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。     

Thickness sensitivities in the CICE sea ice model

Passive microwave satellite observations of ice extent and concentration form the foundation of sea ice model evaluations, due to their wide spatial coverage and decades-long availability. Observations related to other model quantities are somewhat more limited but increasing as interest in high-latitude processes intensifies. Sea ice thickness, long judged a critical quantity in the physical system, is now being scrutinized more closely in sea ice model simulations as more expansive measurements become available. While albedo is often the first parameter chosen by modelers to adjust simulated ice thickness, this paper explores a set of less prominent parameters to which thickness is also quite sensitive. These include parameters associated with sea ice conductivity, mechanical redistribution, oceanic heat flux, and ice–ocean dynamic stress, in addition to shortwave radiation. Multiple combinations of parameter values can produce the same mean ice thickness using the Los Alamos Sea Ice Model, CICE. One of these “tuned” simulations is compared with a variety of observational data sets in both hemispheres. While deformed ice area compares well with the limited observations available for ridged ice, thickness measurements differ such that the model cannot agree with all of them simultaneously. Albedo and ice–ocean dynamic parameters that affect the turning of the ice relative to the ocean currents have the largest effect on ice thickness, of the parameters tested here. That is, sea ice thickness is highly sensitive to changes in external forcing by the atmosphere or ocean, and therefore serves as a sensitive diagnostic for high-latitude change.     

Polynyas in a high‐resolution dynamic–thermodynamic sea ice model and their parameterization using flux models

This paper presents an analysis of the solutions for a steady state latent heat polynya generated by an applied wind stress acting over a semi‐enclosed channel using: (a) a dynamic–thermodynamic sea ice model, and (b) a steady state flux model. We examine what processes in the sea ice model are responsible for the maintenance of the polynya and how sensitive the results are to the choice of rheological parameters. We find that when the ice is driven onshore by an applied wind stress, a consolidated ice pack forms downwind of a zone of strong convergence in the ice velocities. The build‐up of internal stresses within the consolidated ice pack becomes a crucial factor in the formation of this zone and results in a distinct polynya edge. Furthermore, within the ice pack the across‐channel ice velocity varies with the across‐channel distance. It is demonstrated that provided this velocity is well represented, the steady state polynya flux model solutions are in close agreement with those of the sea ice model. Experiments with the sea ice model also show that the polynya shape and area are insensitive to (a) the sea ice rheology; (b) the imposition of either free‐ slip or no‐slip boundary conditions. These findings are used in the development of a simplified model of the consolidated ice pack dynamics, the output of which is then compared with the sea ice model results. Finally, we discuss the relevance of this study for the modelling of the North Water Polynya in northern Baffin Bay.     

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.     

Numerical simulation for dynamical processes of sea ice

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Halocarbons associated with Arctic sea ice

Short-lived halocarbons were measured in Arctic sea–ice brine, seawater and air above the Greenland and Norwegian seas (~81°N, 2–5°E) in mid-summer, from a melting ice floe at the edge of the ice pack. In the ice floe, concentrations of C₂H₅I, 2-C₃H₇I and CH₂Br₂ showed significant enhancement in the sea ice brine, of average factors of 1.7, 1.4 and 2.5 times respectively, compared to the water underneath and after normalising to brine volume. Concentrations of mono-iodocarbons in air are the highest ever reported, and our calculations suggest increased fluxes of halocarbons to the atmosphere may result from their sea–ice enhancement. Some halocarbons were also measured in ice of the sub-Arctic in Hudson Bay (~55°N, 77°W) in early spring, ice that was thicker, colder and less porous than the Arctic ice in summer, and in which the halocarbons were concentrated to values over 10 times larger than in the Arctic ice when normalised to brine volume. Concentrations in the Arctic ice were similar to those in Antarctic sea ice that was similarly warm and porous. As climate warms and Arctic sea ice becomes more like that of the Antarctic, our results lead us to expect the production of iodocarbons and so of reactive iodine gases to increase.     

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.     

