FGOALS_gg1.1极地气候模拟

对中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室发展的气候系统模式FGOALS_g1.1的极地气候模拟现状进行了较为全面的评估.结果表明,FGOALS_g1.1对南北极海冰的主要分布特征、季节变化和年代际变化趋势具有一定的模拟能力.但也注意到,与观测相比,模式存在以下几方面的问题:(1)模拟的海冰总面积北极偏多,而南极偏少.北极,北大西洋海冰全年明显偏多;夏季,西伯利亚沿海海冰偏多,而波弗特海海冰偏少.南极,威德尔海和罗斯海冬季海冰偏少.南北极海冰边缘都存在异常的较大范围密集度很小的碎冰区,夏季尤为显著.(2)海冰流速在南北极海冰边缘和南极大陆沿岸附近较大.北极,模式没能模拟出波弗特涡流,并且由于模式网格中北极点的处理问题,造成其附近错误的海冰流场及厚度分布.这些海冰偏差与模式模拟的大气和海洋状况有着密切的联系.进一步分析表明,FGOALS_g1.1模拟的冰岛低压和南极绕极西风带明显偏弱,其通过大气环流和海表面风应力影响向极地的热量输送,在很大程度上导致上述的海冰偏差.此外,耦合模式中大气-海冰-海洋的相互作用可以放大子模式中的偏差.     

The effects of precipitation and river runoff in a coupled ice-ocean model of the Arctic

A coupled ice-ocean model of the Arctic is developed in order to study the effects of precipitation and river runoff on sea ice. A dynamic-thermodynamic sea ice model is coupled to an ocean general circulation model which includes a turbulent closure scheme for vertical mixing. The model is forced by interannually varying atmospheric temperature and pressure data from 1980–1989, and spatially varying mean monthly precipitation and river runoffs. Salinity and fresh water fluxes to the ocean from ice growth, snow melt, rain, and runoffs are computed, with no artificial constraints on the ocean salinity. The modeled ice thickness is similar to the observed pattern, with the thickest ice remaining against the Canadian Archipelago throughout the year. The modeled ice drift reproduces the Beaufort gyre and Transpolar drift exiting through Fram Strait. The stable arctic halocline produced by the vertical mixing scheme isolates the surface from the Atlantic layer and reduces the vertical fluxes of heat and salinity. A sensitivity experiment with zero precipitation results in rapidly decreasing ice thickness, in response to greater ocean heat flux from a weakening of the halocline, while an experiment with doubled precipitation results in a smaller increase in ice thickness. A zero-runoff experiment results in a slower decrease in ice thickness than the zero-precipitation case, due to the decadal time scale of the transport of runoff in the model. The results suggest that decadal trends in both arctic precipitation and river runoffs, caused either by anthropogenic or natural climatic change, have the potential to exert broad-scale impacts on the arctic sea ice regime. Received: 6 February 1996 / Accepted: 4 April 1996     

渤海海冰单点模式的气候模拟

利用PW1979海冰热力模式，考虑渤海的地理特点和气候特征，假设渤海为薄层海洋，引入二分法求解海冰表面温度。用该地区气候平均的云量、湿度、海平面气压和风速以及附近4站的月平均气温资料作为强迫场，模拟了渤海海冰的气候变化。模拟结果与逐年的海冰级数资料具有一致的变率，表明气温对海冰年际变化有重要影响。     

Mean climatic characteristics in high northern latitudes in an ocean-sea ice-atmosphere coupled model

Emphasizing the model‘s ability in mean climate reproduction in high northern latitudes, resultsfrom an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model cansimulate the main characteristics of annual mean global sea surface temperature and sea level pressurewell, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The maindistribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northernlatitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproducethe Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the NorthernHemisphere is rational and its main distribution features in winter agree well with those from observations.But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Oceanis much larger than the observation. There are significant interannual variation signals in the simulated seaice concentration in winter in high northern latitudes and the most significant area lies in the GreenlandSea, followed by the Barents Sea. All of these features agree well with the results from observations.     

北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验

利用最近发展的MITgcm(麻省理工学院通用环流模式)海冰-海洋耦合模式,以NCEP(美国国家环境预测中心)再分析资料为大气强迫场进行了1992年1月至2009年12月北极海冰数值模拟.结果表明,此模式能很好地模拟卫星观测的北极海冰季节和年际变化,具备很好的北极海冰数值模拟能力.以此为基础,对2009年7月和10月北极...     

