scholarly journals Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss ?

2021 ◽  
pp. 1-54
Author(s):  
Y. Peings ◽  
Z. Labe ◽  
G. Magnusdottir
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Internal Variability ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
Model Assessment ◽  
Atmospheric Response ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Arctic Sea Ice Loss

AbstractThis study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of +2°C. Using two General Circulation Models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100-ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the mid-latitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean-atmosphere PAMIP experiments are analyzed. Substantial differences in the mid-latitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean-atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s-t and False Discovery Rate tests. This is problematic for the multi-model assessment of the response, as some of the spread may be attributed to different model sensitivities while it is due to internal variability. We propose a method to overcome this consistency issue, that allows for more robust conclusions when only 100 ensemble members are used.

scholarly journals The Role of Ocean–Atmosphere Coupling in the Zonal-Mean Atmospheric Response to Arctic Sea Ice Loss

2015 ◽  
Vol 28 (6) ◽  
pp. 2168-2186 ◽  
Author(s):  
Clara Deser ◽  
Robert A. Tomas ◽  
Lantao Sun
Keyword(s):  
Sea Ice ◽  
Hydrological Cycle ◽  
Arctic Sea Ice ◽  
Ocean Dynamics ◽  
Atmospheric Response ◽  
Climate System Model ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Arctic Sea Ice Loss

Abstract The role of ocean–atmosphere coupling in the zonal-mean climate response to projected late twenty-first-century Arctic sea ice loss is investigated using Community Climate System Model version 4 (CCSM4) at 1° spatial resolution. Parallel experiments with different ocean model configurations (full-depth, slab, and no interactive ocean) allow the roles of dynamical and thermodynamic ocean feedbacks to be isolated. In the absence of ocean coupling, the atmospheric response to Arctic sea ice loss is confined to north of 30°N, consisting of a weakening and equatorward shift of the westerlies accompanied by lower tropospheric warming and enhanced precipitation at high latitudes. With ocean feedbacks, the response expands to cover the whole globe and exhibits a high degree of equatorial symmetry: the entire troposphere warms, the global hydrological cycle strengthens, and the intertropical convergence zones shift equatorward. Ocean dynamics are fundamental to producing this equatorially symmetric pattern of response to Arctic sea ice loss. Finally, the absence of a poleward shift of the wintertime Northern Hemisphere westerlies in CCSM4’s response to greenhouse gas radiative forcing is shown to result from the competing effects of Arctic sea ice loss and greenhouse warming on the meridional temperature gradient in middle latitudes.

scholarly journals The Atmospheric Response to Three Decades of Observed Arctic Sea Ice Loss

2013 ◽  
Vol 26 (4) ◽  
pp. 1230-1248 ◽  
Author(s):  
James A. Screen ◽  
Ian Simmonds ◽  
Clara Deser ◽  
Robert Tomas
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Stratospheric Ozone ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Early Winter ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

Abstract Arctic sea ice is declining at an increasing rate with potentially important repercussions. To understand better the atmospheric changes that may have occurred in response to Arctic sea ice loss, this study presents results from atmospheric general circulation model (AGCM) experiments in which the only time-varying forcings prescribed were observed variations in Arctic sea ice and accompanying changes in Arctic sea surface temperatures from 1979 to 2009. