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     

Melt Pond Scheme Parameter Estimation Using an Adjoint Model

Melt ponds significantly affect Arctic sea ice thermodynamic processes. The melt pond parameterization scheme in the Los Alamos sea ice model(CICE6.0) can predict the volume, area fraction(the ratio between melt pond area to sea ice area in a model grid), and depth of melt ponds. However, this scheme has some uncertain parameters that affect melt pond simulations. These parameters could be determined through a conventional parameter estimation method, which requires a large number of sensitivity simulations. The adjoint model can calculate the parameter sensitivity efficiently. In the present research, an adjoint model was developed for the CESM(Community Earth System Model) melt pond scheme. A melt pond parameter estimation algorithm was then developed based on the CICE6.0 sea ice model, melt pond adjoint model,and L-BFGS(Limited-memory Broyden-Fletcher-Goldfard-Shanno) minimization algorithm. The parameter estimation algorithm was verified under idealized conditions. By using MODIS(Moderate Resolution Imaging Spectroradiometer)melt pond fraction observation as a constraint and the developed parameter estimation algorithm, the melt pond aspect ratio parameter in CESM scheme, which is defined as the ratio between pond depth and pond area fraction, was estimated every eight days during summertime for two different regions in the Arctic. One region was covered by multi-year ice(MYI) and the other by first-year ice(FYI). The estimated parameter was then used in simulations and the results show that:(1) the estimated parameter varies over time and is quite different for MYI and FYI;(2) the estimated parameter improved the simulation of the melt pond fraction.     

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.     

Polar WRF模式海冰密集度方案对北极海雾模拟效果的个例研究

全球变暖的背景下,北极航线的常规通航甚至商业运营有望实现,而海雾会严重影响航道上船只的航行安全。海冰的存在使海气之间相互作用变得更为复杂,是研究北极海雾不可忽略的因素。船载观测发现,与中纬度常见平流冷却雾形成时气温下降速度往往超过海水降温速度不同,北极海雾发生时海冰的存在还会使海水降温速度超过空气降温速度。然而目前海冰分布是否会影响模式模拟海雾的准确性还不得而知,因此本文利用Polar WRF（Polar Weather Research and Forecasting）模式模拟了中国第七次北极考察中观测到的一次海雾过程,并进行海冰密集度敏感性试验。通过与船载观测和欧洲中期天气预报中心再分析数据比对发现,在低浮冰区内（海冰密集度小于50%）考虑海冰分布时可以更加准确地刻画潜热通量与水汽通量,模拟出与观测事实相符的表层空气降温与增湿过程以及相对湿度的变化,因此能够更好地刻画海雾的三维结构及其生消演变。     

Ocean heat transport into the Arctic in the twentieth and twenty-first century in EC-Earth

The ocean heat transport into the Arctic and the heat budget of the Barents Sea are analyzed in an ensemble of historical and future climate simulations performed with the global coupled climate model EC-Earth. The zonally integrated northward heat flux in the ocean at 70°N is strongly enhanced and compensates for a reduction of its atmospheric counterpart in the twenty first century. Although an increase in the northward heat transport occurs through all of Fram Strait, Canadian Archipelago, Bering Strait and Barents Sea Opening, it is the latter which dominates the increase in ocean heat transport into the Arctic. Increased temperature of the northward transported Atlantic water masses are the main reason for the enhancement of the ocean heat transport. The natural variability in the heat transport into the Barents Sea is caused to the same extent by variations in temperature and volume transport. Large ocean heat transports lead to reduced ice and higher atmospheric temperature in the Barents Sea area and are related to the positive phase of the North Atlantic Oscillation. The net ocean heat transport into the Barents Sea grows until about year 2050. Thereafter, both heat and volume fluxes out of the Barents Sea through the section between Franz Josef Land and Novaya Zemlya are strongly enhanced and compensate for all further increase in the inflow through the Barents Sea Opening. Most of the heat transported by the ocean into the Barents Sea is passed to the atmosphere and contributes to warming of the atmosphere and Arctic temperature amplification. Latent and sensible heat fluxes are enhanced. Net surface long-wave and solar radiation are enhanced upward and downward, respectively and are almost compensating each other. We find that the changes in the surface heat fluxes are mainly caused by the vanishing sea ice in the twenty first century. The increasing ocean heat transport leads to enhanced bottom ice melt and to an extension of the area with bottom ice melt further northward. However, no indication for a substantial impact of the increased heat transport on ice melt in the Central Arctic is found. Most of the heat that is not passed to the atmosphere in the Barents Sea is stored in the Arctic intermediate layer of Atlantic water, which is increasingly pronounced in the twenty first century.     

