Sea ice in the Barents Sea: seasonal to interannual variability and climate feedbacks in a global coupled model

Sea ice variability in the Barents Sea and its impact on climate are analyzed using a 465-year control integration of a global coupled atmosphere–ocean–sea ice model. Sensitivity simulations are performed to investigate the response to an isolated sea ice anomaly in the Barents Sea. The interannual variability of sea ice volume in the Barents Sea is mainly determined by variations in sea ice import into Barents Sea from the Central Arctic. This import is primarily driven by the local wind field. Horizontal oceanic heat transport into the Barents Sea is of minor importance for interannual sea ice variations but is important on longer time scales. Events with strong positive sea ice anomalies in the Barents Sea are due to accumulation of sea ice by enhanced sea ice imports and related NAO-like pressure conditions in the years before the event. Sea ice volume and concentration stay above normal in the Barents Sea for about 2 years after an event. This strongly increases the albedo and reduces the ocean heat release to the atmosphere. Consequently, air temperature is much colder than usual in the Barents Sea and surrounding areas. Precipitation is decreased and sea level pressure in the Barents Sea is anomalously high. The large-scale atmospheric response is limited with the main impact being a reduced pressure over Scandinavia in the year after a large ice volume occurs in the Barents Sea. Furthermore, high sea ice volume in the Barents Sea leads to increased sea ice melting and hence reduced surface salinity. Generally, the climate response is smallest in summer and largest in winter and spring.     

A Regional Ocean Reanalysis System for Coastal Waters of China and Adjacent Seas

A regional ocean reanalysis system for the coastal waters of China and adjacent seas has been developed by the National Marine Data and Information Service(NMDIS).It produces a dataset package called CORA (China ocean reanalysis).The regional ocean model used is based on the Princeton Ocean Model with a generalized coordinate system(POMgcs).The model is parallelized by NMDIS with the addition of the wave breaking and tidal mixing processes into model parameterizations.Data assimilation is a sequential three-dimensional variational(3D-Var) scheme implemented within a multigrid framework.Observations include satellite remote sensing sea surface temperature(SST),altimetry sea level anomaly(SLA),and temperature/salinity profiles.The reanalysis fields of sea surface height,temperature,salinity,and currents begin with January 1986 and are currently updated every year. Error statistics and error distributions of temperature,salinity and currents are presented as a primary evaluation of the reanalysis fields using sea level data from tidal gauges,temperature profiles,as well as the trajectories of Argo floats.Some case studies offer the opportunity to verify the evolution of certain local circulations.These evaluations show that the reanalysis data produced provide a good representation of the ocean processes and phenomena in the coastal waters of China and adjacent seas.     

The influence of the North Atlantic on climate variations in the Barents Sea and their predictability

The effects of Atlantic water inflow on the climate variability in the Barents Sea are studied. Initial data are the series of water temperature at the Kola meridian cross-section, monthly values of ice extent, air temperature at the stations, sea level pressure from the reanalysis data, and sea surface temperature. The methods of multivariate correlation, spectral, and factor analysis and EOF decomposition are used. It was found that variations in the Atlantic water inflow define the main part of interannual variability of sea ice extent, water temperature, and air temperature in the Barents Sea in the cold season. The influence of regional atmospheric circulation on the interannual variability of these parameters is small. The effects that water temperature anomalies in the area of Newfoundland and in the equatorial part of the North Atlantic have on climate parameters in the Barents Sea are discovered. The response of these parameters lags behind the respective anomalies by 9-58 months. The high correlation between them makes it possible to develop the method of statistical forecasting of sea ice extent and water temperature in the Barents Sea with the lead time up to 4 years.     

