)高分辨率的再分析数据集和低分辨率的Japanese 25-year Reanalysis Project(JRA25)再分析数据集在向下短波辐射、向下长波辐射、10m风场、近地面气温、降水、湿度上的不同,发现二者差异最大的为降水数据,其次为向下短波辐射数据、向下长波辐射数据。用这两个数据集驱动同一冰海耦合模式,CFSR强迫的海冰、北冰洋中层水和加拿大海盆温盐结构与实测相比有很大差距,等密度面上的地转流速在加拿大海盆和欧亚海盆比JRA25强迫的结果高20%,同时等密度面的深度偏深、位温偏高,在弗拉姆海峡的流通量也比海洋再分析数据Simple Ocean Data Assimilation(SODA)偏多。CFSR的向下辐射数据更加接近实测,采用此数据的敏感性实验模拟结果与实测符合的更好。对于海冰的模拟,云量起着至关重要的作用,降水带来的淡水通量通过影响大西洋入流水携带的热量进而影响到冰区。此外,CFSR过量的降水也是二者对于北冰洋温盐结构、弗拉姆海峡流通量以及地转流强度模拟产生偏差的主要原因。尽管风场的分辨率不同,在海盆尺度上对于海冰和海水温盐结构的影响并不大。

基于FY-3/MERSI数据的北冰洋流冰自动提取与跟踪方法

北冰洋航路是未来全球航运的重点开拓领域,海冰运动对北冰洋航路开发有重要影响。本文利用风云三号卫星中分辨率光谱成像仪(FY-3/MERSI)数据的特点和优势,研究北冰洋流冰自动提取和运动跟踪的方法。首先在分析流冰灰度分布特征的基础上,提出分区域阈值分割与梯度差分相结合的方法实现块状流冰提取,然后根据块状流冰的多种几何特征匹配同名流冰并计算其运动速度。应用这种方法跟踪2011年6月弗雷姆海峡流冰运动,跟踪结果与美国国家冰雪数据中心提供的极地网格化日均海冰运动矢量整体趋势一致,验证了方法的有效性。这种方法获取各块流冰实际运动速度,可以有效弥补网格化海冰运动平均速度场分布和细节的不足,为北冰洋航路开发提供更详细的流冰运动信息。

基于遥感数据的近40 a弗雷姆海峡海冰输出研究

北极海冰作为一个巨大的淡水资源库,每年向全球输送大量淡水资源,从北极输出的海冰在向南输送的过程中融化,对海洋水循环与水环境产生影响,进而影响全球气候变化,弗雷姆海峡作为北极海冰输出的主要通道,对其研究显得尤为重要。为了解弗雷姆海峡海冰长期输出量,利用美国冰雪数据中心(NSIDC)发布的海冰密集度、海冰厚度与海冰漂移速度数据,计算得到1979年至2019年弗雷姆海峡海冰输出面积通量与2010至2019年弗雷姆海峡海冰输出体积通量,并在此基础上分析弗雷姆海峡近40 a海冰输出量的变化状况以及弗雷姆海峡海冰输出的年际变化、季节变化,并分析了影响弗雷姆海峡海冰输出量的可能原因。结果表明:近40 a弗雷姆海峡年均海冰输出面积通量为7.83×10^(5)km^(2),近10 a弗雷姆海峡海冰年均输出体积通量为1.34×10^(6)km^(3),从长期来看,弗雷姆海峡海冰输出面积通量呈略微增加趋势,弗雷姆海峡海冰输出体积通量在2010—2019年整体呈下降趋势,且变化幅度很大,在2015年与2019年呈现出海冰低输出。总体而言,弗雷姆海峡海冰输出量变化趋势并不明显,但显示出较大的年际与季节变化,海冰输出主要发生在冬季与春季,海冰密集度与海冰漂移速度对于弗雷姆海峡海冰输出量有关键影响。

三种国际主流的北极卫星遥感冰速产品评估和分析

冰速是海冰的重要参数,但是受资料长度限制,对卫星遥感冰速产品进行系统比较和评估的研究还较少。利用2009年-2017年国际北极浮标计划(IABP)浮标冰速数据,较系统地评估了不同时间间隔的遥感反演冰速产品在北冰洋内区和弗拉姆海峡附近海区的表现。结果显示,对北冰洋内区而言,1 d间隔的美国国家雪冰数据中心(NSIDC)遥感冰速冬季误差整体大于夏季,冬季高估了波弗特海南部海冰向西的运动,低估了从喀拉海流向格陵兰岛北部的穿极流。对于5种2 d间隔冰速产品而言,产品精度不完全取决于源数据空间分辨率的高低,反演算法的改进和数据融合均能提高冰速的精度,均方根误差大小的顺序是OSISAF-Merged<OSISAFAMSR<Ifremer-AMSR<OSISAF-SSM<OSISAF-ASCAT。对于4种使用相同反演算法的3 d间隔的冰速产品,产品的均方根误差取决于源数据分辨率,空间分辨率最高的Ifremer-AMSR冰速均方根误差最小。比较不同种类、不同时间间隔冰速的月平均均方根误差后可知,采用3 d间隔反演的冰速由于能够忽略更多短时间尺度海冰运动,其冰速均方根误差低于2 d间隔的冰速。在弗拉姆海峡,除Ifremer-AMSR外,其余冰速产品均具有较大的经向偏差和均方根误差。在冰速较快弗拉姆海峡,冰速产品均方根误差取决于源数据的分辨率。