Ocean Response to a Climate Change Heat-Flux Perturbation in an Ocean Model and Its Corresponding Coupled Model

State-of-the-art coupled general circulation models(CGCMs)are used to predict ocean heat uptake(OHU)and sealevel change under global warming.However,the projections of different models vary,resulting in high uncertainty.Much of the inter-model spread is driven by responses to surface heat perturbations.This study mainly focuses on the response of the ocean to a surface heat flux perturbation F,as prescribed by the Flux-Anomaly-Forced Model Intercomparison Project(FAFMIP).The results of ocean model were compared with those of a CGCM with the same ocean component.On the global scale,the changes in global mean temperature,ocean heat content(OHC),and steric sea level(SSL)simulated in the OGCM are generally consistent with CGCM simulations.Differences in changes in ocean temperature,OHC,and SSL between the two models primarily occur in the Arctic and Atlantic Oceans(AA)and the Southern Ocean(SO)basins.In addition to the differences in surface heat flux anomalies between the two models,differences in heat exchange between basins also play an important role in the inconsistencies in ocean climate changes in the AA and SO basins.These discrepancies are largely due to both the larger initial value and the greater weakening change of the Atlantic meridional overturning circulation(AMOC)in CGCM.The greater weakening of the AMOC in the CGCM is associated with the atmosphere–ocean feedback and the lack of a restoring salinity boundary condition.Furthermore,differences in surface salinity boundary conditions between the two models contribute to discrepancies in SSL changes.     

Influence of Atlantic Water on the Sea Ice Cover in the Western Arctic in Winter

The results of temperature and salinity measurements in the upper 1000-mlayer of the Nansen Basin in the Arctic Ocean made from the North Pole-35 drifting station in winter of 2007/2008 are analyzed. The uniqueness of the dataset processed is defined by the station drift path in the Nansen Basin and by the time of the drift which immediately followed the record decline of Arctic sea ice in September 2007. It is found that the maximum heat flux from the ocean to the ice cover equal to more than 90 W/m² was observed in the area of Atlantic water in flow between Spitsbergen and Franz Josef Land. It was caused by the drift velocity increase and by the corresponding deepening of the Ekman boundary layer. No significant changes (as compared to climate normals) in the influence of ocean heat on the ice cover in the eastern Nansen Basin in winter were registered.     

Arctic Climate Changes Based on Historical Simulations (1900‒2013) with the CAMS-CSM

The Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) is a newly developed global climate model that will participate in the Coupled Model Intercomparison Project phase 6. Based on historical simulations (1900?2013), we evaluate the model performance in simulating the observed characteristics of the Arctic climate system, which includes air temperature, precipitation, the Arctic Oscillation (AO), ocean temperature/salinity, the Atlantic meridional overturning circulation (AMOC), snow cover, and sea ice. The model?data comparisons indicate that the CAMS-CSM reproduces spatial patterns of climatological mean air temperature over the Arctic (60°?90°N) and a rapid warming trend from 1979 to 2013. However, the warming trend is overestimated south of the Arctic Circle, implying a subdued Arctic amplification. The distribution of climatological precipitation in the Arctic is broadly captured in the model, whereas it shows limited skills in depicting the overall increasing trend. The AO can be reproduced by the CAMS-CSM in terms of reasonable patterns and variability. Regarding the ocean simulation, the model underestimates the AMOC and zonally averaged ocean temperatures and salinity above a depth of 500 m, and it fails to reproduce the observed increasing trend in the upper ocean heat content in the Arctic. The large-scale distribution of the snow cover extent (SCE) in the Northern Hemisphere and the overall decreasing trend in the spring SCE are captured by the CAMS-CSM, while the biased magnitudes exist. Due to the underestimation of the AMOC and the poor quantification of air–sea interaction, the CAMS-CSM overestimates regional sea ice and underestimates the observed decreasing trend in Arctic sea–ice area in September. Overall, the CAMS-CSM reproduces a climatological distribution of the Arctic climate system and general trends from 1979 to 2013 compared with the observations, but it shows limited skills in modeling local trends and interannual variability.     

