scholarly journals Arctic rapid sea ice loss events in regional coupled climate scenario experiments

2012 ◽  
Vol 9 (4) ◽  
pp. 2327-2373 ◽  
Author(s):  
R. Döscher ◽  
T. Koenigk
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Model ◽  
Climate Scenario ◽  
Atlantic Sector ◽  
Clustering Of Events ◽  
Event Clustering ◽  
Strong Control

Abstract. Rapid sea ice loss events (RILEs) in a mini-ensemble of regional Arctic coupled climate model scenario experiments are analyzed. Mechanisms of sudden ice loss are strongly related to atmospheric circulation conditions and preconditioning by sea ice thinning during the seasons and years before the event. Clustering of events in time suggests a strong control by large scale atmospheric circulation. Anomalous atmospheric circulation is forcing ice flow and providing warm air affecting winter ice growth. Even without a seasonal preconditioning during winter, ice drop events can be initiated by anomalous inflow of warm air from the Atlantic sector during summer. It is shown that RILE events can be generated solely based on atmospheric circulation changes without possible competing mechanisms, such as anomalous seasonal radiative forcing or short-lived forcers (e.g. soot). Such forces do merely play minor roles or no role at all in our model. Mechanisms found are qualitatively in line with observations of the 2007 RILE.

scholarly journals Arctic rapid sea ice loss events in regional coupled climate scenario experiments

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 217-248 ◽  
Author(s):  
R. Döscher ◽  
T. Koenigk
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Model ◽  
Climate Scenario ◽  
Clustering Of Events ◽  
Event Clustering ◽  
Anomalous Atmospheric Circulation ◽  
Strong Control

Abstract. Rapid sea ice loss events (RILEs) in a mini-ensemble of regional Arctic coupled climate model scenario experiments are analyzed. Mechanisms of sudden ice loss are strongly related to atmospheric circulation conditions and preconditioning by sea ice thinning during the seasons and years before the event. Clustering of events in time suggests a strong control by large-scale atmospheric circulation. Anomalous atmospheric circulation is providing warm air anomalies of up to 5 K and is forcing ice flow, affecting winter ice growth. Even without a seasonal preconditioning during winter, ice drop events can be initiated by anomalous inflow of warm air during summer. It is shown that RILEs can be generated based on atmospheric circulation changes as a major driving force without major competing mechanisms, other than occasional longwave effects during spring and summer. Other anomalous seasonal radiative forcing or short-lived forcers (e.g., soot) play minor roles or no role at all in our model. RILEs initiated by ocean forcing do not occur in the model, although cannot be ruled out due to model limitations. Mechanisms found are qualitatively in line with observations of the 2007 RILE.

scholarly journals Results from the implementation of the elastic viscous plastic sea ice rheology in HadCM3

2006 ◽  
Vol 3 (4) ◽  
pp. 777-803
Author(s):  
W. Connolley ◽  
A. Keen ◽  
A. McLaren
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Ice Dynamics ◽  
Sea Ice Dynamics ◽  
Future Improvement ◽  
Physically Based ◽  
Solid Foundation ◽  
Hadley Centre ◽  
Better Than

Abstract. We present results of an implementation of the Elastic Viscous Plastic (EVP) sea ice dynamics scheme into the Hadley Centre coupled ocean-atmosphere climate model HadCM3. Although the large-scale simulation of sea ice in HadCM3 is quite good with this model, the lack of a full dynamical model leads to errors in the detailed representation of sea ice and limits our confidence in its future predictions. We find that introducing the EVP scheme results in a worse initial simulation of the sea ice. This paper documents various improvements made to improve the simulation, resulting in a sea ice simulation that is better than the original HadCM3 scheme overall. Importantly, it is more physically based and provides a more solid foundation for future improvement. We then consider the interannual variability of the sea ice in the new model and demonstrate improvements over the HadCM3 simulation.

scholarly journals The Large-Scale Dynamical Response of Clouds to Aerosol Forcing

2017 ◽  
Vol 30 (21) ◽  
pp. 8783-8794 ◽  
Author(s):  
Brian Soden ◽  
Eui-Seok Chung
Keyword(s):  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Energy Transport ◽  
Hadley Cell ◽  
Dynamical Response ◽  
Aerosol Radiative Forcing ◽  
Aerosol Forcing ◽  
Meridional Displacement ◽  
Cloud Response

