ALBERT

Description: Eight earth system models of intermediate complexity (EMICs) are used to project climate change commitments for the recent Intergovernmental Panel on Climate Change’s (IPCC’s) Fourth Assessment Report (AR4). Simulations are run until the year 3000 a.d. and extend substantially farther into the future than conceptually similar simulations with atmosphere–ocean general circulation models (AOGCMs) coupled to carbon cycle models. In this paper the following are investigated: 1) the climate change commitment in response to stabilized greenhouse gases and stabilized total radiative forcing, 2) the climate change commitment in response to earlier CO2 emissions, and 3) emission trajectories for profiles leading to the stabilization of atmospheric CO2 and their uncertainties due to carbon cycle processes. Results over the twenty-first century compare reasonably well with results from AOGCMs, and the suite of EMICs proves well suited to complement more complex models. Substantial climate change commitments for sea level rise and global mean surface temperature increase after a stabilization of atmospheric greenhouse gases and radiative forcing in the year 2100 are identified. The additional warming by the year 3000 is 0.6–1.6 K for the low-CO2 IPCC Special Report on Emissions Scenarios (SRES) B1 scenario and 1.3–2.2 K for the high-CO2 SRES A2 scenario. Correspondingly, the post-2100 thermal expansion commitment is 0.3–1.1 m for SRES B1 and 0.5–2.2 m for SRES A2. Sea level continues to rise due to thermal expansion for several centuries after CO2 stabilization. In contrast, surface temperature changes slow down after a century. The meridional overturning circulation is weakened in all EMICs, but recovers to nearly initial values in all but one of the models after centuries for the scenarios considered. Emissions during the twenty-first century continue to impact atmospheric CO2 and climate even at year 3000. All models find that most of the anthropogenic carbon emissions are eventually taken up by the ocean (49%–62%) in year 3000, and that a substantial fraction (15%–28%) is still airborne even 900 yr after carbon emissions have ceased. Future stabilization of atmospheric CO2 and climate change requires a substantial reduction of CO2 emissions below present levels in all EMICs. This reduction needs to be substantially larger if carbon cycle–climate feedbacks are accounted for or if terrestrial CO2 fertilization is not operating. Large differences among EMICs are identified in both the response to increasing atmospheric CO2 and the response to climate change. This highlights the need for improved representations of carbon cycle processes in these models apart from the sensitivity to climate change. Sensitivity simulations with one single EMIC indicate that both carbon cycle and climate sensitivity related uncertainties on projected allowable emissions are substantial.

Description: Two hindcast (1983–2007) simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing) are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift) to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i) a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii) the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii) the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv) both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°).

Description: Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the representative concentration pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all nine models. RCP4.5 demonstrates continued summer Arctic sea ice decline after the forcing stabilizes due to continued warming on longer timescales. Based on the analysis of these two scenarios, we suggest that Arctic summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in seven of nine models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and the reversibility of declines in seasonal sea ice extent.

Description: We examine the recent (1979–2010) and future (2011–2100) characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5). As was the case with CMIP3, a large intermodel spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The 1979–2010 sea ice extent, thickness distribution and volume characteristics of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE) projections. Our results suggest first that the future changes in SSIE with respect to the 1979–2010 model SSIE are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population: at a given time, some models are in an ice-free state while others are still on the track of ice loss. However, in phase plane plots (that do not consider the time as an independent variable), we show that the transition towards ice-free conditions is actually occurring in a very similar manner for all models. We also find that the year at which SSIE drops below a certain threshold is likely to be constrained by the present-day sea ice properties. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime, the interval [2041, 2060] being our best estimate for a high climate forcing scenario.

Description: Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

Description: We examine the recent (1979–2010) and future (2011–2100) characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5). As was the case with CMIP3, a large inter-model spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The initial 1979–2010 sea ice properties (including the sea ice extent, thickness distribution and volume characteristics) of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE) projections. Our results suggest first that the SSIE anomalies (compared to the 1979–2010 model SSIE) are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population (at a given time, some models are in an ice-free state while others are still on the track of ice loss). In a new diagram (that does not consider the time as an independent variable) we show that the transition towards ice-free conditions is actually occuring in a very similar manner for all models. For these reasons, some quantities that do not explicitly depend on time, such as the year at which SSIE drops below a certain threshold, are likely to be constrained. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime (between 2041 and 2060 for a high climate forcing scenario).

Description: Two hindcast (1983–2007) simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing) are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift) to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i) a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii) the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii) the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv) both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°).

Description: Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into a global sea ice-ocean model, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs) carried out with a simplified model of the Arctic sea ice pack. Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple optimal interpolation scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data can also help in improving the model behavior, but it has to be handled with care because of the strong connection between ice concentration and ice thickness. This study is first step towards real data assimilation into NEMO-LIM, a global sea ice-ocean model.