Pre-Melt Energy Budget of an Arctic Snowpack on Landfast First-Year Sea Ice

The pre-melt energy budget of a snowpack on landfast first-year sea ice at a remote site in the Canadian Arctic Archipelago was analyzed. Over a 19-day period, the total heat conducted into the snowpack at the snow–sea-ice interface was the largest single energy transfer to the snowpack, while each of the turbulent heat fluxes removed comparable amounts of energy. The total energy transferred from the snowpack (∑Q?≈??7027?kJ?m^?2) should have reduced its temperature; however, the opposite occurred. The snowpack’s temperature at both the 7 and 13?cm depths increased over the pre-melt period. The total change in internal energy and latent heat of the snowpack (ΔU_snowpack)_, derived from 15-minute changes in the snowpack’s temperature over the pre-melt period, was approximately 672?kJ?m^?2. Closure of the energy budget was not achieved for either the daily or the total pre-melt period. The terms of the energy budget were determined independently; thus, the failure to close the energy budget was the result of the accumulation of errors associated with all the terms. However, for snow on first-year sea ice, the parameterization of the salinity and temperature dependence of the “specific heat” of the basal layer of the snowpack was likely the primary source of error. The snowpack plays a central role in the transfer of energy across the ocean–sea-ice–atmosphere interface, but an adequate method for modelling the evolution of snow on Arctic sea ice including the energy budget, which determines the warming rate and subsequent melt rate of the snow, has yet to be developed.     

Weak oceanic heat transport as a cause of the instability of glacial climates

The stability of the thermohaline circulation of modern and glacial climates is compared with the help of a two dimensional ocean—atmosphere—sea ice coupled model. It turns out to be more unstable as less freshwater forcing is required to induce a polar halocline catastrophy in glacial climates. The large insulation of the ocean by the extensive sea ice cover changes the temperature boundary condition and the deepwater formation regions moves much further South. The nature of the instability is of oceanic origin, identical to that found in ocean models under mixed boundary conditions. With similar strengths of the oceanic circulation and rates of deep water formation for warm and cold climates, the loss of stability of the cold climate is due to the weak thermal stratification caused by the cooling of surface waters, the deep water temperatures being regulated by the temperature of freezing. Weaker stratification with similar overturning leads to a weakening of the meridional oceanic heat transport which is the major negative feedback stabilizing the oceanic circulation. Within the unstable regime periodic millennial oscillations occur spontaneously. The climate oscillates between a strong convective thermally driven oceanic state and a weak one driven by large salinity gradients. Both states are unstable. The atmosphere of low thermal inertia is carried along by the oceanic overturning while the variation of sea ice is out of phase with the oceanic heat content. During the abrupt warming events that punctuate the course of a millennial oscillation, sea ice variations are shown respectively to damp (amplify) the amplitude of the oceanic (atmospheric) response. This sensitivity of the oceanic circulation to a reduced concentration of greenhouse gases and to freshwater forcing adds support to the hypothesis that the millennial oscillations of the last glacial period, the so called Dansgaard—Oeschger events, may be internal instabilities of the climate system.     

Description and evaluation of the bergen climate model: ARPEGE coupled with MICOM

