Arctic amplification as a rapid response to increased CO2

2021 ◽  
Author(s):  
Tyler Janoski ◽  
Michael Previdi ◽  
Gabriel Chiodo ◽  
Karen Smith ◽  
Lorenzo Polvani
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Forced Response ◽  
Arctic Sea Ice ◽  
Lapse Rate ◽  
The Arctic ◽  
Cmip5 Models ◽  
Arctic Amplification

<p>Arctic amplification (AA), or enhanced surface warming of the Arctic, is ubiquitous in observations, and in model simulations subjected to increased greenhouse gas (GHG) forcing. Despite its importance, the mechanisms driving AA are not entirely understood. Here, we show that in CMIP5 (Coupled Model Intercomparison Project 5) general circulation models (GCMs), AA develops within a few months following an instantaneous quadrupling of atmospheric CO<sub>2</sub>. We find that this rapid AA response can be attributed to the lapse rate feedback, which acts to disproportionately warm the Arctic, even before any significant changes in Arctic sea ice occur. Only on longer timescales (beyond the first few months) does the decrease in sea ice become an important contributor to AA via the albedo feedback and increased ocean-to-atmosphere heat flux. An important limitation of our CMIP5 analysis is that internal climate variability is large on the short time scales considered. To overcome this limitation – and thus better isolate the GHG-forced response – we produced a large ensemble (100 members) of instantaneous CO<sub>2</sub>-quadrupling simulations using a single GCM, the NCAR Community Earth System Model (CESM1). In our new CESM1 ensemble we find the same rapid AA response seen in the CMIP5 models, confirming that AA ultimately owes its existence to fast atmospheric processes.</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 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 The Arctic and Antarctic Sea-Ice Area Index Records versus Measured and Modeled Temperature Data

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nicola Scafetta ◽  
Adriano Mazzarella
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Indices ◽  
Area Index ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

Here we study the Arctic and Antarctic sea-ice area records provided by the National Snow and Ice Data Center (NSIDC). These records reveal an opposite climatic behavior: since 1978 the Arctic sea-ice area index decreased, that is, the region has warmed, while the Antarctic sea-ice area index increased, that is, the region has cooled. During the last 7 years the Arctic sea-ice area has stabilized while the Antarctic sea-ice area has increased at a rate significantly higher than during the previous decades; that is, the sea-ice area of both regions has experienced a positive acceleration. This result is quite robust because it is confirmed by alternative temperature climate indices of the same regions. We also found that a significant 4-5-year natural oscillation characterizes the climate of these sea-ice polar areas. On the contrary, we found that the CMIP5 general circulation models have predicted significant warming in both polar sea regions and failed to reproduce the strong 4-5-year oscillation. Because the CMIP5 GCM simulations are inconsistent with the observations, we suggest that important natural mechanisms of climate change are missing in the models.

scholarly journals The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1

2016 ◽  
Vol 9 (6) ◽  
pp. 2255-2270 ◽  
Author(s):  
Jonathan J. Day ◽  
Steffen Tietsche ◽  
Mat Collins ◽  
Helge F. Goessling ◽  
Virginie Guemas ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
Arctic Climate ◽  
The Arctic ◽  
Initial State ◽  
Data Set ◽  
Archived Data

Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation.

The impact of denying sea ice information on the predictability of atmospheric processes over the Arctic and at mid-latitude regions

2020 ◽  
Author(s):  
Leandro Ponsoni ◽  
Daniela Flocco ◽  
François Massonnet ◽  
Steve Delhaye ◽  
Ed Hawkins ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Model Comparison ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Processes ◽  
Ice Conditions ◽  
The Impact

<p>In this work, we make use of an inter-model comparison and of a perfect model approach, in which model outputs are used as true reference states, to assess the impact that denying sea ice information has on the prediction of atmospheric processes, both over the Arctic and at mid-latitude regions. To do so, two long-term control runs (longer than 250 years) were generated with two state-of-the-art General Circulation Models (GCM), namely EC-Earth and HadGEM. From these two reference states, we have identified three different years in which the Arctic sea ice volume (SIV) was (i) maximum, (ii) minimum and (iii) a representative case for the mean state. By departing from each of these three dates (not necessarily the same for the two models), we generated a set of experiments in which the control runs are restarted both from original and climatological sea ice conditions. Here, climatological sea ice conditions are estimated as the time-average of sea ice parameters from the respective long-term control runs. The experiments are 1-year long and all of them start in January when ice is still thin, snow depth is small, air-ocean temperatures contrast the most and, therefore, the heat conductive flux in sea ice (at the surface) is nearly maximum. To robustly separate the response to degrading the initial sea ice state from background internal variability, each of the two counterfactual experiments (reference and climatological) consists of 50 ensembles members. Threstatedese ensembles are generated by adding small random perturbations to the sea surface temperature (EC-Earth) or to the air temperature (HadGEM) fields. Preliminary results reinforce the importance of having the right sea ice state for improving the (sub-)seasonal prediction of atmospheric parameters (e.g., 2m-temperature and geopotential) and circulation (e.g., Westerlies and Jet Stream) not only over the Arctic, but also at mid-latitude regions.</p>

scholarly journals Ocean Heat Transport as a Cause for Model Uncertainty in Projected Arctic Warming

