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.     

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.     

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2?m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations.     

The Interannual Variability and Predictability in a Global Climate Model

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Extremes and predictability in the European pre-industrial climate of a regional climate model

A high-resolution pre-industrial control simulation with the regional climate model REMO is analyzed in detail for different European subregions. To our knowledge, this is the first long pre-industrial control simulation by a regional climate model as well as at comparable resolution. We assess the ability of the climate model to reproduce the observed climate variability in various parts of the continent. In order to investigate the representation of extreme events in the model under pre-industrial greenhouse gas concentrations, selected seasons are examined with regard to the atmospheric circulation and other climatic characteristics that have contributed to the occurrences. A special focus is dedicated to land-atmosphere interactions. Extreme seasons are simulated by the model under various circumstances, some of them strongly resemble observed periods of extraordinary conditions like the summer 2003 or autumn 2006 in parts of Europe. The regional perspective turns out to be of importance when analyzing events that are constituted by meso-scale atmospheric dynamics. Moreover, the predictability of the European climate on seasonal to decadal time scales is examined by relating the statistics of surface variables to large-scale modes of variability impacting the North Atlantic sector like the Meridional Overturning Circulation, the El Niño Southern Oscillation, and the North Atlantic Oscillation. For this purpose, we introduce a measure of tail dependence that quantifies the correlation between extreme values in two variables that describe the state of the climate system. Significant dependence of extreme events can be detected in various situations.     

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.     

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...     

Impact of prescribed Arctic sea ice thickness in simulations of the present and future climate

This paper describes atmospheric general circulation model climate change experiments in which the Arctic sea-ice thickness is either fixed to 3 m or somewhat more realistically parameterized in order to take into account essentially the spatial variability of Arctic sea-ice thickness, which is, to a first approximation, a function of ice type (perennial or seasonal). It is shown that, both at present and at the end of the twenty-first century (under the SRES-A1B greenhouse gas scenario), the impact of a variable sea-ice thickness compared to a uniform value is essentially limited to the cold seasons and the lower troposphere. However, because first-year ice is scarce in the Central Arctic today, but not under SRES-A1B conditions at the end of the twenty-first century, and because the impact of a sea-ice thickness reduction can be masked by changes of the open water fraction, the spatial and temporal patterns of the effect of sea-ice thinning on the atmosphere differ between the two periods considered. As a consequence, not only the climate simulated at a given period, but also the simulated Arctic climate change over the twenty-first century is affected by the way sea-ice thickness is prescribed.     

Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model

The upper limit of climate predictability in mid and high northern latitudes on seasonal to interannual time scales is investigated by performing two perfect ensemble experiments with the global coupled atmosphere–ocean–sea ice model ECHAM5/MPI-OM. The ensembles consist of six members and are initialized in January and July from different years of the model’s 300-year control integration. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric climate parameters. The predictability of the atmospheric circulation is small except for southeastern Europe, parts of North America and the North Pacific, where significant predictability occurs with a lead time of up to half a year. The predictability of 2 m air temperature shows a large land–sea contrast with highest predictabilities over the sub polar North Atlantic and North Pacific. A combination of relatively high persistence and advection of sea surface temperature anomalies into these areas leads to large predictability. Air temperature over Europe, parts of North America and Asia shows significant predictability of up to half a year in advance. Over the ice-covered Arctic, air temperature is not predictable at time scales exceeding 2 months. Sea ice thickness is highly predictable in the central Arctic mainly due to persistence and in the Labrador Sea due to dynamics. Surface salinity is highly predictable in the Arctic Ocean, northern North Atlantic and North Pacific for several years in advance. We compare the results to the predictability due to persistence and show the importance of dynamical processes for the predictability.     