A new coupled atmosphere–ocean–sea ice model has been developed, named the Bergen Climate Model (BCM). It consists of the atmospheric model ARPEGE/IFS, together with a global version of the ocean model MICOM including a dynamic–thermodynamic sea ice model. The coupling between the two models uses the OASIS software package. The new model concept is described, and results from a 300-year control integration is evaluated against observational data. In BCM, both the atmosphere and the ocean components use grids which can be irregular and have non-matching coastlines. Much effort has been put into the development of optimal interpolation schemes between the models, in particular the non-trivial problem of flux conservation in the coastal areas. A flux adjustment technique has been applied to the heat and fresh-water fluxes. There is, however, a weak drift in global mean sea-surface temperature (SST) and sea-surface salinity (SSS) of respectively 0.1 °C and 0.02 psu per century. The model gives a realistic simulation of the radiation balance at the top-of-the-atmosphere, and the net surface fluxes of longwave, shortwave, and turbulent heat fluxes are within observed values. Both global and total zonal means of cloud cover and precipitation are fairly close to observations, and errors are mainly related to the strength and positioning of the Hadley cell. The mean sea-level pressure (SLP) is well simulated, and both the mean state and the interannual standard deviation show realistic features. The SST field is several degrees too cold in the equatorial upwelling area in the Pacific, and about 1 °C too warm along the eastern margins of the oceans, and in the polar regions. The deviation from Levitus salinity is typically 0.1 psu – 0.4 psu, with a tendency for positive anomalies in the Northern Hemisphere, and negative in the Southern Hemisphere. The sea-ice distribution is realistic, but with too thin ice in the Arctic Ocean and too small ice coverage in the Southern Ocean. These model deficiencies have a strong influence on the surface air temperatures in these regions. Horizontal oceanic mass transports are in the lower range of those observed. The strength of the meridional overturning in the Atlantic is 18 Sv. An analysis of the large-scale variability in the model climate reveals realistic El Niño – Southern Oscillation (ENSO) and North Atlantic–Arctic Oscillation (NAO/AO) characteristics in the SLP and surface temperatures, including spatial patterns, frequencies, and strength. While the NAO/AO spectrum is white in SLP and red in temperature, the ENSO spectrum shows an energy maximum near 3 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.     

‘Modelling the Arctic Boundary Layer: An Evaluation of Six Arcmip Regional-Scale Models using Data from the Sheba Project’

A primary climate change signal in the central Arctic is the melting of sea ice. This is dependent on the interplay between the atmosphere and the sea ice, which is critically dependent on the exchange of momentum, heat and moisture at the surface. In assessing the realism of climate change scenarios it is vital to know the quality by which these exchanges are modelled in climate simulations. Six state-of-the-art regional-climate models are run for one year in the western Arctic, on a common domain that encompasses the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment ice-drift track. Surface variables, surface fluxes and the vertical structure of the lower troposphere are evaluated using data from the SHEBA experiment. All the models are driven by the same lateral boundary conditions, sea-ice fraction and sea and sea-ice surface temperatures. Surface pressure, near-surface air temperature, specific humidity and wind speed agree well with observations, with a falling degree of accuracy in that order. Wind speeds have systematic biases in some models, by as much as a few metres per second. The surface radiation fluxes are also surprisingly accurate, given the complexity of the problem. The turbulent momentum flux is acceptable, on average, in most models, but the turbulent heat fluxes are, however, mostly unreliable. Their correlation with observed fluxes is, in principle, insignificant, and they accumulate over a year to values an order of magnitude larger than observed. Typical instantaneous errors are easily of the same order of magnitude as the observed net atmospheric heat flux. In the light of the sensitivity of the atmosphere–ice interaction to errors in these fluxes, the ice-melt in climate change scenarios must be viewed with considerable caution.     

Record Low Sea-Ice Concentration in the Central Arctic during Summer 2010

The Arctic sea-ice extent has shown a declining trend over the past 30 years. Ice coverage reached historic minima in 2007 and again in 2012. This trend has recently been assessed to be unique over at least the last 1450 years. In the summer of 2010, a very low sea-ice concentration(SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack ice at lower latitudes. This striking low ice concentration—referred to here as a record low ice concentration in the central Arctic(CARLIC)—is unique in our analysis period of 2003–15, and has not been previously reported in the literature. The CARLIC was not the result of ice melt, because sea ice was still quite thick based on in-situ ice thickness measurements.Instead, divergent ice drift appears to have been responsible for the CARLIC. A high correlation between SIC and wind stress curl suggests that the sea ice drift during the summer of 2010 responded strongly to the regional wind forcing. The drift trajectories of ice buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector,which appeared to benefit the CARLIC in 2010. Under these conditions, more solar energy can penetrate into the open water,increasing melt through increased heat flux to the ocean. We speculate that this divergence of sea ice could occur more often in the coming decades, and impact on hemispheric SIC and feed back to the climate.     

