Regional Arctic sea ice variations as predictor for winter climate conditions

Seasonal prediction skill of winter mid and high northern latitudes climate from sea ice variations in eight different Arctic regions is analyzed using detrended ERA-interim data and satellite sea ice data for the period 1980–2013. We find significant correlations between ice areas in both September and November and winter sea level pressure, air temperature and precipitation. The prediction skill is improved when using November sea ice conditions as predictor compared to September. This is particularly true for predicting winter NAO-like patterns and blocking situations in the Euro-Atlantic area. We find that sea ice variations in Barents Sea seem to be most important for the sign of the following winter NAO—negative after low ice—but amplitude and extension of the patterns are modulated by Greenland and Labrador Seas ice areas. November ice variability in the Greenland Sea provides the best prediction skill for central and western European temperature and ice variations in the Laptev/East Siberian Seas have the largest impact on the blocking number in the Euro-Atlantic region. Over North America, prediction skill is largest using September ice areas from the Pacific Arctic sector as predictor. Composite analyses of high and low regional autumn ice conditions reveal that the atmospheric response is not entirely linear suggesting changing predictive skill dependent on sign and amplitude of the anomaly. The results confirm the importance of realistic sea ice initial conditions for seasonal forecasts. However, correlations do seldom exceed 0.6 indicating that Arctic sea ice variations can only explain a part of winter climate variations in northern mid and high latitudes.     

Sensitivity of last glacial maximum climate to sea ice conditions in the Nordic Seas

Published reconstructions of last glacial maximum (LGM) sea surface temperatures and sea ice extent differ significantly. We here test the sensitivity of simulated North Atlantic climates to two different reconstructions by using these reconstructions as boundary conditions for model experiments. An atmospheric general circulation model has been used to perform two simulations of the (LGM) and a modern-day control simulation. Standard (CLIMAP) reconstructions of sea ice and sea surface temperatures have been used for the first simulation, and a set of new reconstructions in the Nordic Seas/Northern Atlantic have been used for the second experiment. The new reconstruction is based on 158 core samples, and represents ice-free conditions during summer in the Nordic Seas, with accordingly warmer sea surface temperatures and less extensive sea ice during winter as well. The simulated glacial climate is globally 5.7 K colder than modern day, with the largest changes at mid and high latitudes. Due to more intense Hadley circulation, the precipitation at lower latitudes has increased in the simulations of the LGM. Relative to the simulation with the standard CLIMAP reconstructions, reduction of the sea ice in the North Atlantic gives positive local responses in temperature, precipitation and reduction of the sea level pressure. Only very weak signatures of the wintertime Icelandic Low occur when the standard CLIMAP sea surface temperature reconstruction is used as the lower boundary condition in LGM. With reduced sea ice conditions in the Nordic Seas, the Icelandic Low becomes more intense and closer to its present structure. This indicates that thermal forcing is an important factor in determining the strength and position of the Icelandic Low. The Arctic Oscillation is the most dominant large scale variability feature on the Northern Hemisphere in modern day winter climate. In the simulation of the LGM with extensive sea ice this pattern is significantly changed and represents no systematic large scale variability over the North Atlantic. Reduction of the North Atlantic sea ice extent leads to stronger variability in monthly mean sea level pressure in winter. The synoptic variability appears at a lower level in the simulation when standard reconstructions of the sea surface in the LGM are used. A closer inspection of storm tracks in this model experiment shows that that the synoptic lows follow a narrow band along the ice edge during winter. The trajectories of synoptic lows are not constrained to the sea ice edge to the same degree when the sea ice extent is reduced. Seasonally open waters in the Nordic Seas in the new reconstruction apparently act as a moisture source, consistent with the current understanding of the rapid growth of the Fennoscandian and Barents Ice Sheets, during the LGM. The signal from the intensified thermal forcing in the North Atlantic in Boreal winter is carried zonally by upper tropospheric waves, and thus generates non-local responses to the changed sea ice cover.     

