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

1990 ◽  
Vol 16 (3) ◽  
pp. 283-306 ◽  
Author(s):  
Gerald A. Meehl ◽  
Warren M. Washington
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Sensitivity ◽  
Ocean Model ◽  
Mixed Layer Ocean

Mechanisms affecting equilibrium climate sensitivity in the PlaSim Earth System Model with different ocean model configurations

2020 ◽  
Author(s):  
Michela Angeloni ◽  
Elisa Palazzi ◽  
Jost von Hardenberg
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Sensitivity ◽  
Ocean Model ◽  
Earth System Model ◽  
System Model ◽  
Cmip5 Models ◽  
Earth System ◽  
Feedback Parameter ◽  
Equilibrium Climate Sensitivity

<p>The equilibrium climate sensitivity (ECS) of a state-of-the-art Earth System Model of intermediate complexity, the Planet Simulator (PlaSim), is determined under three tuned configurations, in which the model is coupled with a simple Mixed Layer (ML) or with the full 3D Large Scale Geostrophic (LSG) ocean model, at two horizontal resolutions, T21 (600 km) and T42 (300 km). Sensitivity experiments with doubled and quadrupled CO<sub>2</sub> were run, using either dynamic or prescribed sea ice. The resulting ECS using dynamic sea ice is 6.3 K for PlaSim-ML T21, 5.4 K for PlaSim-ML T42 and a much smaller 4.2 K for PlaSim-LSG T21. A systematic comparison between simulations with dynamic and prescribed sea ice helps to identify a strong contribution of sea ice to the value of the feedback parameter and of the climate sensitivity. Additionally, Antarctic sea ice is underestimated in PlaSim-LSG leading to a further reduction of ECS when the LSG ocean is used. The ECS of ML experiments is generally large compared with current estimates of equilibrium climate sensitivity in CMIP5 models and other EMICs: a relevant observation is that the choice of the ML horizontal diffusion coefficient, and therefore of the parameterized meridional heat transport and in turn the resulting equator-poles temperature gradient, plays an important role in controlling the ECS of the PlaSim-ML configurations. This observation should be possibly taken into account when evaluating ECS estimates in models with a mixed layer ocean. The configuration of PlaSim with the LSG ocean shows very different AMOC regimes, including 250-year oscillations and a complete shutdown of meridional transport, which depend on the ocean vertical diffusion profile and the CO<sub>2</sub> forcing conditions. These features can be explored in the framework of tipping points: the simplified and parameterized form of the climate system components included in PlaSim makes this model a suitable tool to study the transitions occurring in the Earth system in presence of critical points.</p>

Ocean model formulation influences climate sensitivity

2021 ◽  
Author(s):  
Tido Semmler ◽  
Johann Jungclaus ◽  
Christopher Danek ◽  
Helge F Goessling ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Sensitivity ◽  
North Atlantic ◽  
Heat Content ◽  
Ocean Model ◽  
Max Planck ◽  
Coupled Models ◽  
Ocean Heat Uptake ◽  
Marine Research ◽  
Transient Climate Response

<p>The climate sensitivity is known to be mainly determined by the atmosphere model but here we discover that the ocean model can change a given transient climate response (TCR) by as much as 20% while the equilibrium climate sensitivity (ECS) change is limited to 10%. In our study, two different coupled CMIP6 models (MPI-ESM and AWI-CM) in two different resolutions each are compared. The coupled models share the same atmosphere-land component ECHAM6.3, which has been developed at the Max-Planck-Institute for Meteorology (MPI-M). However, as part of MPI-ESM and AWI-CM, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice-ocean model developed at MPI-M and the FESOM sea ice-ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is different ocean heat uptake through greenhouse gas forcing in AWI simulations compared to MPI-M simulations. Specifically, AWI-CM simulations show stronger surface heating than MPI-ESM simulations while the MPI-M model accumulates more heat in the deeper ocean. The vertically integrated ocean heat content is increasing stronger in MPI-M model configurations compared to AWI model configurations in the high latitudes. Strong vertical mixing in MPI-M model configurations compared to AWI model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell Gyre, but there are also important differences in another key region, the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI model configurations and the presence of a warming hole in MPI-M model configurations. All these differences occur largely independent of the considered model resolutions.</p>

scholarly journals A One-Dimensional Mixed Layer Ocean Model for Use in Three-Dimensional Climate Simulations: Control Simulation Compared to Observations

2005 ◽  
Vol 18 (13) ◽  
pp. 2199-2221 ◽  
Author(s):  
Monica Y. Stephens ◽  
Robert J. Oglesby ◽  
Martin Maxey
Keyword(s):  
Heat Flux ◽  
Mixed Layer ◽  
General Circulation ◽  
Climate Model ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Ocean Model ◽  
Ocean Dynamics ◽  
One Dimensional ◽  
Mixed Layer Ocean