一个海洋-海冰耦合模式的北极气候模拟

This paper evaluates the simulation of Arctic sea ice states using an ocean-ice coupled model that employs LASG/IAP(the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/the Institute of Atmospheric Physics) Climate Ocean Model(LICOM) and the sea-ice model from the Bergen Climate Model(BCM).It is shown that the coupled model can reasonably reproduce the major characteristics of the mean state,annual cycle,and interannual variability of the Arctic sea ice concentration.The coupled model also shows biases that were generally presented in other models,such as the underestimation of summer sea ice concentration and thickness as well as the unsatisfactory sea ice velocity.Sensitivity experiments indicate that the insufficient performance of the ocean model at high latitudes may be the main reason for the biases in the coupled model.The smoother and the fake "island",which had to be used due to the model’s grid in the North Pole region,likely caused the ocean model’s weak performance.Sea ice model thermodynamics are also responsible for the sea ice simulation biases.Therefore,both the thermodynamic module of the sea ice component and the model grid of the ocean component need to be further improved.     

Effect of the large-scale atmospheric circulation on the variability of the Arctic Ocean freshwater export

Freshwater (FW) leaves the Arctic Ocean through sea-ice export and the outflow of low-salinity upper ocean water. Whereas the variability of the sea-ice export is known to be mainly caused by changes in the local wind and the thickness of the exported sea ice, the mechanisms that regulate the variability of the liquid FW export are still under investigation. To better understand these mechanisms, we present an analysis of the variability of the liquid FW export from the Arctic Ocean for the period 1950–2007, using a simulation from an energy and mass conserving global ocean–sea ice model, coupled to an Energy Moisture Balance Model of the atmosphere, and forced with daily winds from the NCEP reanalysis. Our results show that the simulated liquid FW exports through the Canadian Arctic Archipelago (CAA) and the Fram Strait lag changes in the large-scale atmospheric circulation over the Arctic by 1 and 6 years, respectively. The variability of the liquid FW exports is caused by changes in the cyclonicity of the atmospheric forcing, which cause a FW redistribution in the Arctic through changes in Ekman transport in the Beaufort Gyre. This in turn causes changes in the sea surface height (SSH) and salinity upstream of the CAA and Fram Strait, which affect the velocity and salinity of the outflow. The SSH changes induced by the large-scale atmospheric circulation are found to explain a large part of the variance of the liquid FW export, while the local wind plays a much smaller role. We also show that during periods of increased liquid FW export from the Arctic, the strength of the simulated Atlantic meridional overturning circulation is reduced and the ocean heat transport into the Arctic is increased. These results are particularly relevant in the context of global warming, as climate simulations predict an increase in the liquid FW export from the Arctic during the twenty-first century.     

Simulation of sea ice in FGOALS-g2: Climatology and late 20th century changes

Sea ice is an important component in the Earth’s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean-Atmosphere-Land System model Grid-point Version 2 (FGOALS-g2), in the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), with a focus on historical experiments and late 20th century simulation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-g1.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future: (1) ocean model improvements to remove the artificial island at the North Pole; (2) higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and (3) ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.     

一个热动力海冰模式的改进与实验

影响海冰变化的物理因素中热力和动力部分是同等重要的，但多数热动力海冰模式的热力部分考虑得较为简单。针对Hibler热动力海冰模式的不足，以1个3层热力模式为基础改进了其热力部分。比较了原模式中的零层热力模式和用于改进的3层热力模式；并应用改进前后的两种热动力模式对1983年的北极海冰进行了模拟。模拟结果表明，海冰厚度比原模式厚，季节变化减弱，海冰密集度与观测资料更为符合。     

CICE海冰模式中反照率相关参数对北极海冰模拟的影响

国家气候中心气候系统模式BCC_CSM2.0最新耦合了美国Los Alamos国家实验室发展的海冰模式CICE5.0,为试验模式中与反照率相关参数的敏感性及其对模拟结果的影响,提高模式对北极海冰的模拟能力,选取海冰模式中3个主要参数进行了敏感性试验。利用以BCC_CSM2.0耦合框架为基础建立的海冰-海洋耦合模式,选取CORE资料为大气强迫场开展试验,试验的3个参数分别为冰/雪表面反射率、雪粒半径和雪粒半径参考温度。结果表明,参数取值的不同对北极海冰的模拟有显著的影响,优化后的取值组合极大提高了模式的模拟能力,主要表现在:（1）改善了对北极冬季海冰厚度的模拟,海冰厚度增大,与观测资料更为吻合;（2）显著提高了对北极夏季海冰密集度的模拟能力,从而模拟的北极海冰范围年际循环与观测更为一致。参数取值的优化改进了模式对海冰反照率的模拟,进而影响了冰面短波辐射的吸收和海冰表层的融化,最终提高了模式对海冰密集度和厚度的模拟效果。      