Interannual variability and predictability of sea level along the Indian Coast

Summary The Indian coast stretching more than 7,500 km constitutes the major portion of the South Asian coastline in the North Indian Ocean region. The South Asian region is significantly influenced by meteorological/oceanographic phenomena like monsoons, El Ni?o/Southern Oscillation (ENSO) and tropical cyclones. Direct/indirect impacts of these phenomena, which exhibit large interannual variabilities, on sea level changes in this region are considerable. Our results show that the mean sea level along the eastern coast of India, which is highly vulnerable to the incidence of severe tropical cyclones, is considerably higher than normal during the intense cyclonic period of a year falling in the positive phase of the Southern Oscillation (La Ni?a epoch), thereby enhancing the hazardous potential of tropical cyclones. Further, in the closing phase of the La Ni?a southwest monsoon, higher sea level anomalies prevail along the Indian coast raising the flooding potential of such monsoons. Over the west coast of India significant simultaneous correlations have been found between the amount of southwest monsoon rainfall and the mean sea level during the period from June to September. Over the east coast of India at Visakhapatnam, mean sea level is predictable with a fair degree of confidence one month in advance, by using the Sea Surface Temperature (SST) and the Southern Oscillation Index (SOI) as predictors. These results will be useful in the annual preparedness programmes aimed at mitigating the impacts of natural disasters like tropical cyclones and floods in the South Asian region. Received November 9, 2001     

The impact of Arctic sea ice on the Arctic energy budget and on the climate of the Northern mid-latitudes

The atmospheric general circulation model EC-EARTH-IFS has been applied to investigate the influence of both a reduced and a removed Arctic sea ice cover on the Arctic energy budget and on the climate of the Northern mid-latitudes. Three 40-year simulations driven by original and modified ERA-40 sea surface temperatures and sea ice concentrations have been performed at T255L62 resolution, corresponding to 79?km horizontal resolution. Simulated changes between sensitivity and reference experiments are most pronounced over the Arctic itself where the reduced or removed sea ice leads to strongly increased upward heat and longwave radiation fluxes and precipitation in winter. In summer, the most pronounced change is the stronger absorption of shortwave radiation which is enhanced by optically thinner clouds. Averaged over the year and over the area north of 70° N, the negative energy imbalance at the top of the atmosphere decreases by about 10?W/m² in both sensitivity experiments. The energy transport across 70° N is reduced. Changes are not restricted to the Arctic. Less extreme cold events and less precipitation are simulated in sub-Arctic and Northern mid-latitude regions in winter.     

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...     

Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3

Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice?Cocean?Cterrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1?year. In all regimes, ice thickness has high potential predictability for at least 2?years.     

Variability of Fram Strait sea ice export: causes, impacts and feedbacks in a coupled climate model

Analyses of a 500-year control integration of the global coupled atmosphere–sea ice–ocean model ECHAM5.0/MPI-OM show a high variability in the ice export through Fram Strait on interannual to decadal timescales. This variability is mainly determined by variations in the sea level pressure gradient across Fram Strait and thus geostrophic wind stress. Ice thickness anomalies, formed at the Siberian coast and in the Chukchi Sea, propagate across the Arctic to Fram Strait and contribute to the variability of the ice export on a timescale of about 9 years. Large anomalies of the ice export through Fram Strait cause fresh water signals, which reach the Labrador Sea after 1–2 years and lead to significant changes in the deep convection. The associated anomalies in ice cover and ocean heat release have a significant impact on air temperature in the Labrador Sea and on the large-scale atmospheric circulation. This affects the sea ice transport and distribution in the Arctic again. Sensitivity studies, simulating the effect of large ice exports through Fram Strait, show that the isolated effect of a prescribed ice/fresh water anomaly is very important for the climate variability in the Labrador Sea. Thus, the ice export through Fram Strait can be used for predictability of Labrador Sea climate up to 2 years in advance.     

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...     

Role for Eurasian Arctic shelf sea ice in a secularly varying hemispheric climate signal during the 20th century

A hypothesized low-frequency climate signal propagating across the Northern Hemisphere through a network of synchronized climate indices was identified in previous analyses of instrumental and proxy data. The tempo of signal propagation is rationalized in terms of the multidecadal component of Atlantic Ocean variability—the Atlantic Multidecadal Oscillation. Through multivariate statistical analysis of an expanded database, we further investigate this hypothesized signal to elucidate propagation dynamics. The Eurasian Arctic Shelf-Sea Region, where sea ice is uniquely exposed to open ocean in the Northern Hemisphere, emerges as a strong contender for generating and sustaining propagation of the hemispheric signal. Ocean-ice-atmosphere coupling spawns a sequence of positive and negative feedbacks that convey persistence and quasi-oscillatory features to the signal. Further stabilizing the system are anomalies of co-varying Pacific-centered atmospheric circulations. Indirectly related to dynamics in the Eurasian Arctic, these anomalies appear to negatively feed back onto the Atlantic‘s freshwater balance. Earth’s rotational rate and other proxies encode traces of this signal as it makes its way across the Northern Hemisphere.     

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.