Abstract A study has been made of the dynamic interactions between the surface layer of the ocean and the atmosphere using a climate model that contains a new approach to predicting the sea surface temperature (SST). The atmospheric conditions are simulated numerically with the NCAR Community Climate Model (CCM3). The SST is determined by a modified Kraus–Turner-type one-dimensional mixed layer ocean model (MLOM) for the upper ocean that has been coupled to CCM3. The MLOM simulates vertical ocean dynamics and demonstrates the effects of the seasonal variation of mixed layer depth and convective instability on the SST. A purely thermodynamic slab ocean model (SOM) is currently available for use with CCM3 to predict the SST. A large-scale ocean general circulation model (OGCM) may also be coupled to CCM3; however, the OGCM is computationally intensive and is therefore not a good tool for conducting multiple sensitivity studies. The MLOM provides an alternative to the SOM that contains seasonally and spatially specified mixed layer depths. The SOM also contains a heat flux correction called Q-flux that crudely accounts for ocean heat transport by artificially specifying a heat flux that forces the SOM to replicate the observed SST. The results of the coupled MLOM–CCM3 reveal that the MLOM may be used on a global scale and can therefore replace the standard coupled SOM–CCM3 that contains no explicit ocean dynamics. Additionally, stand-alone experiments of the MLOM that are forced with realistic winds, heat, and moisture fluxes show that the MLOM closely approximates the observed seasonal cycle of SST.

scholarly journals Evaluation and climate sensitivity of the PlaSim v.17 Earth System Model coupled with ocean model components of different complexity

2020 ◽  
Author(s):  
Michela Angeloni ◽  
Elisa Palazzi ◽  
Jost von Hardenberg
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
Mixed Layer ◽  
Climate Sensitivity ◽  
Ice Cover ◽  
Earth System Model ◽  
Sea Surface ◽  
System Model ◽  
Earth System ◽  
Feedback Mechanisms

Abstract. A set of experiments is performed with coupled atmosphere-ocean configurations of the Planet Simulator, an Earth-system Model of Intermediate Complexity (EMIC), in order to identify under which set of parameters the model output better agrees with observations and reanalyses of the present climate. Different model configurations are explored, in which the atmospheric module of PlaSim is coupled with two possible ocean models, either a simple mixed-layer (ML) ocean with a diffusive transport parameterization or a more complex dynamical Large-Scale Geostrophic (LSG) ocean, together with a sea-ice module. In order to achieve a more realistic representation of present-day climate, we performed a preliminary tuning of the oceanic horizontal diffusion coefficient for the ML ocean and of the vertical oceanic diffusion profile when using LSG. Model runs under present-day conditions are compared, in terms of surface air temperature, sea surface temperature, sea ice cover, precipitation, radiation fluxes, ocean circulation, with a reference climate from observations and reanalyses. Our results indicate that, in all configurations, coupled PlaSim configurations are able to reproduce the main characteristics of the climate system, with the exception of the Southern Ocean region in the PlaSim-LSG model, where surface air and sea surface temperatures are warm-biased and sea ice cover is by consequence highly underestimated. The resulting sets of tuned parameters are used to perform a series of model equilibrium climate sensitivity (ECS) experiments, with the aim to identify the main mechanisms contributing to differences between the different configurations and leading to elevated values of ECS. In fact, high resulting global ECS values are found, positioned in the upper range of CMIP5 and recent CMIP6 estimates. Our analysis shows that a significant contribution to ECS is given by the sea-ice feedback mechanisms and by details of the parameterization of meridional oceanic heat transport. In particular, the configurations using a diffusive heat transport in the mixed layer present an important sensitivity in terms of radiative forcing to changes in sea-ice cover, leading to an important contribution of sea-ice feedback mechanisms to ECS.

scholarly journals Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features

2009 ◽  
Vol 2 (2) ◽  
pp. 197-212 ◽  
Author(s):  
O. H. Otterå ◽  
M. Bentsen ◽  
I. Bethke ◽  
N. G. Kvamstø
Keyword(s):  
Sea Ice ◽  
Observational Data ◽  
Mixed Layer ◽  
Large Scale ◽  
Climate Model ◽  
Ocean Model ◽  
Meridional Overturning Circulation ◽  
Model Description ◽  
Sea Ice Extent ◽  
Large Scale Circulation

Abstract. The Bergen Climate Model (BCM) is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

scholarly journals Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization

2021 ◽  
Author(s):  
Shan Sun ◽  
Amy Solomon
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Warm Season ◽  
Seasonal Prediction ◽  
The Arctic ◽  
Ice Thickness ◽  
Positive Bias ◽  
Mixed Layer Ocean ◽  
Ice Edge

Abstract. The Los Alamos sea ice model (CICE) is being tested in standalone mode for its suitability for seasonal time scale prediction. The prescribed atmospheric forcings to drive the model are from the NCEP Climate Forecast System Reanalysis (CFSR). A built-in mixed layer ocean model in CICE is used. Initial conditions for the sea ice and the mixed layer ocean in the control experiments are also from CFSR. The simulated sea ice extent in the Arctic in control experiments is generally in good agreement with observations in the warm season at all lead times up to 12 months, suggesting that CICE is able to provide useful ice edge information for seasonal prediction. However, the ice thickness forecast has a positive bias stemming from the initial conditions and often persists for more than a season, limiting the model’s seasonal forecast skill. In addition, thicker ice has a lower melting rate in the warm season, both at the bottom and top, contributing to this positive bias. When this bias is removed by initializing the model using ice thickness data from satellite observations while keeping all other initial fields unchanged, both simulated ice edge and thickness improve. This indicates the important role of ice thickness initialization in sea ice seasonal prediction.

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