SIMULATION ON CLIMATIC VARIATION OF ARCTIC SEA ICE THROUGH AN ICE-OCEAN COUPLED MODEL*

An ocean model developed by the Institute of Marine Research and the University of Bergen in Norway (BOM) and a state-of-the-art sea ice model developed by NCAR (CSIM4) are coupled, Considering influences of 9 major rivers,forced by the NCEP reanalysis atmospheric fields and the Levitus surface salinity,the Arctic sea ice climatic variation from January 1949 to December.1999 was simulated through the coupled model.The comparison of simulated results and observations shows that:(1)the long-term ice concentration variation tendencies are in consistent with the observations in the divisional ocean regions;(2)simulated ice thickness horizontal distribution is reasonable.Simulated ice thickness has a decreasing tendency in the central Arctic,which agrees with the submarine observations.Simulated annually maximum ice thickness is highly related to observed fast-ice thickness off the Russian coast;and (3)sea ice area/volume fluxes through the Fram Strait are in accord with the satellite-derived data.Generally,the coupled model successfully simulated the Arctic Ocean sea ice climatic variation.     

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。      

Arctic sea ice decay simulated for a CO2-induced temperature rise

A large scale numerical time-dependent model of sea ice that takes into account the heat fluxes in and out of the ice, the seasonal occurrence of snow, and ice motions has been used in an experiment to determine the response of the Arctic Ocean ice pack to a warming of the atmosphere. The degree of warming specified is that expected for a doubling of atmospheric carbon dioxide with its associated greenhouse effect, a condition that could occur before the middle of the next century. The results of three 5-year simulations with a warmer atmosphere and varied boundary conditions were: (1) that in the face of a 5 K surface atmospheric temperature increase the ice pack disappeared completely in August and September but reformed in the central Arctic Ocean in mid fall; (2) that the simulations were moderately dependent on assumptions concerning cloud cover; and (3) that even when atmospheric temperature increases of 6–9 K were combined with an order-of-magnitude increase in the upward heat flux from the ocean, the ice still reappeared in winter. It should be noted that a year-round ice-free Arctic Ocean has apparently not existed for a million years or more.Currently on leave, working for the World Meteorological Organization in Geneva, Switzerland, on the World Climate Programme.The calculations for this work were carried out while both authors were at the National Center for Atmospheric Research (NCAR), which 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模拟性能的影响。结果表明,引入CICE5.0后,新耦合模式能较好地模拟出东亚冬季海平面气压、850 hPa风场以及辐射通量,进而改善东亚气温以及降水的气候态空间分布模拟效果。进一步分析发现,与原有耦合模式相比,新耦合模式更好地抓住了东亚冬季海平面气压、总降水量和气温异常对同期巴伦支海-喀拉海海冰密集度异常的响应,进而提高了模式对东亚冬季中高纬度地区气温以及降水变率的模拟能力。     

Mechanism of an Abrupt Decrease in Sea-Ice Cover in the Pacific Sector of the Arctic during the Late 1980s

The recent decline in Arctic sea-ice cover (SIC) shows seasonal and regional characteristics. The retreat of summer sea ice has occurred mainly in the Pacific sector of the Arctic. In this study, using the moving t-test, we found an abrupt change event in the long-term sea-ice area in the Pacific sector in summer 1989. This event was linked to the phase shift of the Arctic Oscillation (AO) or the Northern Annular Mode (NAM). Corresponding with the AO/NAM phase shift from negative to positive, the area of the northern hemisphere stratospheric polar vortex decreased abruptly in winter 1988/89. Comparisons of two periods before (1979–1988) and after (1989–1993) the abrupt decrease in sea ice show that an anomalous winter sea level pressure (SLP) was induced by changes in the polar vortex leading to an anomalous cyclonic ice drift in the Pacific sector. The changes in SLP and wind field persisted into the following spring, resulting in a decrease in SIC and warming of the surface air temperature (SAT). The influence of the spring SLP and SAT on ice persisted into the following summer. Meanwhile, the increased summer net surface heat flux over the ocean and sea ice as a result of the decreased spring ice cover further contributed to the summer sea-ice melt.     

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.