引入拖曳系数参数化的海冰自由漂流模拟研究

Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient(C_a) and oceanic drag coefficient(C_w).Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions.In the present study,the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model,and the wind factor α and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of C_a to C_w are studied to investigate their dependence on the impact factors such as local drag coefficients,floe and ridge geometry.The results reveal that in an idealized steady ocean,C_a/C_w increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone,while it remains at a steady level(0.2-0.25) for large floes in the central ice zone.The wind factor α increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%.And the deflection angle θ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than20%without a steady level like α.The values of these parameters agree well with the previously reported observations in Arctic.The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient(C_s' /C_s) and the ratio of ridge form drag coefficient(C_r'/C_r) to the value of C_a/C_w,α,and θ,because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces.Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.     

An elastic–viscous–plastic sea ice model formulated on Arakawa B and C grids

The elastic–viscous–plastic (EVP) sea ice rheology has been introduced in the large-scale Louvain-la-Neuve sea-Ice Model, version 2 (LIM2), and its performance has been evaluated. Centred difference versions of the rheology have been implemented on both an Arakawa B grid and a C grid, and their performance have been intercompared in coupled simulations with the Nucleus for European Modelling of the Ocean (NEMO) model. Integrations with both implementations lead to fairly similar results which compare well with observations and with previous LIM simulations. The C grid version, however, offers a number of advantages: (a) easier ice coupling with NEMO, which is itself defined on a C grid; (b) possibility of representing ice transport across one-cell-wide straits and passages; (c) better representation of inertial-plastic compressive waves. For these reasons, we recommend the use of the C grid EVP formulation of the ice dynamics in future LIM applications.     

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.     

利用探地雷达(GPR)观测加拿大北极群岛和陆架区海冰厚度空间分布特征

Ground Penetrating Radar(GPR) measurements of sea ice thickness including undeformed ice and ridged ice were carried out in the central north Canadian Archipelago in spring 2010. Results have shown a significant spatial heterogeneity of sea ice thickness across the shelf. The undeformed multi-year fast ice of(2.05±0.09) m thick was investigated southern inshore zone of Borden island located at middle of the observational section,which was the observed maximum thickness in the field work. The less thick sea ice was sampled across a flaw lead with the thicknesses of(1.05±0.11) m for the pack ice and(1.24±0.13) m for the fast ice. At the northernmost spot of the section, the undeformed multi-year pack ice was(1.54±0.22) m thick with a ridged ice of 2.5 to 3 m,comparing to the multi-year fast ice with the thickness of(1.67±0.16) m at the southernmost station in the Prince Gustaf Adolf Sea.     

Atmospheric drag coefficients over sea ice — validation of a parameterisation concept

The concept of drag partitioning to parameterise the surface roughness of sea ice is validated using topography data of regions with high sea ice concentrations. The parameterised drag is compared to measurements obtained by aircraft and ship. The form drag can well be expressed as a function of mean ridge heights and spacings averaged over flight legs of 12 km, if an improved approximation for the coefficient of resistance of a single ridge is used. We find a good agreement between the parameterised and observed drag coefficients. The highest sea ice roughness was encountered close to coastal regions and the lowest in the central Arctic.     

海冰动力过程的改进离散元模型及在渤海的应用

海冰的断裂、重叠和堆积等离散分布特性广泛地存在于极区和副极区的不同海域,并对海冰的生消、运移过程有着重要影响。针对海冰在不同尺度下的离散分布特点,发展海冰动力过程的离散元方法有助于完善海冰数值模式,提高海冰数值模拟的计算精度。为此,本文针对海冰生消运移过程中的非连续分布和形变特性,发展了适用于海冰动力过程的改进离散元模型(MDEM)。不同于传统离散元方法,该模型将海冰离散为具有一定厚度、尺寸和密集度的圆盘单元。海冰单元设为诸多浮冰块的集合体,其在运移和相互接触碰撞过程中,依照质量守恒发生单元尺寸、密集度和厚度的相应变化。基于海冰离散性和流变性的特点,该模型采用黏弹性接触本构模型计算单元间的作用力,并依据Mohr-Coulomb准则计算海冰法向作用下的塑性变形及切向摩擦力。为验证该模型的可靠性,本文对海冰在规则水域内的运移和堆积过程进行了分析,离散元计算结果与解析值相一致;此外,对旋转风场下海冰漂移规律的模拟进一步验证了本文方法的精确性。在此基础上,对渤海辽东湾的海冰动力过程进行了48h数值分析,计算结果与卫星遥感资料和油气作业区的海冰现场监测数据吻合良好。在下一步工作中将考虑海冰离散元模拟中的热力因素影响,发展具有冻结、断裂效应的海冰离散元模型,更精确地模拟海冰动力-热力耦合作用下的生消和运移过程。     

