scholarly journals An EC-Earth coupled atmosphere-ocean single-column model (AOSCM) for studying coupled marine and polar processes

2018 ◽  
Author(s):  
Kerstin Hartung ◽  
Gunilla Svensson ◽  
Hamish Struthers ◽  
Anna-Lena Deppenmeier ◽  
Wilco Hazeleger
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Computational Cost ◽  
Global Climate Models ◽  
The Arctic ◽  
Small Scale ◽  
Single Column

Abstract. Single-column models (SCM) have been used as a tool to develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing and thus allow to test physical parameterizations in a controlled environment with reduced computational cost. Typically, either the ocean, sea-ice or atmosphere is fully modelled and assumptions have to be made on the boundary conditions from other subsystems, adding a potential source of errors. Here, we present a fully coupled atmosphere-ocean SCM (AOSCM), including sea-ice, which is related to the global climate model EC-Earth, consisting of NEMO3.6, LIM3, OpenIFS cycle 40r1, and OASIS3-MCT. The AOSCM is tested at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations in-situ observations are available for comparison. Evaluating model performance with buoy data, soundings and ship based observations, we find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution. Model evolution is sensitive to the initial conditions and forcing data imposed on the column. Coupling several model components while alongside using them individually can help disentangle model feedbacks. Although the model can be extended, we demonstrate that already in the current setup it is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions of their coupled components.

scholarly journals An EC-Earth coupled atmosphere–ocean single-column model (AOSCM.v1_EC-Earth3) for studying coupled marine and polar processes

2018 ◽  
Vol 11 (10) ◽  
pp. 4117-4137 ◽  
Author(s):  
Kerstin Hartung ◽  
Gunilla Svensson ◽  
Hamish Struthers ◽  
Anna-Lena Deppenmeier ◽  
Wilco Hazeleger
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Computational Cost ◽  
Global Climate Models ◽  
The Arctic ◽  
Small Scale ◽  
Single Column

Abstract. Single-column models (SCMs) have been used as tools to help develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing, which allows the testing of physical parameterisations in a controlled environment with reduced computational cost. Typically, either the ocean, sea ice or atmosphere is fully modelled and assumptions have to be made regarding the boundary conditions from other subsystems, adding a potential source of error. Here, we present a fully coupled atmosphere–ocean SCM (AOSCM), which is based on the global climate model EC-Earth3. The initial configuration of the AOSCM consists of the Nucleus for European Modelling of the Ocean (NEMO3.6) (ocean), the Louvain-la-Neuve Sea Ice Model (LIM3) (sea ice), the Open Integrated Forecasting System (OpenIFS) cycle 40r1 (atmosphere), and OASIS3-MCT (coupler). Results from the AOSCM are presented at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations, in situ observations are available for comparison. We find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution based on comparisons with buoy data, soundings and ship-based observations. The model evolution is sensitive to the initial conditions and forcing data imposed on the column. Comparing coupled and uncoupled configurations of the model can help disentangle model feedbacks. We demonstrate that the AOSCM in the current set-up is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions between the individual components of the system (atmosphere, sea ice and ocean).

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. 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.

scholarly journals The Granular Sea Ice Model in Spherical Coordinates and Its Application to a Global Climate Model

2007 ◽  
Vol 20 (24) ◽  
pp. 5946-5961 ◽  
Author(s):  
Jan Sedlacek ◽  
Jean-François Lemieux ◽  
Lawrence A. Mysak ◽  
L. Bruno Tremblay ◽  
David M. Holland
Keyword(s):  
Growth Rate ◽  
Sea Ice ◽  
Climate Model ◽  
Heat Budget ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Heat ◽  
The Arctic ◽  
Spherical Coordinates ◽  
Ice Model

Abstract The granular sea ice model (GRAN) from Tremblay and Mysak is converted from Cartesian to spherical coordinates. In this conversion, the metric terms in the divergence of the deviatoric stress and in the strain rates are included. As an application, the GRAN is coupled to the global Earth System Climate Model from the University of Victoria. The sea ice model is validated against standard datasets. The sea ice volume and area exported through Fram Strait agree well with values obtained from in situ and satellite-derived estimates. The sea ice velocity in the interior Arctic agrees well with buoy drift data. The thermodynamic behavior of the sea ice model over a seasonal cycle at one location in the Beaufort Sea is validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) datasets. The thermodynamic growth rate in the model is almost twice as large as the observed growth rate, and the melt rate is 25% lower than observed. The larger growth rate is due to thinner ice at the beginning of the SHEBA period and the absence of internal heat storage in the ice layer in the model. The simulated lower summer melt is due to the smaller-than-observed surface melt.

Northern Hemisphere Atmospheric Blocking Representation in Global Climate Models: Twenty Years of Improvements?

2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea
Keyword(s):  
Northern Hemisphere ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Main Concern ◽  
Atmospheric Blocking ◽  
Atlantic Sector

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.

scholarly journals Antarctic regional modelling of atmospheric, sea-ice and oceanic processes and validation with observations

2000 ◽  
Vol 31 ◽  
pp. 348-352 ◽  
Author(s):  
David A. Bailey ◽  
Amanda H. Lynch
Keyword(s):  
Sea Ice ◽  
Global Climate ◽  
Regional Climate ◽  
Climate System ◽  
The Arctic ◽  
Small Scale ◽  
Atmospheric Conditions ◽  
Regional Modelling ◽  
Climate System Model ◽  
The Antarctic