大气环流模式（SAMIL）海气耦合前后性能的比较

基于耦合器框架，中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室大气环流谱模式 （SAMIL）最近成功地实现了与海洋、海冰等气候分量模式的耦合，形成了“非通量调整”的海－陆－气－冰直接耦合的气候模式系统（FGOALS-s）。在耦合系统中，由于海温、海冰等的分布由预报模式驱动，大气与海洋、海冰之间引入了相互作用过程，这样大气环流的模拟特征与耦合前会有不同。为分析耦合系统的性能，作者对耦合前后的模拟结果进行了分析比较，重点是大气模拟特征的差异。结果表明，耦合前、后大气环流的基本特征相似，都能成功地模拟出主要的环流系统分布及季节变化，但是由于海温和海冰的模拟存在系统性的偏差，使得耦合后的大气环流受到明显影响。例如耦合后热带海温偏冷，南大洋、北太平洋和北大西洋等中纬度地区的海温偏高，导致海温等值线向高纬海域的伸展较弱，海温经向梯度减小。耦合后海冰在北极区域范围偏大，在南极周边地区则偏小。海温、海冰分布模拟的偏差影响到中、高纬低层大气的温度。热带海温偏低，使得赤道地区降水偏弱，凝结潜热减少，热带对流层中高层温度比耦合前要低，大气温度的经向梯度减小。经向温度梯度的改变，直接影响到对平均经圈环流及西风急流强度的模拟。尽管耦合系统中海温、海冰的模拟存在偏差，但在亚洲季风区，耦合后季风环流及降水等的分布都比耦合前单独大气模式的结果合理，表明通过海[CD*2]气相互作用可减少耦合前季风区的模拟误差，改善季风模拟效果。比较发现，海温、海冰模拟的偏差，除与海洋模式中经向热输送偏弱、海冰模式中海冰处理等有关外，也与大气模式中总云量模拟偏低有关。大气模式本身的误差，特别是云、辐射过程带来的误差，对耦合结果具有极为重要的影响。完全耦合后，这些误差通过与海洋、海冰的反馈作用而放大。因此，对于FGOALS-s而言，要提高耦合系统的整体性能，除改进各气候分量模式的模拟性能外，需要重点改进大气模式中的云、辐射过程。     

Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model

A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system sensitivity.     

Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia.     

Simulation of the Atlantic meridional overturning circulation in an atmosphere–ocean global coupled model. Part I: a mechanism governing the variability of ocean convection in a preindustrial experiment

A preindustrial climate experiment was conducted with the third version of the CNRM global atmosphere–ocean–sea ice coupled model (CNRM-CM3) for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). This experiment is used to investigate the main physical processes involved in the variability of the North Atlantic ocean convection and the induced variability of the Atlantic meridional overturning circulation (MOC). Three ocean convection sites are simulated, in the Labrador, Irminger and Greenland–Iceland–Norwegian (GIN) Seas in agreement with observations. A mechanism linking the variability of the Arctic sea ice cover and convection in the GIN Seas is highlighted. Contrary to previous suggested mechanisms, in CNRM-CM3 the latter is not modulated by the variability of freshwater export through Fram Strait. Instead, the variability of convection is mainly driven by the variability of the sea ice edge position in the Greenland Sea. In this area, the surface freshwater balance is dominated by the freshwater input due to the melting of sea ice. The ice edge position is modulated either by northwestward geostrophic current anomalies or by an intensification of northerly winds. In the model, stronger than average northerly winds force simultaneous intense convective events in the Irminger and GIN Seas. Convection interacts with the thermohaline circulation on timescales of 5–10 years, which translates into MOC anomalies propagating southward from the convection sites.     

