scholarly journals A fully coupled Arctic sea ice-ocean-atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results

2020 ◽  
Author(s):  
Shihe Ren ◽  
Xi Liang ◽  
Qizhen Sun ◽  
Hao Yu ◽  
L. Bruno Tremblay ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Description ◽  
Preliminary Results ◽  
Comparison Results ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. The implementation of a new Arctic regional coupled sea ice-ocean-atmosphere model (ArcIOAM) and its preliminary results in the year of 2012 are presented in this paper. A newly developed coupler, C-Coupler2 (the Community Coupler 2), is used to couple the Arctic sea ice-oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. ArcIOAM is demonstrated with focus on seasonal simulation of the Arctic sea ice and ocean state in the year of 2012. The results obtained by ArcIOAM, along with the experiment of one-way coupling strategy, are compared with available observational data and reanalysis products. From the comparison, results obtained from two experiments both realistically capture the sea ice and oceanic variables in the Arctic region over a 1-year simulation period. The two-way coupled model has better performance in terms of sea ice extent, concentration, thickness and SST, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution. The coupled model and documentation are available at  https://doi.org/10.5281/zenodo.3742692 (last access: 9 June 2020), and the source code is maintained at  https://github.com/cdmpbp123/Coupled_Atm_Ice_Oce (last access: 7 April 2020).

scholarly journals A fully coupled Arctic sea-ice–ocean–atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results

2021 ◽  
Vol 14 (2) ◽  
pp. 1101-1124
Author(s):  
Shihe Ren ◽  
Xi Liang ◽  
Qizhen Sun ◽  
Hao Yu ◽  
L. Bruno Tremblay ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Description ◽  
Preliminary Results ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Coupling Strategy ◽  
Atmosphere Model

Abstract. The Arctic regional coupled sea-ice–ocean–atmosphere model (ArcIOAM) has been developed to provide reliable Arctic sea ice prediction on seasonal timescales. The description and implementation of ArcIOAM and its preliminary results for the year of 2012 are presented in this paper. In the ArcIOAM configuration, the Community Coupler 2 (C-Coupler2) is used to couple the Arctic sea-ice–oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. A scalability test is performed to investigate the parallelization of the coupled model. As the first step toward reliable Arctic seasonal sea ice prediction, ArcIOAM, implemented with two-way coupling strategy along with one-way coupling strategy, is evaluated with respect to available observational data and reanalysis products for the year of 2012. A stand-alone MITgcm run with prescribed atmospheric forcing is performed for reference. From the comparison, all the experiments simulate reasonable evolution of sea ice and ocean states in the Arctic region over a 1-year simulation period. The two-way coupling has better performance in terms of sea ice extent, concentration, thickness and sea surface temperature (SST), especially in summer. This result indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.

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.

Greenhouse-gas contribution to Arctic sea-ice loss

2021 ◽  
Author(s):  
Yeon-Hee Kim ◽  
Seung-Ki Min
Keyword(s):  
Sea Ice ◽  
Greenhouse Gas ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Detection Analysis ◽  
External Forcings ◽  
Arctic Sea ◽  
Intercomparison Project ◽  
Arctic Sea Ice Loss

<p>Arctic sea-ice area (ASIA) has been declining rapidly throughout the year during recent decades, but a formal quantification of greenhouse gas (GHG) contribution remains limited. This study conducts an attribution analysis of the observed ASIA changes from 1979 to 2017 by comparing three satellite observations with the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations using an optimal fingerprint method. The observed ASIA exhibits overall decreasing trends across all months with stronger trends in warm seasons. CMIP6 anthropogenic plus natural forcing (ALL) simulations and GHG-only forcing simulations successfully capture the observed temporal trend patterns. Results from detection analysis show that ALL signals are detected robustly for all calendar months for three observations. It is found that GHG signals are detectable in the observed ASIA decrease throughout the year, explaining most of the ASIA reduction, with a much weaker contribution by other external forcings. We additionally find that the Arctic Ocean will occur ice-free in September around the 2040s regardless of the emission scenario.</p>

scholarly journals Constraining projections of summer Arctic sea ice

2012 ◽  
Vol 6 (6) ◽  
pp. 1383-1394 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
C. M. Bitz ◽  
G. Philippon-Berthier ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Thickness Distribution ◽  
Coupled Model ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Volume Characteristics

Abstract. 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.

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.

scholarly journals Constraining projections of summer Arctic sea ice

2012 ◽  
Vol 6 (4) ◽  
pp. 2931-2959 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
C. M. Bitz ◽  
G. Philippon-Berthier ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Thickness Distribution ◽  
Coupled Model ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Volume Characteristics

Abstract. 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).

scholarly journals Ocean–Atmosphere State Dependence of the Atmospheric Response to Arctic Sea Ice Loss

2017 ◽  
Vol 30 (5) ◽  
pp. 1537-1552 ◽  
Author(s):  
Joe M. Osborne ◽  
James A. Screen ◽  
Mat Collins
Keyword(s):  
Sea Ice ◽  
North Pacific ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Arctic Sea Ice Loss ◽  
The North Pacific ◽  
Sst Anomalies

Abstract The Arctic is warming faster than the global average. This disproportionate warming—known as Arctic amplification—has caused significant local changes to the Arctic system and more uncertain remote changes across the Northern Hemisphere midlatitudes. Here, an atmospheric general circulation model (AGCM) is used to test the sensitivity of the atmospheric and surface response to Arctic sea ice loss to the phase of the Atlantic multidecadal oscillation (AMO), which varies on (multi-) decadal time scales. Four experiments are performed, combining low and high sea ice states with global sea surface temperature (SST) anomalies associated with opposite phases of the AMO. A trough–ridge–trough response to wintertime sea ice loss is seen in the Pacific–North American sector in the negative phase of the AMO. The authors propose that this is a consequence of an increased meridional temperature gradient in response to sea ice loss, just south of the climatological maximum, in the midlatitudes of the central North Pacific. This causes a southward shift in the North Pacific storm track, which strengthens the Aleutian low with circulation anomalies propagating into North America. While the climate response to sea ice loss is sensitive to AMO-related SST anomalies in the North Pacific, there is little sensitivity to larger-magnitude SST anomalies in the North Atlantic. With background ocean–atmosphere states persisting for a number of years, there is the potential to improve predictions of the impacts of Arctic sea ice loss on decadal time scales.

scholarly journals Influence of stochastic sea ice parametrization on climate and the role of atmosphere–sea ice–ocean interaction

2014 ◽  
Vol 372 (2018) ◽  
pp. 20130283 ◽  
Author(s):  
Stephan Juricke ◽  
Thomas Jung
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Stochastic Perturbations ◽  
Arctic Sea ◽  
The Mean ◽  
Mean Climate

The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere–sea ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.

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