北极海冰及其与气象要素年际关系的年代际变化

利用Hadley海冰密集度资料和NCEP/NCAR再分析资料,分析了北极海冰融冰量及其与大气变量年际关系的年代际变化。结果表明,北极海冰存在显著的年代际变化,且有较强的区域性。东西伯利亚海和波弗特海海冰融冰量的平均值变大且方差增大,格陵兰岛以东洋面海冰融冰量的量值和变率均在减弱。对3个不同气候时段内北极海冰融冰量进行EOF分解,前两个模态均在3个气候时段发生显著的年代际变化,东西伯利亚海海冰融冰量的增加与EOF第一模态年代际变化相关,而EOF第二模态则明显造成了波弗特海海冰的年代际消融。并且,与之相应的大气环流也出现了明显的年代际变化,它们与AO/NAO的年际关系也存在年代际转折,融冰量第二模态与AO的年际关系更为紧密,1960—1990年第二模态与AO的相关系数仅为0.186,而1980—2010年相关系数已升高至0.367。整个北冰洋的海冰融冰量与AO的年际关系也出现了年代际增强,尤其是东西伯利亚地区海冰融冰量与AO的年际关系发生了年代际增强,1980—2010年两者相关达到了0.4以上。而波弗特海融冰量与AO相关系数变化较大,1960—1990年其的相关系数高达-0.488,1980年后却减少至0.161。然而AO却未发生明显的年代际变化。造成北极海冰融冰量及其与大气变量年际关系发生年代际变化的主要因子之一是波弗特高压,其年代际减弱使得极区向东西伯利亚海和波弗特海的海冰输送减弱,导致这两个区域海冰减少,使得AO与北极海冰的年际关系发生了年代际转折。     

Arctic sea ice and Eurasian climate: A review

The Arctic plays a fundamental role in the climate system and has shown significant climate change in recent decades,including the Arctic warming and decline of Arctic sea-ice extent and thickness. In contrast to the Arctic warming and reduction of Arctic sea ice, Europe, East Asia and North America have experienced anomalously cold conditions, with record snowfall during recent years. In this paper, we review current understanding of the sea-ice impacts on the Eurasian climate.Paleo, observational and modelling studies are covered to summarize several major themes, including: the variability of Arctic sea ice and its controls; the likely causes and apparent impacts of the Arctic sea-ice decline during the satellite era,as well as past and projected future impacts and trends; the links and feedback mechanisms between the Arctic sea ice and the Arctic Oscillation/North Atlantic Oscillation, the recent Eurasian cooling, winter atmospheric circulation, summer precipitation in East Asia, spring snowfall over Eurasia, East Asian winter monsoon, and midlatitude extreme weather; and the remote climate response(e.g., atmospheric circulation, air temperature) to changes in Arctic sea ice. We conclude with a brief summary and suggestions for future research.     

Methodology of assessing interannual dynamics of bioclimatic potential under climate change conditions

Scientific and methodological issues of assessing interannual variability of bioclimatic potential (BCP) in the Russian Federation are under consideration; mathematical models, technology of assessing the BCP from the multiyear mean data and individual years are presented. The calculations and assessments of the BCP and its components are performed by the constituent entities of the Russian Federation from the multiyear mean data and individual years over the period of 1997–2006. It is shown that in several constituent entities of the Russian Federation, the BCP for each year of a 10-year period of the BCP was either below or above its multiyear mean. It is also shown that in the constituent entities of the Russian Federation, where the deficiency of thermal resources is observed, some increase in the BCP due to this factor is observed, however, it has not yet reached such values, which would not limit the effective use of other constituents and the BCP as a whole.     

Physical processes responsible for the interannual variability of sea ice concentration in Arctic in boreal autumn since 1979

Arctic sea ice concentration (ASIC) in boreal autumn exhibits prominent interannual variability since 1979. The physical mechanism responsible for the year-to-year variation of ASIC is investigated through observational data analyses and idealized numerical modeling. It is found that the ASIC interannual variability is closely associated with the anomalous meridional circulations over the Northern Hemisphere, which is further linked with the tropical sea surface temperature (SST) forcing. A tropics-wide SST cooling anomaly leads to an enhanced meridional SST gradient to the north of the equator in boreal summer, generating strengthened and northward shifting Hadley circulation over the Northern Hemisphere. Consequently, the meridional circulations are enhanced and pushed poleward, leading to an enhanced descending motion at the North Pole, surrounded by an ascending motion anomaly; the surface outflow turns into easterly anomalies, opposing the mean-state winds. As a result, positive cloudiness and weakened surface wind speed emerge, which reduce ASIC through changes in the surface latent heat flux and the downward longwave radiation.     