The climatic response of the Arctic Ocean to Soviet river diversions

A numerical model is constructed to evaluate the effect of river diversions on the circulation of the Arctic Ocean, including the climatically important response in the extent of sea ice. The ocean model solves the primitive equations of motion in finite-difference form for the irregular geometry of the Arctic Ocean and Greenland/Norwegian Sea, using 110 km horizontal grid spacing and up to 13 unevenly spaced levels in the vertical. Annual mean atmospheric conditions and river discharges are specified from observations. The presence of sea ice is diagnosed on the basis of model ocean temperature; and the effects of sea ice on the surface fluxes of momentum, heat, and salt are included in a simplified way. Lateral exchanges at the southernmost boundary are held near observed values but respond to circulation changes in the Greenland/Norwegian Sea. Three equilibrium solutions are obtained by eighty-year integrations from simple initial conditions: the first with inflow from all rivers, the second with one-third of the inflow diverted from four major rivers (the Ob, Yenesei, Dvina, and Pechora), and the third with total diversion from those rivers. The middle case corresponds to maximal diversions which are either planned or envisioned by the Soviet Union over the next fifty years, whereas the final extreme case is run in the event that model sensitivity is low relative to that of nature.The control integration gives a good simulation of known water masses and currents. In the Central Arctic, for example, the model correctly predicts a strong shallow halocline, a relatively warm intermediate layer of Atlantic origin, and a temperature jump across the deep Lomonosov Ridge. The overall pattern of surface salinity and the margin of the pack ice are also properly simulated.When runoff into the marginal Kara and Barents Seas is diverted, either in part or in full, almost no effect on the halocline results in the Central Arctic. In particular, deep convection does not develop in the Eurasian Basin, the possibility of which was suggested by Aagaard and Coachman (1975). The vertical stability within the two marginal seas is considerably decreased by the total diversion of four rivers, but not to the point of convective overturning. The surface currents in this area change to confine the water with increased salinity to the shelf region. At deeper levels, an increased salinity tongue spreads into the deep basins of the ice-free Greenland/Norwegian Sea, where existing deep convection is slightly enhanced. As a result, there is some additional heat loss from the Atlantic layer before it enters the Central Arctic. The ice extent remains nearly the same as before within the Kara and Barents Seas. In fact, since modified bottom currents over the continental shelf bring in less heat from the Greenland Sea, an increased thickness of sea ice may result there, in spite of reduced vertical stability. These model responses are generally in agreement with those suggested by Micklin (1981) and by Soviet investigations of the effect of river diversions. These annualmean results should be regarded as tentative, pending confirmation by studies which include the seasonal cycles of runoff and atmospheric forcing.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

BCC_CSM北极海冰模拟性能的改进对东亚冬季气候模拟的影响

国家气候中心气候系统模式(BCC_CSM)将美国Los Alamos国家实验室发展的海冰模式CICE5.0替代原有的海冰模式SIS,形成一个新版本耦合模式,很好地提高了模式对北极海冰和北极气候的模拟能力.在此基础上,本文评估新耦合模式对1985-2014年东亚冬季气候的模拟性能,检验北极海冰模拟性能的改进对东亚冬季气候...     

Possible impacts of Barents Sea ice on the Eurasian atmospheric circulation and the rainfall of East China in the beginning of summer

Possible influences of the Barents Sea ice anomalies on the Eurasian atmospheric circulation and the East China precipitation distribution in the late spring and early summer (May-June) are investigated by analyzing the observational data and the output of an atmospheric general circulation model (AGCM).The study indicates that the sea ice condition of the Barents Sea from May to July may be interrelated with the atmospheric circulation of June. When there is more than average sea ice in the Barents Sea, the local geopotential height of the 500-hPa level will decrease, and the same height in the Lake Baikal and Okhotsk regions will increase and decrease respectively to form a wave-chain structure over North Eurasia.This kind of anomalous height pattern is beneficial to more precipitation in the south part of East China and less in the north.     

Climatic variations of ice conditions in different regions of the Barents Sea

Presented are the results of studying the regional peculiarities of climatic variations of spatiotemporal distribution of ice in the Barents Sea water area in 1977?C2010. Demonstrated is the dynamics of the interannual and seasonal variability of main elements of the ice regime (ice cover area, ice edge position, and ice period duration). Revealed are the common features and differences in the ice conditions in the water areas under study. It has been found that there is a significant feedback between the specific ice coverage in different areas of the sea. The climatic variations of the total ice coverage of the Barents Sea for the period of 1960?C2010 are analyzed using the electronic database on the Barents Sea ice coverage. It can be supposed that the current warm phase of climatic variations in the Barents Sea is coming to the end.     

