Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

2013 ◽  
Vol 26 (1) ◽  
pp. 231-245 ◽  
Author(s):  
Michael Winton ◽  
Alistair Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
Larry W. Horowitz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
Historical Simulation ◽  
Model Version ◽  
Salinity Response ◽  
The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

scholarly journals How well must climate models agree with observations?

2015 ◽  
Vol 373 (2052) ◽  
pp. 20140164 ◽  
Author(s):  
Dirk Notz
Keyword(s):  
Sea Ice ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Internal Variability ◽  
Evaluation Study ◽  
Limiting Factors ◽  
Observational Uncertainty ◽  
The Impact

The usefulness of a climate-model simulation cannot be inferred solely from its degree of agreement with observations. Instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the uncertainty in the forcing. In any model-evaluation study, the impact of these limiting factors on the suitability of specific metrics must hence be examined. This can only meaningfully be done relative to a given purpose for using a model. I here generally discuss these points and substantiate their impact on model evaluation using the example of sea ice. For this example, I find that many standard metrics such as sea-ice area or volume only permit limited inferences about the shortcomings of individual models.

scholarly journals On The Interannual Variability Of A Diagnostic Ice-Ocean Model

1990 ◽  
Vol 14 ◽  
pp. 339-339
Author(s):  
W.D Hibler ◽  
Peter Ranelli
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
The Arctic ◽  
Time Interval ◽  
Ice Drift ◽  
Ice Model

Sea-ice drift and dynamics can significantly affect the exchanges of heat between the atmosphere and ocean and salt fluxes into the ocean. The ice drift and dynamics, in turn, can be modified by the ocean circulation. This is especially true of the ice margin location whose seasonal characteristics are largely controlled by the substantial oceanic heat flux in the Greenland Sea due to convective overturning.A useful framework to analyze the interannual variability of ice–ocean interaction effects relevant to climatic change is the diagnostic ice–ocean model developed by Hibler and Bryan (1987). In this model, the oceanic temperature and salinity is weakly relaxed (except in the upper layer of the ocean which is essentially driven by the ice dynamic-thermodynamic sea-ice model) to climatological temperature and salinity data. This procedure allows seasonal and interannual variability to be simulated while still preventing the baroclinic characteristics of the ocean circulation from gradually drifting off into a total model defined state. However, in the work of Hibler and Bryan only the seasonal equilibrium characteristics of this model with the same forcing repeated year after year have been considered.In order to begin to examine the interannual behavior of this model, we have carried out a three-year simulation for the Arctic Greenland and Norwegian seas over the time period 1981–83. (The geographical region is essentially the same as used by Hibler and Bryan.) This three year simulation is carried out after an initial two year spin up using the 1981 atmospheric forcing data. For comparison purposes, an ice model simulation with only a fixed depth mixed layer was also carried out over this time interval.The results of these two simulations are analyzed with special attention to the ice margin characteristics in the Greenland and Norwegian seas to determine the role of ocean circulation on the variability there. The ice margin results are also compared to the variability in the northward transports of heat through the Faero-Shetland passage which in the fully-coupled model are calculated rather than specified.

Investigating the dynamics of an Antarctic coastal polynya using a regional climate model

2020 ◽  
Author(s):  
Pierre-Vincent Huot ◽  
Thierry Fichefet ◽  
Christoph Kittel ◽  
Nicolas Jourdain ◽  
Xavier Fettweis
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled Model ◽  
Polar Regions ◽  
Coupled Models ◽  
Polar Climate ◽  
Coastal Polynya ◽  
The Impact ◽  
Regional Coupled Model

<p>Coastal polynyas of the Southern Ocean, such as the Mertz Glacier Polynya, are paramount features of the polar climate. They allow for exchanges of heat, momentum and moisture between the atmosphere and ocean where sea ice usually prevents such interactions. Polynyas are believed to have a profound impact on polar and global climate, thanks to their sustained sea ice production and the associated formation of Dense Shelf Waters. Less is known, however, about the impact of polynyas on the atmosphere. Changes in air properties and winds induced by heat and moisture flux could for instance affect precipitation regime over the ice sheet or sea ice. As the formation and evolution of coastal polynyas are tied to the state of the atmosphere, such changes can also induce important feedbacks to polynyas dynamics. Such processes have almost never been studied, whether on the field or with the help of coupled models. Here, we propose to describe the behavior of a coastal polynya and its relationship with the ocean and atmosphere. To do so, we developed a regional coupled model of the ocean, sea ice and atmosphere (including interactive basal melt of ice shelves) and applied it to the Adélie Land area, in East Antarctica. The dynamics of the Mertz Glacier Polynya is described, together with its impact on the atmosphere, sea ice growth, dense water production and ice shelf melt. To assess the importance of potential feedbacks, we compare the dynamics of the polynya from the coupled model to a forced ocean-sea ice model. We then use the regional coupled model to investigate the implications of the Mertz ice tongue calving in early 2010 which led to a drastic decrease of the Mertz Glacier Polynya extent. This experiment aims at investigating the sensitivity of the atmosphere to the activity of the polynya and to evaluate the impact of the calving on regional climate. This work improves the understanding of the Mertz Glacier Polynya dynamics, and of the impact of coastal polynyas on polar climate. It also constitutes an additional step in the modelling of the polar regions in Earth System Models.</p>

scholarly journals On The Interannual Variability Of A Diagnostic Ice-Ocean Model