Influence of coupling on atmosphere, sea ice and ocean regional models in the Ross Sea sector, Antarctica

Air–sea ice–ocean interactions in the Ross Sea sector form dense waters that feed the global thermohaline circulation. In this paper, we develop the new limited-area ocean–sea ice–atmosphere coupled model TANGO to simulate the Ross Sea sector. TANGO is built up by coupling the atmospheric limited-area model MAR to a regional configuration of the ocean–sea ice model NEMO. A method is then developed to identify the mechanisms by which local coupling affects the simulations. TANGO is shown to simulate realistic sea ice properties and atmospheric surface temperatures. These skills are mostly related to the skills of the stand alone atmospheric and oceanic models used to build TANGO. Nonetheless, air temperatures over ocean and winter sea ice thickness are found to be slightly improved in coupled simulations as compared to standard stand alone ones. Local atmosphere ocean feedbacks over the open ocean are found to significantly influence ocean temperature and salinity. In a stand alone ocean configuration, the dry and cold air produces an ocean cooling through sensible and latent heat loss. In a coupled configuration, the atmosphere is in turn moistened and warmed by the ocean; sensible and latent heat loss is therefore reduced as compared to the stand alone simulations. The atmosphere is found to be less sensitive to local feedbacks than the ocean. Effects of local feedbacks are increased in the coastal area because of the presence of sea ice. It is suggested that slow heat conduction within sea ice could amplify the feedbacks. These local feedbacks result in less sea ice production in polynyas in coupled mode, with a subsequent reduction in deep water formation.     

Simulation of sea ice and ocean variability in the arctic during 1955–2002 with an intermediate complexity model

Abstract

A number of recent sea‐ice and ocean changes in the Arctic and subarctic regions are simulated using the global University of Victoria (UVic) Earth System Climate Model version 2.6. This is an intermediate complexity model which includes a three‐dimensional ocean model (MOM 2.2), an energy‐moisture balance model for the atmosphere with heat and moisture transport, and a dynamic‐thermodynamic sea‐ice model with elastic‐viscous‐plastic rheology. The model is first spun up for 1800 years with monthly wind stress forcing derived from the National Centers for Environmental Prediction (NCEP) climatology winds and a pre‐industrial atmospheric CO₂ concentration of 280 ppm. After a second spin‐up for the period 1800–1947 with daily climatology winds‐tress forcing, and a linearly increasing atmospheric CO₂ concentration, the model is run with interannually varying wind stresses for the period 1948–2002 with an average forcing interval of 2.5 days and an exponentially increasing atmospheric CO₂ concentration varying from 315 to 365 ppm. However, the analysis of the model output is only carried out for the years 1955–2002.

The simulated maximum and minimum sea‐ice areas for the Arctic are within 6% of the observed climatologies for the years 1978–2001. The model output also shows a small downward trend in sea‐ice extent, which, however, is smaller than has been observed during the past few decades. In addition, the model simulates a decrease in sea‐ice thickness in the SCICEX (SCientific ICe EXpeditions) measurement area in the central Arctic that is consistent with, but smaller than, that observed from submarine sonar profiling data.

The observed variability and magnitude of the export of sea ice through Fram Strait is quite well captured in the simulation. The change in correlation between the North Atlantic Oscillation (NAO) index and the sea‐ice export around 1977 as found in a data study by Hilmer and Jung (2000) is also reproduced. Within the Arctic basin the model simulates well the patterns and the timing of the two major regimes of wind‐forced sea‐ice drift circulation (cyclonic and anticyclonic) as found earlier by Proshutinsky and Johnson (1997). The influence of variations in the Fram Strait ice export on the strength of the North Atlantic thermohaline circulation and surface air temperature are also determined. In particular, it is shown that 3–4 years after a large ice export, the maximum meridional overturning streamfunction decreases by more than 10%.

The temperature and salinity increase at depths of 200–300 m, as observed in the eastern Arctic by Morison et al. (1998), between the USS Pargo cruise in 1993 and the Environmental Working Group (EWG) Joint USRussian Arctic Atlas climatology for the years 1948–87, are just visible in the model simulation. The increases are more noticeable, however, when the ocean model data are averaged over the pentade 1995–2000 and compared with model data averaged over the pentade 1955–60. The fact that these, and some of the other modelled changes, are smaller than the observed changes can likely be attributed to the relatively coarse resolution of the UVic Earth System Climate Model (3.6°E‐W and 1.8°N‐S). Nevertheless, the fact that the model captures qualitatively many of the recent sea‐ice and ocean changes in the Arctic suggests that it can be successfully used to investigate other Arctic‐North Atlantic Ocean climate interactions during past and future eras.     

