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.     

基于卫星高度计的北极海冰厚度变化研究

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.     

北极地区不同冰龄的海冰厚度变化研究

In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite(ICESat)-based results show a thickness reduction over perennial sea ice(ice that survives at least one melt season with an age of no less than 2 year) up to approximately 0.5–1.0 m and 0.6–0.8 m(depending on ice age) during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980 s, there is a clear thickness drop of roughly 0.50 m in 2010 s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water(primarily via albedo feedback) in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness.     

Spatiotemporal characteristics of sea ice transport in the Baffin Bay and its association with atmospheric variability

Sea ice export through the Baffin Bay plays a vital role in modulating the sea ice cover variability in the Labrador Sea.In this study,satellite-derived sea ice products are used to obtain the sea ice area flux (SIAF) through the three passages in the Baffin Bay (referred to as A,B,and C for the north,middle,and south passages,respectively).The spatial variability of the monthly sea ice drift in the Baffin Bay is presented.The interannual variability and trends in SIAF via the three passages are outlined.The connection to several large-scale atmospheric circulation modes is assessed.Over the period of 1988–2015,the average annual (October to the following September) SIAF amounts to 555×10~3 km~2,642×10~3 km~2,and 551×10~3 km~2 through Passages A,B,and C,respectively.These quantities are less than that observed through the Fram Strait (FS,707×10~3 km~2) of the corresponding period.The positive trends in annual SIAF,on the order of 53.1×10~3 km~2/(10 a) and 43.2×10~3 km~2/(10 a)(significant at the 95%confidence level),are identified at Passages A and B,respectively.The trend of the south passage (C),however,is slightly negative (–13.3×10~3 km~2/(10 a),not statistically significant).The positive trends in annual SIAF through the Passages A and B are primarily attributable to the significant increases after 2000.The connection between the Baffin Bay sea ice export and the North Atlantic Oscillation is not significant over the studied period.By contrast,the association with the cross-gate sea level pressure difference is robust in the Baffin Bay (R equals 0.69 to 0.71,depending on the passages considered),but relatively weaker than that over FS (R=0.74).     

A coupled ice-ocean model for the Bohai Sea Ⅱ. Case study

The coupled ice-ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat balance at the sea-ice, air-ice, and air-sea interfaces of the Bohai Sea during the entire winter in 1998-1999 and 2000-2001. The coupled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.     

A coupled ice-ocean model for the Bohai Sea Ⅱ. Case study

The coupled ice-ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat balance at the sea-ice, air-ice, and air-sea interfaces of the Bohai Sea during the entire winter in 1998～1999 and 2000～2001. The coupled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.     

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 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).     

Physical structure and vertical distribution of chlorophyll a in winter sea ice from the northwestern Weddell Sea, Antarctica

The investigation on sea-ice biology in combination with physics, chemistry and ecology was carried out in the northwestern Weddell Sea, Antarctica, during the cruise ANT/XX III-7 on board POLARSTERN in the austral winter (August-October) in 2006. The distribution of chlorophyll a was measured and related to sea ice texture. The mean concentrations of chlorophyll a in the sea ice varied considerably with ice texture. The concentration of chlorophyll a per core ranged from 2.10– 84.40 μg/dm 3 with a mean of 16.56 μg/dm 3 . And the value of R (chlorophyll a / gross chlorophyll) ranged from 0.79–0.83. These high winter chlorophyll values indicate that primary production is considerable and confirms that there is significant primary production in Antarctic sea ice during winter. Thus this constitutes a major proportion of southern ocean primary production and carbon flux before the sea ice retreats.     

Rapid decrease in Antarctic sea ice in recent years

A 41-year Antarctic sea ice concentration(SIC) dataset derived from satellite passive microwave radiometers during the period of 1979–2019 has been used to analyze sea ice changes in recent decades. The trends of SIC and sea ice extent(SIE) are calculated during the periods of 1979–2019, 1979–2013, and 2014–2019. The trends show regionally dependent features. The SIC shows an increasing trend in most of the regions except the Bellingshausen Sea and Amundsen Sea(BA) during 1979–2019 and 1979–2013. The SIE trend shows a decreasing or decelerating trend in the period of 1979–2019((6 835±2 210) km2/a) compared with the 1979–2013 period((18 600±2 203) km~2/a). In recent years(2014–2019), the SIC and SIE have exhibited decreasing trends(–(34 567±3 521) km~2/month), especially in the Weddell Sea(WS) and Ross Sea(RS) during summer and autumn. The trends are related to regionally dependent causes. The analyses show that the SIC and SIE decreased in response to the warming trend of 2 m air temperature(T_(a-2m)) and have exhibited a good relationship with T_(a-2m) in summer and autumn in recent years. The sea ice decrease in the Antarctic is mainly caused by increases in absorbed energy and southward energy transportation in recent years, such as the increase in gained solar radiation and moist static energy from the south, which demonstrate notable regional characteristics. In the WS region, the local positive feedback from the additional absorbed solar radiation, resulting in warmer air and reduced sea ice, is the main reason for the sea ice decrease in recent years. The increase in southward energy transport has also favored a decrease in sea ice. In the RS region, the increase in southward-transported moist static energy has contributed to the decrease in sea ice, and the increases in cloud cover and longwave radiation have prevented sea ice growth.     