BCC_CSM对全球海冰面积和厚度模拟及其误差成因分析

本文评估了国家气候中心发展的BCC_CSM模式对全球海冰的模拟能力,结果表明:该气候系统模式能够较好地模拟出全球海冰面积和厚度的时空分布特征,且南半球海冰模拟能力优于北半球。通过对比分析发现:年平均海冰面积模拟误差最大的区域位于鄂霍次克海、白令海和巴伦支海等海区,年平均海冰厚度分布与观测相近,在北半球冬季模拟的厚度偏薄;从海冰季节变化来看,模拟的夏季海冰面积偏低,冬季偏高;从海冰年际变化来看,近60年南北半球海冰面积模拟都比观测偏多,但南半球偏多幅度较小,然而北半球海冰年际变化趋势的模拟却好于南半球。另外,通过对海冰模拟误差成因分析,发现模拟的净辐射能量收入偏低使得海温异常偏冷,是导致北半球冬季海冰模拟偏多的主要原因。     

Model simulation of the currents in the Barents Sea in connection with the development of the Shtokman gas condensate field

A three-dimensional nonstationary baroclinic model of the Barents Sea is under consideration. The simulation was performed with allowance for all basic factors influencing the current: wind, pressure, tides, inhomogeneous water density, and flows across the open boundaries. Stationary and nonstationary sea dynamics has been simulated. It is found that an instantaneous flow pattern is highly variable and does not coincide with the schemes of a general drift. The main contribution to variability is made by tidal oscillations. Periodically, the tide and wind form vortex structures in different parts of the Barents Sea. The model is developed and used for getting data on currents on open boundaries of local models of different sea sites for calculating the transport of suspended substances when laying the subwater gas pipeline from the Shtokman gas condensate field to Kola Peninsula. A brief review of measurement data and results of model simulation of the currents in the Barents Sea is prepared.     

Is There a Link between Arctic Sea Ice Loss and Increasing Frequency of Extremely Cold Winters in Eurasia and North America? Synthesis of Current Research

Studies dealing with impact of the Arctic warming and related sea ice decline on the Northern Hemisphere atmospheric circulation are considered. The causes of occurrence of extremely cold winters over the mid-latitude continents observed in the recent decades against the warming background are discussed. Several conceptions are outlined which explain potential reasons for occurrence of this phenomenon. The paper discusses impacts of the Arctic sea ice loss on the large-scale atmospheric circulation, oscillations of planetary waves. It also discusses issues related to sea ice changes in the Barents and Kara seas and their link to the frequency of extremely cold winters observed in Eurasia and North America, the contribution of internal atmospheric variability to the increasing frequency of cold weather, and the role of the Atlantic Multidecadal Oscillation in the Arctic sea ice reduction.     

Modeled winter sea ice variability and the North Atlantic Oscillation: a multi-century perspective

The relationship between winter sea ice variability and the North Atlantic Oscillation (NAO) is examined for the time period 1860–2300. This study uses model output to extend recently reported observational results to multi-century time scales. Nine ensemble members are used in two Global Climate Models with forcing evolving from pre-industrial conditions through the so-called A1B scenario in which carbon dioxide stabilizes at 720 ppm by 2100. Throughout, the NAO generates an east-west dipole pattern of sea ice concentration (SIC) anomalies with oppositely signed centers of action over the Labrador and Barents Seas. During the positive polarity of the NAO, SIC increases over the Labrador Sea due to wind-driven equatorward advection of ice, and SIC decreases over the Barents Sea due to wind-driven poleward transport of heat within the mixed layer of the ocean. Although this NAO-driven SIC variability pattern can always be detected, it accounts for a markedly varying fraction of the total sea ice variability depending on the strength of the forced sea ice extent trend. For the first half of the 20th century or 1990 control conditions, the NAO-driven SIC pattern accounts for almost a third of the total SIC variance. In the context of the long term winter sea ice retreat from 1860 to 2300, the NAO-driven SIC pattern is robustly observable, but accounts for only 2% of the total SIC variance. The NAO-driven SIC dipole retreats poleward with the retreating marginal ice zone, and its Barents Sea center of action weakens. Results presented here underscore the idea that the NAO’s influence on Arctic climate is robustly observable, but time dependent in its form and statistical importance.     

冬季北半球大气对秋冬季巴伦支海海冰异常的敏感性研究

基于ERA-Interim再分析资料,借助大气模式CAM4,分析了北半球冬季不同月份的平均大气对巴伦支海不同振幅及不同季节海冰扰动的敏感性,并考察了中高纬度典型大气模态的分布变化情况.结果表明,冬季巴伦支海海冰的减少,会导致湍流热通量异常向上、局地异常变暖及水汽含量的异常升高,且相关异常的强度和范围随着海冰减少幅度的减...     

Arctic climate change in 21st century CMIP5 simulations with EC-Earth

The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.     

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.     