Variations of sea ice temperature from CHINARE 2003 and its application on sea ice model evaluation

Variation of vertical profiles of sea ice temperature and adjacent atmosphere and ocean temperatures were measured by ice drifting buoys deployed in the northeast Chukchi Sea as part of the 2003 Chinese Arctic Research Expedition.The buoy observations (September 2003 to February 2005) show that the cooling of the ice began in late September,propagated down through the ice,reaching the bottom of the ice in December,and continued throughout the winter.In winter 2003/04,some obvious warmings were observed in the upper portion of the ice in response to major warmings in the overlying atmosphere associated with the periodicity of storms in the northeast Chukchi Sea.It is found that the melt season at the buoy site in 2004 was about 15% longer than normal.The buoy observed vertical ice temperature profiles were used as a diagnostic for sea ice model evaluation.The results show that the simulated ice temperature profiles have large discrepancies as compared with the observations.     

Properties of adjoint sea ice sensitivities to atmospheric forcing and implications for the causes of the long term trend of Arctic sea ice

Based on adjoint sensitivities of the coupled Massachusetts Institute of Technology ocean–sea ice circulation model, the potential influence of thermodynamic atmospheric forcing on the interannual variability of the September sea ice area (AREA) and volume (VOLUME) in the Arctic is investigated for the three periods 1980–1989, 1990–1999 and 2000–2009. Sensitivities suggest that only large forcing anomalies prior to the spring melting onset in May can influence the September sea ice characteristics while even small changes in the atmospheric variables during subsequent months can significantly influence September sea ice state. Specifically, AREA close to the ice edge in the Arctic seas is highly sensitive to thermodynamic atmospheric forcing changes from June to July. In contrast, VOLUME is highly sensitive to atmospheric temperature changes occurring during the same period over the central parts of the Arctic Ocean. A comparison of the sea ice conditions and sensitivities during three different periods reveals that, due to the strong decline of sea ice concentration and sea ice thickness, sea ice area became substantially more sensitive to the same amplitude thermodynamic atmospheric forcing anomalies during 2000–2009 relative to the earlier periods. To obtain a quantitative estimate of changes that can be expected from existing atmospheric trends, adjoint sensitivities are multiplied by monthly temperature differences between 1980s and two following decades. Strongest contributions of surface atmospheric temperature differences to AREA and VOLUME changes are observed during May and September. The strongest contribution from the downward long-wave heat flux to AREA changes occurs in September and to VOLUME changes in July–August. About 62 % of the AREA decrease simulated by the model can be explained by summing all contributions to the thermodynamic atmospheric forcing. The changing sea ice state (sensitivity) is found to enhance the decline and accounts for about one third of the explained reduction. For the VOLUME decrease, the explained fraction of the decrease is only about 37 %.     

Modelling of Ocean Shallow Convection under Fast Ice in the Arctic

Ocean convection in the Antarctic has been studied many times and has been revealed to be responsible for ice-cover reduction. In the Arctic, proof of that phenomenon has not been documented. It is believed that this phenomenon happens on a smaller scale in the Arctic when local circulation of deep warmer water melts and slows ice production. An example of this is the North Water (NOW) polynya in northern Baffin Bay. A polynya is an area of open water in an otherwise ice-covered area. As ice forms under the fast ice near the boundary of the polynya, ocean salts (brine) are ejected from the newly formed ice. This water, which has an increased concentration of salt, sinks and is replaced by warmer water from below, and this slows ice formation. In our study a coupled one-dimensional thermodynamic snow–fast ice model incorporating ocean heat flux input via a shallow convection model was used. Ice thickness was calculated using a thermodynamic model that included a current-induced entrainment model and a convection model to account for brine rejection during ice growth. Atmospheric observations from Grise Fiord and Thule and ocean profiles around the NOW polynya near these sites were used as input to the model. This purely thermodynamic study enables us to obtain ice thickness values that can be compared with qualitative observations. This modelling study compares two sites related to the NOW polynya. The results indicate that the shallow convection model simulates the reduction of fast ice near Thule but not near Grise Fiord.     

Evaluation of Arctic Sea Ice Drift and its Relationship with Near-surface Wind and Ocean Current in Nine CMIP6 Models from China

The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.