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.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

On the sensitivity of Antarctic sea ice model biases to atmospheric forcing uncertainties

Climate Dynamics - Although atmospheric reanalyses are an extremely valuable tool to study the climate of polar regions, they suffer from large uncertainties in these data-poor areas. In this work,...     

Development of a new sea ice growth and lead parameterization

A thermodynamic sea ice model that has been numerically structured to take time steps on the order of a week has been shown to be sensitive to time step size. This sensitivity was caused by the extrapolation of initial ice growth rates over the long time step. A new parameterization of new sea ice growth on open ocean and in leads that can be used over a large range of time step sizes (at least from 0.3 to 12 days) is described here. In this parameterization new sea ice growth is computed as a power law function of the initial energy deficit in the ocean. This power law takes into account the rapid reduction of the ice growth rate as the sea ice gets thicker, and therefore reduces sensitivity to time step size. Tests of this parameterization show that this method does a good job of simulating the rate of new ice growth when compared to data from Mawson, Antarctica, and is relatively insensitive to the length of the time step.     

适应极地快速变化海冰模式的研发与挑战

极地海冰是地球气候系统的重要组成部分,也是气候环境变化的指示器和放大器.极地海冰复杂的多尺度物理过程和极地观测资料的匮乏,给海冰模式的研发带来了巨大的挑战.在过去的半个多世纪中,大气-海冰-海洋的复杂相互作用和冰内物理过程在海冰模式中的数学描述取得了重大的进展,但海冰模式对一些重要物理过程的描述仍很不完善,尤其是近年来...     

General circulation model CO2 sensitivity experiments: Snow-sea ice albedo parameterizations and globally averaged surface air temperature

Two experiments are performed with the NCAR Community Climate Model (CCM) coupled to a swamp ocean with annually averaged solar forcing. A swamp ocean model is one in which the ocean temperature is computed from a surface energy balance. Both experiments are run with present (1 × CO₂) and doubled (2 × CO₂) amounts of atmospheric carbon dioxide (CO₂). The first tests the sensitivity of the model to a snow and sea-ice-albedo formulation which facilitates relatively greater ice melt. The second assesses the model response when the basic state of the model in the control run is colder due to a 2% decrease in solar constant. Both are compared to a previous experiment with the same model using a different snow and sea-ice-albedo formulation and the present value of the solar constant. It is found that the globally averaged surface air temperature increase due to a doubling of CO₂ is highly dependent on (1) the type of snow-sea-ice-albedo formulation used such that the parameterization which better facilitates relatively greater ice melt exhibits a greater sensitivity to increased CO₂, and (2) the basic state of the control run such that the colder the basic state, the greater the warming due to increased CO₂.A portion of this study is supported by the U.S. Department of Energy as part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation     

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。      

Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

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

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

Supercell simulations with simple ice parameterization

Summary A three-dimensional cloud model derived from the Klemp-Wilhelmson model has been used to perform simulations of a right-moving supercell with the purpose of testing the effects of terminal velocity of precipitation on the storm dynamics. The model has no ice variables and computes a fall velocity for condensed water. We simulate one of the effects of ice presence, without including phase transition, by reducing the fall velocity of the precipitation in the coldest cloud layers. The reduction of precipitation terminal velocity is shown to have a strong influence on supercell dynamics and to be responsible for nearly all the improvements in the simulation of supercells that are obtained with full ice microphysics. This includes the transition to tornadic phase, which is sharper than in the case of a pure rain supercell. The vertical component of vorticity is seen to increase at all levels, as observed in real storms, instead of just at the surface as is common in simulations with no ice phase.Our results indicate the primary importance of terminal fall speed among the effects due to the presence of ice.With 13 Figures     

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...     