全球变暖背景下北极海冰与东亚冬季风关系的变化及其机制

为了进一步了解全球变暖背景下北极海冰与东亚冬季风的关系及其变化,本文选用东亚冬季风北模态及南模态作为东亚冬季风指数,利用滑动相关分析、回归分析及合成分析研究了全球变暖背景下1953—2021年北极海冰密集度与东亚冬季风关系的变化特征及其机制。结果表明:11月巴伦支海海冰密集度与东亚冬季风北模态之间的关系发生了显著变化,从1962—1977年显著正相关转为1983—1999年显著负相关,2000年以后两者无显著关系。1962—1977年11月巴伦支海海冰偏多对应东亚冬季风偏强,这是大气环流影响海冰的结果,11月的大气环流异常特征维持到了冬季,使得欧亚大陆上空大气呈现出北极涛动(Arctic Oscillation,AO)负位相,在增强东亚冬季风的同时将中高纬大陆干冷空气输送至巴伦支海,在表面风应力的作用下巴伦支海海冰增多。1983—1999年则由前一时期的大气环流影响海冰变为海冰影响大气环流,11月巴伦支海海冰显著减少在冬季激发出了北极涛动负位相,加强东亚大槽及东亚高空西风急流,从而使得东亚冬季风偏强。2000年以后北极海冰与东亚冬季风北模态的关系明显减弱,此时东亚冬季风与北极涛动的负相关关系更为显著。     

Impact of climatic change on the biological production in the Barents Sea

The Barents Sea is a high latitude ecosystem and is an important nursery and feeding area for commercial fish stocks such as cod, capelin and herring. There is a large inter-annual variability both in physical and biological conditions in the Barents Sea. Understanding and predicting changes in the system requires insight into the coupled nature of the physical and biological interactions. A coupled physical and biological ocean model is used to study the impact of postulated future atmospheric changes on the physical and biological conditions in the Barents Sea. Results from this simulation not only show that there is a large variability in the physical conditions on a wide range of time scales, but also that the temperature in the Barents Sea is increasing. The corresponding ice cover decrease is most noticeable in the summer months. The changes in physical properties will most likely have an impact on the biotope. On average, the primary production increases slightly over a 65 year long period, about 8%, partly due to an increased production in the northern Barents Sea. The model further simulates that the production of Atlantic zooplankton species increases approximately 20% and becomes more abundant in the east. The Arctic zooplankton biomass decreases significantly (50%) causing the total simulated production to decrease.     

Statistical Characteristics and Modeling of Storm Surges in the North Caspian Sea

The characteristics of storm surges obtained from sea level observations at four hydrometeorological stations in the North Caspian Sea for 2003–2017 are presented. The sea level that by 30 cm exceeds the monthly mean value at the analyzed point of the Caspian Sea was considered as a surge. In total, 370 surges were registered, 83% of them occurred during the cold season (September-April). The maximum surge height was 125 cm, the longest duration was 7 days. The most significant surges on Tyulenii Island were simulated with the operational hydrodynamic model of the sea level and currents of the Caspian Sea using atmospheric forcing from the COSMO model. The mean coefficient of correlation between the simulated and observed sea level is equal to 0.94.     

One-dimensional thermodynamic model of hummock evolution

The one-dimensional thermodynamic model of evolution of hummock formation described. The relative speeds of freezing and melting of a hummock were calculated in the framework of the suggested model. Comparisons of model results with the analogous characteristics of flat sea ice were carried out. It is found that the results obtained agree well with data of field investigations in the Barents Sea.     

A simulation of sea‐ice motion and distribution off Newfoundland during LIMEX,March 1987

Abstract

A coupled ice‐ocean dynamical model is applied to the simulation of sea‐ice motion and distribution off Newfoundland during the Labrador Ice Margin Experiment (LIMEX), March 1987. In the model, the ice is coupled to a barotropic ocean through an Ekman layer that deepens with increasing wind speed. A 6‐hourly gridded wind dataset was used as input to drive the ice and the ocean. The results show that ice velocities with ice‐ocean coupling are appreciably higher than those without coupling because of the generation of wind‐driven coastal currents. This suggests that coupled ice‐ocean dynamics should always be considered in short‐term sea‐ice models. The model gives reasonable agreement with the observed ice edge except in the southern boundary where ice‐melt has a strong influence on the ice‐edge position. Ocean currents, sea level and ice velocities computed from the model are in qualitative agreement with limited current‐meter, tide‐gauge, and ice drifter trajectory data.