Relationship between Arctic sea ice thickness distribution and climate of China

Based on the simulated ice thickness data from 1949 to 1999,monthly mean temperature data from 160 stations,and monthly mean 1 × 1 precipitation data reconstructed from 749 stations in China from 1951 to 2000,the relationship between the Arctic sea ice thickness distribution and the climate of China is analyzed by using the singular value decomposition method.Climate patterns of temperature and precipitation are obtained through the rotated empirical orthogonal function analysis.The results are as follows.(1) Sea ice in Arctic Ocean has a decreasing trend as a whole,and varies with two major periods of 12-14 and 16-20 yr,respectively.(2) When sea ice is thicker in central Arctic Ocean and Beaufort-Chukchi Seas,thinner in Barents-Kara Seas and Baffin Bay-Labrador Sea,precipitation is less in southern China,Tibetan Plateau,and the north part of northeastern China than normal,and vice versa.(3) When sea ice is thinner in the whole Arctic seas,precipitation is less over the middle and lower reaches of Yellow River and north part of northeastern China,more in Tibetan Plateau and south part of northeastern China than normal,and the reverse is also true.(4) When sea ice is thinner in central Arctic Ocean,East Siberian Sea,Beaufort-Chukchi Seas,and Greenland Sea;and thicker in Baffin Bay-Labrador Sea,air temperature is higher in northeastern China,southern Tibetan Plateau,and Hainan Island than normal.(5) When sea ice is thicker in East Siberian Sea 5 months earlier,thinner in Baffin Bay-Labrador Sea 7-15 months earlier,air temperature is lower over the north of Tibetan Plateau and higher in the north part of northwestern China than normal,and a reverse correlation also exists.     

Twentieth century simulation of the southern hemisphere climate in coupled models. Part II: sea ice conditions and variability

We examine the representation of the mean state and interannual variability of Antarctic sea ice in six simulations of the twentieth century from coupled models participating in the Intergovernmental Panel on Climate Change fourth assessment report. The simulations exhibit a largely seasonal southern hemisphere ice cover, as observed. There is a considerable scatter in the monthly simulated climatological ice extent among different models, but no consistent bias when compared to observations. The scatter in maximum winter ice extent among different models is correlated to the strength of the climatological zonal winds suggesting that wind forced ice transport is responsible for much of this scatter. Observations show that the leading mode of southern hemisphere ice variability exhibits a dipole structure with anomalies of one sign in the Atlantic sector associated with anomalies of the opposite sign in the Pacific sector. The observed ice anomalies also exhibit eastward propagation with the Antarctic circumpolar current, as part of the documented Antarctic circumpolar wave phenomenon. Many of the models do simulate dipole-like behavior in sea ice anomalies as the leading mode of ice variability, but there is a large discrepancy in the eastward propagation of these anomalies among the different models. Consistent with observations, the simulated Antarctic dipole-like variations in the ice cover are led by sea-level pressure anomalies in the Amundsen/ Bellingshausen Sea. These are associated, to different degrees in different models, with both the southern annular mode and the El Nino-Southern Oscillation (ENSO). There are indications that the magnitude of the influence of ENSO on the southern hemisphere ice cover is related to the strength of ENSO events simulated by the different models.     

Impact of interannual variations of spring sea ice in the Barents Sea on East Asian rainfall in June

本研究揭示了春季巴伦支海海冰偶极子分布的年际变化和东亚夏季降水之间存在显著关联。对应春季巴伦支海北部海冰增加、东南部海冰减少,东亚夏季雨带位置向北移动。这两者主要是通过初夏欧亚大陆北部对流层低层的波列联系起来:该波列从极地向东南传播到东亚北部地区,导致东北亚低压增强,进而引起东亚夏季雨带北侧降水增加,雨带位置北移。该研究暗示春季巴伦支海海冰偶极子模态作为一个前期预测因子,有利于提高东亚夏季降水预测。     

Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model

Climate Dynamics - The version of the Norwegian Climate Prediction Model (NorCPM) that only assimilates sea surface temperature (SST) with the Ensemble Kalman Filter has been used to investigate...     

大气初始场对短期气候数值预测的影响

利用中国科学院大气物理研究所发展的九层大气环流模式(简称IAP 9L2°×2.5°-AGCM)分析了大气初始场对短期气候数值预测的影响,分别从实际观测海温、海冰的外强迫和气候态海温、海冰的外强迫出发,进行两组集合回报试验,每组包含3个试验,分别将实时NCEP-Ⅱ资料和对NCEP-Ⅱ资料经5 d平滑、11 d平滑后的资料作为大气初始场,进行17 a(1988—2004年)集合回报试验,采用相关分析方法对试验结果进行对比分析。结果表明,比较相关系数定量检验出大气初始场对热带地区可预报性影响较小,而对中、高纬度地区影响很大。通过对6个试验中对应气象要素在对流层各层距平时间相关系数以及17 a空间异常相关系数均值比较分析发现对东亚(中国)地区夏季气候而言,NCEP-Ⅱ资料经5 d平滑后生成的大气初始场对应回报试验结果相对最好。     