1990 ◽  
Vol 14 ◽  
pp. 339
Author(s):  
W.D Hibler ◽  
Peter Ranelli
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
The Arctic ◽  
Time Interval ◽  
Ice Drift ◽  
Ice Model

Sea-ice drift and dynamics can significantly affect the exchanges of heat between the atmosphere and ocean and salt fluxes into the ocean. The ice drift and dynamics, in turn, can be modified by the ocean circulation. This is especially true of the ice margin location whose seasonal characteristics are largely controlled by the substantial oceanic heat flux in the Greenland Sea due to convective overturning. A useful framework to analyze the interannual variability of ice–ocean interaction effects relevant to climatic change is the diagnostic ice–ocean model developed by Hibler and Bryan (1987). In this model, the oceanic temperature and salinity is weakly relaxed (except in the upper layer of the ocean which is essentially driven by the ice dynamic-thermodynamic sea-ice model) to climatological temperature and salinity data. This procedure allows seasonal and interannual variability to be simulated while still preventing the baroclinic characteristics of the ocean circulation from gradually drifting off into a total model defined state. However, in the work of Hibler and Bryan only the seasonal equilibrium characteristics of this model with the same forcing repeated year after year have been considered. In order to begin to examine the interannual behavior of this model, we have carried out a three-year simulation for the Arctic Greenland and Norwegian seas over the time period 1981–83. (The geographical region is essentially the same as used by Hibler and Bryan.) This three year simulation is carried out after an initial two year spin up using the 1981 atmospheric forcing data. For comparison purposes, an ice model simulation with only a fixed depth mixed layer was also carried out over this time interval. The results of these two simulations are analyzed with special attention to the ice margin characteristics in the Greenland and Norwegian seas to determine the role of ocean circulation on the variability there. The ice margin results are also compared to the variability in the northward transports of heat through the Faero-Shetland passage which in the fully-coupled model are calculated rather than specified.

The Impact of Poleward Moisture and Sensible Heat Flux on Arctic Winter Sea Ice Variability*

2015 ◽  
Vol 28 (13) ◽  
pp. 5030-5040 ◽  
Author(s):  
Hyo-Seok Park ◽  
Sukyoung Lee ◽  
Seok-Woo Son ◽  
Steven B. Feldstein ◽  
Yu Kosaka
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Model Simulation ◽  
Early Stage ◽  
Sensible Heat Flux ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Surface Warming ◽  
The Impact

Abstract The surface warming in recent decades has been most rapid in the Arctic, especially during the winter. Here, by utilizing global reanalysis and satellite datasets, it is shown that the northward flux of moisture into the Arctic during the winter strengthens the downward infrared radiation (IR) by 30–40 W m−2 over 1–2 weeks. This is followed by a decline of up to 10% in sea ice concentration over the Greenland, Barents, and Kara Seas. A climate model simulation indicates that the wind-induced sea ice drift leads the decline of sea ice thickness during the early stage of the strong downward IR events, but that within one week the cumulative downward IR effect appears to be dominant. Further analysis indicates that strong downward IR events are preceded several days earlier by enhanced convection over the tropical Indian and western Pacific Oceans. This finding suggests that sea ice predictions can benefit from an improved understanding of tropical convection and ensuing planetary wave dynamics.

scholarly journals Formulation of an ocean model for global climate simulations

2005 ◽  
Vol 2 (3) ◽  
pp. 165-246 ◽  
Author(s):  
S. M. Griffies ◽  
A. Gnanadesikan ◽  
K. W. Dixon ◽  
J. P. Dunne ◽  
R. Gerdes ◽  
...  
Keyword(s):  
Free Surface ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Three Dimensional ◽  
Coupled Model ◽  
Ocean Model ◽  
Tidal Mixing ◽  
The Arctic ◽  
Tracer Transport