A motion correction on direct estimations of air-sea fluxes from a buoy

A flux system deployed on a moored buoy has been described, which is capable of directly estimating the airsea fluxes after removing the contamination in the signal due to buoy motion. A triple loop fitting method has been demonstrated for determining the three angular offsets between measurement axes of the sonic anemometer and motion pack. The data collected in an experiment in the Northern Huanghai Sea is used to correct the three sonic anemometer measurements of turbulent wind for buoy motion. The effective removal of wave-scale motion from the spectra and cospectra are demonstrated. Estimates of along-wind momentum flux, sensible heat flux and latent heat flux calculated by the eddy correlation method based on data obtained by sonic anemometer 81000V are shown to be in the same trend and scale with those determined by the bulk aerodynamic method after motion correction. The motion correction not only greatly improve the estimation of the momentum flux but also has a great impact on the calculated sensible heat flux.     

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 7.83×10⁵ km²,近 10 a 弗雷姆海峡海冰年均输出体积通量为 1.34×10⁶ km³, 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—20...     

基于卫星观测的2003-2013年北极海冰体积变化估算

北极海冰正处于快速减退时期，北极海冰体积变化是全球气候变化的重要指示因子。本文利用两种卫星高度计数据（ICESat和CryoSat-2）反演得到的海冰厚度数据，结合星载辐射计提取的海冰密集度数据以及海冰年龄数据，估算了近期的北极海冰体积以及一年冰和多年冰体积变化。CryoSat-2观测时段（2011-2013年）与ICESat观测时段（2003-2008年）相比，北极海冰体积在秋季（10-11月）和冬季（2-3月）分别减少了1 426 km3和412 km3。其中，秋季和冬季的一年冰的体积增加了702 km3和2 975 km3。相反，多年冰分别减少了2 108 km3和3 206 km3。多年冰的大量流失是造成北极海冰净储量下降的主要原因。     

基于CryoSat-2卫星测高数据的北极海冰体积估算方法

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。     

Reproduction of the large-scale state of water and sea ice in the Arctic Ocean from 1948 to 2002: Part II. The state of ice and snow cover

This paper presents the results of reconstructing the state of ice and snow covers on the Arctic Ocean from 1948 to 2002 obtained with a couplod model of ocean circulation and sea-ice evolution. The area of the North Atlantic and Arctic Ocean north of 65° N, excluding Hudson Bay, is considered. The monthly mean ice areas and extents are analyzed. The trends of these areas are calculated separately for the periods of 1970–1979, 1979–1990, and 1990–2002. A systematic slight underestimation by the model is observed for the ice extent. This error is estimated to fit the error of 100 km in determining the position of the ice edge (i.e., close to the model resolution). In summer the model fails to reproduce many observed polynias: by observational data, the ice concentration in the central part of the Arctic Ocean constitutes around 0.8, while the model yields around 0.99. The average trend for the area of ice propagation in 1960–2002 is 13931 km²/year (or approximately 2% per decade); the trend of the ice area is 17643 km²/year (or approximately 3% per decade). This is almost three times lower than satellite data. The calculated data for ice thickness in the late winter varies from 3.5 to 4.8 m, with a clear indication of periods of thick ice (the 1960s–1970s) and relatively thin ice (the 1980s); 1995 is the starting point for quick ice-area reduction. The maximum ice accumulation is in 1977 and 1988; here, the average trend is negative: −121 km³/year (or approximately 5.5% per decade). In 1996–2002, the average change in the ice thickness constituted +1.7 cm/year. This speaks to the relatively fast disappearance of thin-ice fractions. This model also slightly underestimates the snow mass with a trend of −2.5 km³/year (almost 0.35 mm of snow per year or 0.1 mm of liquid water per year). An analysis of the monthly mean ice-drift velocity indicates the good quality of the model. Data on the average drift velocity and the results of comparisons between the calculated and satellite data for individual months are presented. A comparison with observational data from 1990–1996 in the Fram Strait shows that the model yields 3.28 m for the average ice thickness against the observed value of approximately 3.26 m. For the same period, the model yields a monthly mean transport of 291.29 km³ as compared to the observed value of 237.17 km³. A comparison between the measured and calculated drift velocities in the Fram Strait indicates that the model value is around 9.78 cm/s, which is comparable to the measured value of 10.2 cm/s. The existing problems with describing the ice redistribution by thickness gradations are illustrated by comparing data on ice thickness in the Fram Strait.     