AbstractHigh-latitude interactions of local-scale processes in the atmosphere-ice-ocean system have effects on the local, Antarctic and global climate. Phenomena including polynyas and leads are examples of such interactions which, when combined, have a significant impact on larger scales. These small-scale features, which are typically parameterized in global models, can be explicitly simulated using high-resolution regional climate system models. As such, the study of these interactions is well suited to a regional model approach and is considered here using the Arctic Regional Climate System Model (ARCSyM). This model has been used for many simulations in the Arctic, and is now implemented for the Antarctic. Observations of such processes in the Antarctic are limited, which makes model validation difficult. However, using the best available observations for an annual cycle, we have determined a suite of model parameterization which allows us to reasonably simulate the Antarctic climate. This work considers a fine-resolution (20 km) simulation in the Cosmonaut Sea region, with the eventual goal of elucidating the mechanisms in the formation and maintenance of the sensible-heat polynya which is a regular occurrence in this area. It was found in an atmosphere-sea-ice simulation that the ocean plays an important role in regulating the sea-ice cover in this region in compensating for the cold atmospheric conditions.

scholarly journals Refinement of future Arctic sea-ice projections

2021 ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

Abstract Arctic sea ice has been retreating at unprecedented pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) in order to reduce these uncertainties. We select the models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to smaller Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of the future Arctic sea-ice loss when including all models.

Statistical Downscaling for Climate Science

2019 ◽  
Author(s):  
Douglas Maraun
Keyword(s):  
Statistical Downscaling ◽  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Scale ◽  
Climatic Changes ◽  
Global Climate Models ◽  
Small Scale ◽  
Climate Projections

Global climate models are our main tool to generate quantitative climate projections, but these models do not resolve the effects of complex topography, regional scale atmospheric processes and small-scale extreme events. To understand potential regional climatic changes, and to provide information for regional-scale impact modeling and adaptation planning, downscaling approaches have been developed. Regional climate change modeling, even though it is still a matter of basic research and questioned by many researchers, is urged to provide operational results. One major downscaling class is statistical downscaling, which exploits empirical relationships between larger-scale and local weather. The main statistical downscaling approaches are perfect prog (often referred to as empirical statistical downscaling), model output statistics (which is typically some sort of bias correction), and weather generators. Statistical downscaling complements or adds to dynamical downscaling and is useful to generate user-tailored local-scale information, or to efficiently generate regional scale information about mean climatic changes from large global climate model ensembles. Further research is needed to assess to what extent the assumptions underlying statistical downscaling are met in typical applications, and to develop new methods for generating spatially coherent projections, and for including process-understanding in bias correction. The increasing resolution of global climate models will improve the representation of downscaling predictors and will, therefore, make downscaling an even more feasible approach that will still be required to tailor information for users.

Uncertainty in Forced and Natural Arctic Solar Absorption Variations in CMIP6 Models

2021 ◽  
Vol 34 (3) ◽  
pp. 931-948
Author(s):  
Anne Sledd ◽  
Tristan L’Ecuyer
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Internal Variability ◽  
Global Climate Models ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Solar Absorption ◽  
Clear Sky

AbstractThe Arctic is rapidly changing, with increasingly dramatic sea ice loss and surface warming in recent decades. Shortwave radiation plays a key role in Arctic warming during summer months, and absorbed shortwave radiation has been increasing largely because of greater sea ice loss. Clouds can influence this ice–albedo feedback by modulating the amount of shortwave radiation incident on the Arctic Ocean. In turn, clouds impact the amount of time that must elapse before forced trends in Arctic shortwave absorption emerge from internal variability. This study determines whether the forced climate response of absorbed shortwave radiation in the Arctic has emerged in the modern satellite record and global climate models. From 18 years of satellite observations from CERES-EBAF, we find that recent declines in sea ice are large enough to produce a statistically significant trend (1.7 × 106 PJ or 3.9% per decade) in observed clear-sky absorbed shortwave radiation. However, clouds preclude any forced trends in all-sky absorption from emerging within the existing satellite record. Across 18 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), the predicted time to emergence of absorbed shortwave radiation trends varies from 8 to 39 and from 8 to 35 years for all-sky and clear-sky conditions, respectively, across two future scenarios. Furthermore, most models fail to reproduce the observed cloud delaying effect because of differences in internal variability. Contrary to observations, one-third of models suggest that clouds may reduce the time to emergence of absorbed shortwave trends relative to clear skies, an artifact that may be the result of inaccurate representations of cloud feedbacks.

scholarly journals Atmospheric drag coefficients of Weddell Sea ice computed from roughness profiles

1998 ◽  
Vol 27 ◽  
pp. 455-460 ◽  
Author(s):  
R. Fisher ◽  
Victoria I. Lytle
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Weddell Sea ◽  
The Arctic ◽  
Speed Ratio ◽  
Surface Drag ◽  
Drag Coefficients ◽  
The Antarctic

Sea ice is a highly mobile component of the Antarctic environment. Its velocity and deformation are critical processes, important in global climate models. These variables are determined by the balance of atmospheric and oceanic forces on each ice Hoe and variations in these forcings, and can produce regions ofdivcrgence or convergence. Surface drag coefficients relate the forces due to wind or water to the stress applied to the ice floe. This study adds to the limited drag coefficients reported previously for Antarctic data. Surface elevation profiles were collected during two ship-based voyages to the Weddell Sea in 1992 and 1994, and were also recorded on Ice Station Weddell in 1992. These data are used to derive surface drag coefficients using an empirical formulation following Banke and others (1980). The eastern and western regions of the Weddell Sea contain primarily first- and second-year ice, respectively. Despite these different ice types, the drag coefficients calculated are similar. The difieren! ice-drifl/wind-speed ratio in the two regions suggests a difference in ocean currents, internal ice stress or water drag. The drag coefficients calculated ranged between 1.2 X 10 −3 and 2.2 X 10 −3 The results compare well with other published Antarctic coefficients, and are generally smaller than those reported for the Arctic.

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