Abstract. This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL) coupled climate model used for the 4th IPCC Assessment (AR4) of global climate change. In particular, it reviews elements of ocean climate models and how they are pieced together for use in a state-of-the-art coupled model. Novel issues are also highlighted, with particular attention given to sensitivity of the coupled simulation to physical parameterizations and numerical methods. Features of the model described here include the following: (1) tripolar grid to resolve the Arctic Ocean without polar filtering, (2) partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3) more accurate equation of state, (4) three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5) incorporation of regional climatological variability in shortwave penetration, (6) neutral physics parameterization for representation of the pathways of tracer transport, (7) staggered time stepping for tracer conservation and numerical efficiency, (8) anisotropic horizontal viscosities for representation of equatorial currents, (9) parameterization of exchange with marginal seas, (10) incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11) transport of water across the ocean free surface to eliminate unphysical "virtual tracer flux" methods, (12) parameterization of tidal mixing on continental shelves.

scholarly journals Marginal ice zone fraction benchmarks sea ice and climate model skill

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher Horvat
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Global Mean Temperature ◽  
Marginal Ice Zone ◽  
The Impact

AbstractGlobal climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-ice models or from improvements in forcing driven by other GCM components. I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs from 1979–2014, showing modern GCMs do not plausibly estimate the response of SIA to warming in all months. I identify the marginal ice zone fraction (MIZF) as a metric that is less correlated to warming, has a response plausibly simulated from January–September (but not October–December), and has highly variable future projections across GCMs. These qualities make MIZF useful for evaluating the impact of sea-ice model changes on past, present, and projected sea-ice state.

Uncertainty of climate change and its impact on reference evapotranspiration in Rasht City, Iran

2011 ◽  
Vol 2 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Heerbod Jahanbani ◽  
Lee Teang Shui ◽  
Alireza Massah Bavani ◽  
Abdul Halim Ghazali
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Model ◽  
Reference Evapotranspiration ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
General Circulation Models ◽  
Model Version ◽  
The Impact

There are many factors of uncertainty regarding the impact of climate change on reference evapotranspiration (ETo). The accuracy of the results is strictly related to these factors and ignoring any one of them reduces the precision of the results, and reduces their applicability for decision makers. In this study, the uncertainty related to two ETo models, the Hargreaves-Samani (HGS) and Artificial Neural Network (ANN), and two Atmosphere-Ocean General Circulation Models (AOGCMs), Hadley Centre Coupled Model, version 3 (HadCM3) climatic model and the Canadian Global Climate Model, version 3 (CGCM3) climatic model under climate change, was evaluated. The models predicted average temperature increases by 2010 to 2039 of 0.95 °C by the HadCM3 model and 1.13°C by the CGCM3 model under the A2 scenario relative to observed temperature. Accordingly, the models predicted average ETo would increase of 0.48, 0.60, 0.50 and 0.60 (mm/day) by 2010 to 2039 projected by four methods (by introducing the temperature of the HadCM3-A2 model and the CGCM3-A2 to ANN and HGS) relative to ETo of the observed period. The results showed that uncertainty of the AOGCMs is more than that of the ETo models applied in this study.

scholarly journals Half a degree Additional warming, Projections, Prognosis and Impacts (HAPPI): Background and Experimental Design

2016 ◽  
Author(s):  
Daniel Mitchell ◽  
Krishna AchutaRao ◽  
Myles Allen ◽  
Ingo Bethke ◽  
Piers Forster ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
Internal Climate Variability ◽  
Large Ensembles ◽  
Half Degree ◽  
The Impact

Abstract. The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the Half a degree Additional warming, Projections, Prognosis and Impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 °C and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of integrated assessment models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments. Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slice experiments are proposed, each a decade in length; the first being the most recent observed 10-year period (2006–2015), the second two being estimates of the a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the Representative Concentration Pathways 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.

Do Climate Models Underestimate the Sensitivity of Northern Hemisphere Sea Ice Cover?

2011 ◽  
Vol 24 (15) ◽  
pp. 3924-3934 ◽  
Author(s):  
Michael Winton
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Ice Cover ◽  
Natural Variability ◽  
Global Temperature ◽  
Temperature Trends ◽  
Gfdl Model ◽  
The Impact

Abstract The sensitivity of Northern Hemisphere sea ice cover to global temperature change is examined in a group of climate models and in the satellite-era observations. The models are found to have well-defined, distinguishable sensitivities in climate change experiments. The satellite-era observations show a larger sensitivity—a larger decline per degree of warming—than any of the models. To evaluate the role of natural variability in this discrepancy, the sensitivity probability density function is constructed based upon the observed trends and natural variability of multidecadal ice cover and global temperature trends in a long control run of the GFDL Climate Model, version 2.1 (CM2.1). This comparison shows that the model sensitivities range from about 1 to more than 2 pseudostandard deviations of the variability smaller than observations indicate. The impact of natural Atlantic multidecadal temperature trends (as simulated by the GFDL model) on the sensitivity distribution is examined and found to be minimal.

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