两种盐度参数化方案在海冰模式中的应用比较

本文详细介绍了SIS海冰模式中引进两种盐度参数化方案即等盐度方案和盐度廓线方案对海冰模拟所存在的差异。利用盐度廓线方案导出的表征盐度与海冰温度间关系的方程比等盐度方案多出一项,将定义为盐度差异项。盐度差异项对海冰厚度的热力作用表现为：在海冰厚度增长季节（11月到次年5月）,盐度差异项通过升高海冰内部温度,抑制海冰增长;在消融的第一阶段（6．8月）,盐度差异项通过升高海冰内部温度加快海冰消融;在消融的第二阶段（9．10月）,盐度差异项通过降低海冰内部的温度抑制海冰消融。但尺度分析表明,盐度差异项要比方程中队海冰温度作用最大项小1．2个量级,如果采用一级近似,可以略去盐度差异项,因此盐度差异项对海冰增长和消融影响很小。同时利用冰洋耦合模式（ModularOceanModel,MOM4）,分别采用两种盐度参数化方案模拟北极海冰厚度和海冰密集度的季节性变化,模拟结果也表明两种方案模拟得到的海冰厚度和海冰密集度的季节性变化相差甚小。     

南极海冰变化及其气候效应研究述评

南极海冰是全球气候系统的重要组成部分。不同于北极海冰的快速减少,近40年来,南极海冰范围在2014年前是缓慢增加、后是突变减少。单一的大尺度大气环流因素无法解释南极海冰的长期变化趋势,海洋?大气相互作用对海冰的耦合影响还未得到充分研究。受南极海冰厚度遥感观测和数值模拟能力所限,现有数据仍无法准确量化全球变化背景下南极海冰的厚度和体积变化;目前南极海冰变化的气候效应还未充分明确。当前国内外对南极海冰研究的不足迫切要求发展长期可靠的南极海冰厚度数据,以突破南极海冰体积变化研究的难题,同时应综合考虑多气候模态和海气系统耦合的作用,研究南极海冰变化的机制及其气候效应。     

Dimethylsulphide and dimethylsulphoniopropionate in Antarctic sea ice and their release during sea ice melting

This study presents concentrations of dimethylsulphide (DMS) and its precursor compound dimethylsulphoniopropionate (DMSP) in a variety of sea ice and seawater habitats in the Antarctic Sea Ice Zone (ASIZ) during spring and summer. Sixty-two sea ice cores of pack and fast ice were collected from twenty-seven sites across an area of the eastern ASIZ (64°E to 110°E; and the Antarctic coastline north to 62°S). Concentrations of DMS in 81 sections of sea ice ranged from < 0.3 to 75 nM, with an average of 12 nM. DMSP in 60 whole sea ice cores ranged from 25 to 796 nM and showed a negative relationship with ice thickness (y = 125x^− 0.8). Extremely high DMSP concentrations were found in 2 cores of rafted sea ice (2910 and 1110 nM). The relationship of DMSP with ice thickness (excluding rafted ice) suggests that the release of large amounts of DMSP during sea ice melting may occur in discrete areas defined by ice thickness distribution, and may produce ‘hot spots’ of elevated seawater DMS concentration of the order of 100 nM. During early summer across a 500 km transect through melting pack ice, elevated DMS concentrations (range 21–37 nM, mean 31 nM, n = 15) were found in surface seawater. This band of elevated DMS concentration appeared to have been associated with the release of sea ice DMS and DMSP rather than in situ production by an ice edge algal bloom, as chlorophyll a concentrations were relatively low (0.09–0.42 μg l^− 1). During fast ice melting in the area of Davis station, Prydz Bay, sea ice DMSP was released mostly as extracellular DMSP, since intracellular DMSP was negligible in both hyposaline brine (5 ppt) and in a melt water lens (4–5 ppt), while extracellular DMSP concentrations were as high as 149 and 54 nM, respectively in these habitats. DMS in a melt water lens was relatively high at 11 nM. During the ice-free summer in the coastal Davis area, DMS concentrations in surface seawater were highest immediately following breakout of the fast ice cover in late December (range 5–14 nM), and then remained at relatively low concentrations through to late February (< 0.3–6 nM). These measurements support the view that the melting of Antarctic sea ice produces elevated seawater DMS due to release of sea ice DMS and DMSP.     