Impact of in-consistency between the climate model and its initial conditions on climate prediction

We investigated the influence of dynamical in-consistency of initial conditions on the predictive skill of decadal climate predictions. The investigation builds on the fully coupled global model “Coupled GCM for Earth Simulator” (CFES). In two separate experiments, the ocean component of the coupled model is full-field initialized with two different initial fields from either the same coupled model CFES or the GECCO2 Ocean Synthesis while the atmosphere is initialized from CFES in both cases. Differences between both experiments show that higher SST forecast skill is obtained when initializing with coupled data assimilation initial conditions (CIH) instead of those from GECCO2 (GIH), with the most significant difference in skill obtained over the tropical Pacific at lead year one. High predictive skill of SST over the tropical Pacific seen in CIH reflects the good reproduction of El Niño events at lead year one. In contrast, GIH produces additional erroneous El Niño events. The tropical Pacific skill differences between both runs can be rationalized in terms of the zonal momentum balance between the wind stress and pressure gradient force, which characterizes the upper equatorial Pacific. In GIH, the differences between the oceanic and atmospheric state at initial time leads to imbalance between the zonal wind stress and pressure gradient force over the equatorial Pacific, which leads to the additional pseudo El Niño events and explains reduced predictive skill. The balance can be reestablished if anomaly initialization strategy is applied with GECCO2 initial conditions and improved predictive skill in the tropical Pacific is observed at lead year one. However, initializing the coupled model with self-consistent initial conditions leads to the highest skill of climate prediction in the tropical Pacific by preserving the momentum balance between zonal wind stress and pressure gradient force along the equatorial Pacific.

     

BCC-CSM2-MR模式对北极海冰和气候的模拟及预估

基于第六次耦合模式比较计划(CMIP6),使用新一代全球模式BCC-CSM2-MR的历史试验和未来共享社会经济路径(SSPs)数据,依据Hadley中心的海表面温度和海冰密集度数据及NCEP/NCAR I再分析资料,评估了BCC-CSM2-MR模式对北极海冰及北极气候的模拟能力,并对未来变化进行了预估.结果表明:BCC...     

A method for obtaining pre-twentieth century initial conditions for use in climate change studies

A method is proposed to initialise coupled atmosphere-ocean general circulation models (AOGCMs) developed to study climate change on multi-century time scales. The method assumes that current generation AOGCMs are developed and evaluated using present-day radiative forcing and near present day oceanic initial conditions. To find pre-twentieth century initial conditions, we propose that the radiative forcing be run backwards in time from the present to the desired starting date. The model should then be run for 3–5 centuries with the radiative forcing held constant at the desired date. In our tests, instantaneously switching to pre-twentieth century radiative forcing did not save computational time. When a sufficiently stable pre-twentieth century condition is achieved, the coupled system can be integrated forward to the present and into the future. This method is a first step toward the standardization of AOGCM initialization and suggests a framework for AOGCM initialization for the first time. It provides an internally consistent set of pre-twentieth century initial conditions, although they will vary from model to model. Furthermore, it is likely that this method will yield a fairly realistic present-day climate in transient climate change experiments of the twentieth century, if the model biases are not too large. The main disadvantage of the method is that it is fairly computationally expensive in that it requires an additional 4–6 centuries of model integration before starting historical twentieth century integrations. However, the relative cost of this technique diminishes as more simulations are conducted using the oceanic initial condition obtained using our method.     

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...     

Ensemble empirical mode decomposition for tree-ring climate reconstructions

A novel data adaptive method named ensemble empirical mode decomposition (EEMD) was used to reconstruct past temperature and precipitation variability in two 2,328- and 1,837-year tree-ring chronologies from the Dulan region, northeastern Qinghai–Tibetan Plateau. Our results show that EEMD can be used to extract low-frequency signals from the Dulan tree-ring data. The extracted low-frequency temperature trends in the two chronologies correlate significantly with Northern Hemisphere temperatures over the past two millennia. In addition, the newly reconstructed precipitation data have a higher standard deviation than that of data reconstructed with the conventional ordinary least squares and variance matching methods and yield the best amplitude match to the instrumental data. This study shows that EEMD is a powerful tool for extracting the full spectrum of climate information in tree-ring chronologies.     

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO₂ concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2–5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6–9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2–5 years and 6–9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6–9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.