Radiative kernels are used to quantify the instantaneous radiative forcing of aerosols and the aerosol-mediated cloud response in coupled ocean–atmosphere model simulations under both historical and future emission scenarios. The method is evaluated using matching pairs of historical climate change experiments with and without aerosol forcing and accurately captures the spatial pattern and global-mean effects of aerosol forcing. It is shown that aerosol-driven changes in the atmospheric circulation induce additional cloud changes. Thus, the total aerosol-mediated cloud response consists of both local microphysical changes and nonlocal dynamical changes that are driven by hemispheric asymmetries in aerosol forcing. By comparing coupled and fixed sea surface temperature (SST) simulations with identical aerosol forcing, the relative contributions of these two components are isolated, exploiting the ability of prescribed SSTs to also suppress changes in the atmospheric circulation. The radiative impact of the dynamical cloud changes is found to be comparable in magnitude to that of the microphysical cloud changes and acts to further amplify the interhemispheric asymmetry of the aerosol radiative forcing. The dynamical cloud response is closely linked to the meridional displacement of the Hadley cell, which, in turn, is driven by changes in the cross-equatorial energy transport. In this way, the dynamical cloud changes act as a positive feedback on the meridional displacement of the Hadley cell, roughly doubling the projected changes in cross-equatorial energy transport compared to that from the microphysical changes alone.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

scholarly journals Impacts of large-scale atmospheric circulation changes due to winter sea-ice retreat on Black Carbon transport and deposition to the Arctic

2016 ◽  
Author(s):  
Luca Pozzoli ◽  
Srdan Dobricic ◽  
Simone Russo ◽  
Elisabetta Vignati
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
The Arctic ◽  
The North ◽  
Ice Retreat ◽  
The North Atlantic Oscillation ◽  
Sea Ice Retreat

Abstract. Winter warming and sea ice retreat observed in the Arctic in the last decades determine changes of large scale atmospheric circulation pattern that may impact as well the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a new statistical algorithm, based on the Maximum Likelihood Estimate approach, to determine how the changes of three large scale weather patterns (the North Atlantic Oscillation, the Scandinavian Blocking, and the El Nino-Southern Oscillation), associated with winter increasing temperatures and sea ice retreat in the Arctic, impact the transport of BC to the Arctic and its deposition. We found that the three atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the Eastern Arctic while they increase BC deposition in the Western Arctic. The increasing trend is mainly due to the more frequent occurrences of stable high pressure systems (atmospheric blocking) near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. The North Atlantic Oscillation has a smaller impact on BC deposition in the Arctic, but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The El Nino-Southern Oscillation does not influence significantly the transport and deposition of BC to the Arctic. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.

Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*

2015 ◽  
Vol 28 (14) ◽  
pp. 5477-5509 ◽  
Author(s):  
Mitchell Bushuk ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Spring Sea Ice ◽  
Phase Relationships

Abstract Arctic sea ice reemergence is a phenomenon in which spring sea ice anomalies are positively correlated with fall anomalies, despite a loss of correlation over the intervening summer months. This work employs a novel data analysis algorithm for high-dimensional multivariate datasets, coupled nonlinear Laplacian spectral analysis (NLSA), to investigate the regional and temporal aspects of this reemergence phenomenon. Coupled NLSA modes of variability of sea ice concentration (SIC), sea surface temperature (SST), and sea level pressure (SLP) are studied in the Arctic sector of a comprehensive climate model and in observations. It is found that low-dimensional families of NLSA modes are able to efficiently reproduce the prominent lagged correlation features of the raw sea ice data. In both the model and observations, these families provide an SST–sea ice reemergence mechanism, in which melt season (spring) sea ice anomalies are imprinted as SST anomalies and stored over the summer months, allowing for sea ice anomalies of the same sign to reappear in the growth season (fall). The ice anomalies of each family exhibit clear phase relationships between the Barents–Kara Seas, the Labrador Sea, and the Bering Sea, three regions that compose the majority of Arctic sea ice variability. These regional phase relationships in sea ice have a natural explanation via the SLP patterns of each family, which closely resemble the Arctic Oscillation and the Arctic dipole anomaly. These SLP patterns, along with their associated geostrophic winds and surface air temperature advection, provide a large-scale teleconnection between different regions of sea ice variability. Moreover, the SLP patterns suggest another plausible ice reemergence mechanism, via their winter-to-winter regime persistence.

scholarly journals The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations

2011 ◽  
Vol 24 (13) ◽  
pp. 3520-3544 ◽  
Author(s):  
Stephen M. Griffies ◽  
Michael Winton ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Stephanie M. Downes ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Atmospheric Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate Indices ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Coupled Climate Model

Abstract This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.

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