On the future navigability of Arctic sea routes: High-resolution projections of the Arctic Ocean and sea ice

The rapid Arctic summer sea ice reduction in the last decade has lead to debates in the maritime industries on the possibility of an increase in cargo transportation in the region. Average sailing times on the North Sea Route along the Siberian Coast have fallen from 20 days in the 1990s to 11 days in 2012–2013, attributed to easing sea ice conditions along the Siberian coast. However, the economic risk of exploiting the Arctic shipping routes is substantial. Here a detailed high-resolution projection of ocean and sea ice to the end of the 21st century forced with the RCP8.5 IPCC emission scenario is used to examine navigability of the Arctic sea routes. In summer, opening of large areas of the Arctic Ocean previously covered by pack ice to the wind and surface waves leads to Arctic pack ice cover evolving into the Marginal Ice Zone. The emerging state of the Arctic Ocean features more fragmented thinner sea ice, stronger winds, ocean currents and waves. By the mid 21st century, summer season sailing times along the route via the North Pole are estimated to be 13–17 days, which could make this route as fast as the North Sea Route.     

夏季北极密集冰区范围确定及其时空变化研究

研究夏季北极密集冰区的范围变化是了解北极海冰融化过程的重要手段。密集冰区与海冰边缘区之间没有明确的分界线, 海冰密集度在两者之间平滑过渡, 确定密集冰区范围就需确定一个密集度阈值。文中依据分辨率为6.25 km的AMSR-E遥感数据, 发现不同密集度阈值所围范围在密集冰区边缘处的减小存在由快变慢的过程, 同时与周围格点的密集度差异变化在该处最为显著, 对这两个特征进行统计分析, 获得的阈值同为89%, 具有明确的物理意义和合理性。以此为基础, 运用腐蚀算法剔除海冰边缘区, 同时结合连通域法排除小范围密集冰的影响, 进而确定密集冰区的范围。结果表明, 2002-2006年密集冰区覆盖范围较大, 年际变化较小, 2007年以后明显减小, 2010年与2011年相继出现最小值, 其中2011年的范围最小值仅为2006年的64%。密集冰区范围的变化不同于海冰覆盖范围, 是具有独立特性的海冰变化参数, 反映出高密集度海冰区域的变化特征。海冰的融化与海冰边缘区的变化是导致密集冰区范围发生变化的两个主要因素, 受动力学因素的影响, 海冰边缘区发生伸展或收缩, 发生密集冰区与海冰边缘区互相转化。本文提出了一种研究北极海冰变化的新思路, 密集冰区覆盖范围的减小表明北极中央区域高密集度海冰正持续减少。     

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.     

Improvement of short-term sea ice forecast in the southern Okhotsk Sea

In this study, a numerical model of 7-day forecast of sea ice produced by the Japan Meteorological Agency was improved by the following approaches. First, a new ice dynamic model was introduced: the distributed mass/discrete floe model. The model takes account of discrete characteristics of ice floes and well simulates the ice edge location at low computational cost. Secondly, the grid size was reduced to 5 × 5 km for the future high resolution forecasts. Next, the sea surface current data was examined because it significantly influences sea ice movement. We applied two new datasets of HINO and Okhotsk Ocean General Circulation Model (Okhotsk OGCM), which are estimated by numerical simulations, for the 7-day forecast of sea ice. Ice southward speed in January and the whorl formations in February and March were well reproduced with Okhotsk OGCM datasets. Finally, the ocean heat flux at the ice-ocean interface was refined. As a result, we achieved an ice edge error reduction from 30.8 km to 23.5 km.