A Coupled Ice-Ocean Model in the Pan-Arctic and North Atlantic Ocean: Simulation of Seasonal Cycles

A coupled ice-ocean model is configured for the pan-Arctic and northern North Atlantic Ocean with a 27.5 km resolution. The model is driven by the daily atmospheric climatology averaged from the 40-year NCEP reanalysis (1958–1997). The ocean model is the Princeton Ocean Model (POM), while the sea ice model is based on a full thermodynamical and dynamical model with plastic-viscous rheology. A sea ice model with multiple categories of thickness is utilized. A systematic model-data comparison was conducted. This model reasonably reproduces seasonal cycles of both the sea ice and the ocean. Climatological sea ice areas derived from historical data are used to validate the ice model performance. The simulated sea ice cover reaches a maximum of 14 × 10⁶ km² in winter and a minimum of 6.7 × 10⁶ km² in summer. This is close to the 95-year climatology with a maximum of 13.3 × 10⁶ km² in winter and a minimum of 7 × 10⁶ km² in summer. The simulated general circulation in the Arctic Ocean, the GIN (Greenland, Iceland, and Norwegian) seas, and northern North Atlantic Ocean are qualitatively consistent with historical mapping. It is found that the low winter salinity or freshwater in the Canada Basin tends to converge due to the strong anticyclonic atmospheric circulation that drives the anticyclonic ocean surface current, while low summer salinity or freshwater tends to spread inside the Arctic and exports out of the Arctic due to the relaxing wind field. It is also found that the warm, saline Atlantic Water has little seasonal variation, based on both simulation and observations. Seasonal cycles of temperature and salinity at several representative locations reveals regional features that characterize different water mass properties.     

The effects of resolving the Canadian Arctic Archipelago in a finite element sea ice model

Though narrow straits may have a strong influence on the large-scale sea ice mass balance, they are often crudely represented in coarse resolution sea ice models. Unstructured meshes, with their natural ability to fit boundaries and locally increase the mesh resolution, propose an alternative framework to capture the complex oceanic areas formed by coasts and islands. In this paper, we develop a finite element sea ice model to investigate the sensitivity of the Arctic sea ice cover features to the resolution of the narrow straits constituting the Canadian Arctic Archipelago. The model is a two-level dynamic-thermodynamic sea ice model, including a viscous-plastic rheology. It is run over 1979–2005, forced by daily NCEP/NCAR reanalysis data. Confronting qualitatively numerical experiments with observations shows a good agreement with satellite and buoys measurements. Due to its simple representation of the oceanic interactions, the model overestimates the sea ice extent during winter in the southernmost parts of the Arctic, while the Baffin Bay and Kara Sea remain ice-covered during summer. In order to isolate the benefits from resolving the Canadian Arctic Archipelago, a numerical experiment is performed where we artificially close the archipelago. Focusing on the large-scale sea ice thickness pattern, no significant change is found in our model, except in the close surroundings of the archipelago. However, the local and short-term influences of the ice exchanges are nonnegligible. In particular, we show that the ice volume associated to the Canadian Arctic Archipelago represents 10% of the Northern Hemisphere sea ice volume and that the annual mean ice export towards Baffin Bay amounts to 125 km³ yr⁻¹, which may play an important role on the convective overturning in the Labrador Sea.     

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman ?lter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.     

Evidence for multiple Quaternary ice advances and fan development from the Amundsen Gulf cross-shelf trough and slope,Canadian Beaufort Sea margin

The seismic stratigraphy and sedimentary architecture of the Amundsen Gulf Trough and adjacent slope, Canadian Beaufort Sea margin, are investigated using a grid of 2-D seismic reflection data. The inner-shelf of the Amundsen Gulf Trough is interpreted to be composed predominantly of exposed or near-surface bedrock, overlain by a spatially-discontinuous veneer of glacimarine to open-marine sediment. There is a seaward transition from exposed bedrock on the inner-shelf to a thick (up to 500 m) outer-shelf prograding wedge of acoustically semi-transparent sediment. Eight seismic sequences, divided into four megasequences, are described from the outer-shelf stratigraphy. Eight till sheets are identified from Megasequences A to C, providing evidence for at least eight Quaternary ice-stream advances through the Amundsen Gulf Trough to the shelf break. A trough-mouth fan with a minimum volume of about 10,000 km³ is present on the adjacent slope. The Amundsen Gulf ice stream probably represented the most northwesterly marine-terminating ice stream of the Laurentide Ice Sheet through much of the Quaternary, providing a major route for ice and sediment transfer to the Arctic Ocean. The youngest till sheet within the Amundsen Gulf Trough, Megasequence D, was probably deposited by a subsidiary ice stream, the Anderson ice stream, subsequent to retreat of the last, Late Wisconsinan Amundsen Gulf ice stream. This provides evidence of dynamic ice-sheet behaviour and the reorganisation of the northwest Laurentide Ice Sheet margin during the last deglaciation. A number of buried glacigenic landforms, including palaeo-shelf break gullies and a grounding-zone wedge with a volume of 90 km³, are described from the Amundsen Gulf Trough stratigraphy. Lateral grounding-zone wedges are identified at the northern and southern lateral margins of the Amundsen Gulf and M'Clure Strait troughs, respectively, and are interpreted to have been formed roughly contemporaneously by ice streams in Amundsen Gulf and M'Clure Strait.