A sensitivity experiment for the removal of Arctic sea ice with the French spectral general circulation model

Sea ice has a major influence on climate in high latitudes. In this paper we analyzed the impact of removal of Arctic sea-ice cover on the climate simulated by a T42 20-level version of the French spectral model Emeraude. The control experiment was the second winter of an annual cycle simulation of the present climate. In the perturbed simulation the Arctic sea-ice cover was replaced by open ocean maintained at the freezing temperature of sea water. The zonal mean patterns of the model response were found to be in good agreement with earlier simulations of Fletcher et al. and Warshaw and Rapp. The atmospheric warming, caused by the increase of upward fluxes of sensible and latent heat and of longwave radiation from the ice-free ocean surface, is largely limited to the high latitudes poleward of 70° N and the lower half of the troposphere and leads to a surface pressure decrease and a precipitation increase over this area. We also analyze the geographical distribution of the response and the mechanisms that can explain the simulated cooling over Eurasia in relation to the energy budget at the surface. Finally, we discuss the reduction of cloud cover over the ice-free Arctic, which was an unexpected result of our simulation, and conclude that further studies are necessary to resolve the question of cumulus convection and cloud process parameterization in high latitudes.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

Large-scale numerical model of antarctic sea ice extent variations

Data on sampling long-term monthly mean distributions of Antarctic sea ice extent are analyzed for the period of 1974-2013. In the framework of propositions on the nature of variations in the components of limited-area system, the numerical model of sea ice extent dynamics was developed. It is demonstrated that in 1974-2013 the variations in monthly mean sea ice extent were defined by semiannual, annual, 30-year, and 60-year periodic components. The interpolation of the obtained results is presented. The forecast of Antarctic sea ice conditions for 2015-2135 is given.     

Intercomparison and validation of snow albedo parameterization schemes in climate models

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.     

The effect of snow on Antarctic sea ice simulations in a coupled atmosphere-sea ice model

 The effect of a snow cover on sea ice accretion and ablation is estimated based on the ‘zero-layer’ version sea ice model of Semtner, and is examined using a coupled atmosphere-sea ice model including feedbacks and ice dynamics effects. When snow is disregarded in the coupled model the averaged Antarctic sea ice becomes thicker. When only half of the snowfall predicted by the atmospheric model is allowed to land on the ice surface sea ice gets thicker in most of the Weddell and Ross Seas but thinner in East Antarctic in winter, with the average slightly thicker. When twice as much snowfall as predicted by the atmospheric model is assumed to land on the ice surface sea ice also gets much thicker due to the large increase of snow-ice formation. These results indicate the importance of the correct simulation of the snow cover over sea ice and snow-ice formation in the Antarctic. Our results also illustrate the complex feedback effects of the snow cover in global climate models. In this study we have also tested the use of a mean value of 0.16 Wm^-1 K^-1 instead of 0.31 for the thermal conductivity of snow in the coupled model, based on the most recent observations in the eastern Antarctic and Bellingshausen and Amundsen Seas, and have found that the sea ice distribution changes greatly, with the ice becoming much thinner by about 0.2 m in the Antarctic and about 0.4 m in the Arctic on average. This implies that the magnitude of the thermal conductivity of snow is of considerable importance for the simulation of the sea ice distribution. An appropriate value of the thermal conductivity of snow is as crucial as the depth of the snow layer and the snowfall rate in a sea ice model. The coupled climate models require accurate values of the effective thermal conductivity of snow from observations for validating the simulated sea ice distribution under the present climate conditions. Received: 20 November 1997/Accepted: 27 July 1998     

On the sensitivity of mesoscale models to surface-layer parameterization constants

The Colorado State University standard mesoscale model is used to evaluate the sensitivity of one-dimensional (1D) and two-dimensional (2D) fields to differences in surface-layer parameterization constants. Such differences reflect the range in the published values of the von Karman constant, Monin-Obukhov stability functions and the temperature roughness length at the surface. The sensitivity of 1D boundary-layer structure, and 2D sea-breeze intensity, is generally less than that found in published comparisons related to turbulence closure schemes generally.