2011 ◽  
Vol 24 (5) ◽  
pp. 1451-1460 ◽  
Author(s):  
Irina Mahlstein ◽  
Reto Knutti
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
General Circulation ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ocean Heat Transport ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Future Warming

Abstract The Arctic climate is governed by complex interactions and feedback mechanisms between the atmosphere, ocean, and solar radiation. One of its characteristic features, the Arctic sea ice, is very vulnerable to anthropogenically caused warming. Production and melting of sea ice is influenced by several physical processes. The authors show that the northward ocean heat transport is an important factor in the simulation of the sea ice extent in the current general circulation models. Those models that transport more energy to the Arctic show a stronger future warming, in the Arctic as well as globally. Larger heat transport to the Arctic, in particular in the Barents Sea, reduces the sea ice cover in this area. More radiation is then absorbed during summer months and is radiated back to the atmosphere in winter months. This process leads to an increase in the surface temperature and therefore to a stronger polar amplification. The models that show a larger global warming agree better with the observed sea ice extent in the Arctic. In general, these models also have a higher spatial resolution. These results suggest that higher resolution and greater complexity are beneficial in simulating the processes relevant in the Arctic and that future warming in the high northern latitudes is likely to be near the upper range of model projections, consistent with recent evidence that many climate models underestimate Arctic sea ice decline.

scholarly journals Potential faster Arctic sea ice retreat triggered by snowflakes' greenhouse effect

2018 ◽  
Author(s):  
Jui-Lin Frank Li ◽  
Mark Richardson ◽  
Wei-Liang Lee ◽  
Yulan Hong ◽  
Jonathan Jiang ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Arctic Sea Ice ◽  
Cmip5 Models ◽  
Arctic Sea ◽  
First Occurrence ◽  
Ice Retreat ◽  
Sea Ice Retreat

Abstract. Recent Arctic sea ice retreat has been quicker than in most general circulation model (GCM) simulations. Natural factors may have amplified this, but reliable attribution and projection requires accurate representation of relevant physics. Most current GCMs don’t fully represent falling ice radiative effects (FIRE), and here we show that the small set of Coupled Model Intercomparison Project, phase 5 (CMIP5) models that include FIRE tend to show faster observed retreat. We investigate this using controlled simulations with the CESM1-CAM5 model. Under 1pctCO2 simulations, including FIRE results in the first occurrence of an “ice free” Arctic (extent

The Transient and Equilibrium Response of the AMOC to Arctic sea decline in a coupled model.

2021 ◽  
Author(s):  
Amelie Simon ◽  
Brady Ferster ◽  
Alexey Fedorov ◽  
Juliette Mignot ◽  
Eric Guilyardi
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Arctic Sea ◽  
The Impact

<p>Since the mid-20th century, the Arctic has experienced two major impacts of climate change: a warming at a faster rate than the global mean surface temperature and a reduction of both winter and summer sea ice cover. However, the impact of the Arctic sea ice loss on global climate remains under debate, in particular the impact on the Atlantic meridional overturning circulation (AMOC). Specifically, some studies find that in response to Arctic sea ice decline, the AMOC weakens on multi-decadal timescales, reaching a new equilibrium state with a significantly reduced AMOC, while others studies see a weak AMOC reduction followed by a partial or full recovery. To further investigate the impact of sea ice loss on the climate, ensemble simulations are performed with the coupled atmosphere-ocean general circulation model CM5A2 from the Insitut Pierre Simon Laplace (IPSL-CM5A2). To induce the change in sea ice, the Arctic sea ice albedo is reduced by about 23%, previously shown to be consistent with the sea ice changes expected to occur by approximately the year 2040. The experimental design compares the response to sea ice loss starting from AMOC minimum and neutral phases, respectively. The objective of our experiment is to further investigate the AMOC-sea ice relationship in the transient and equilibrium responses to decreased sea ice and the robustness within a coupled model. The initial 30-year response results in similar spatial patterns in sea ice volume and 500mb potential height responses (inducing a negative NAO-like pattern) for both types of initial conditions. In both cases, the AMOC reduces by 0.5 to 1.5Sv Sv (about 15% of the model mean AMOC) during the first ~100 years of the experiment. Yet, there are differences in the response depending on the AMOC initial state, for example, in the magnitude and timing of the AMOC reduction. The AMOC eventually recover towards years 151-200. Our results give insight into the importance of decadal variability for anticipating the response of the next decades to climate change, as well as improves the understanding of the long-term transient and equilibrium responses between AMOC and Arctic sea ice.</p>

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 Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

Sign in / Sign up

Export Citation Format

Share Document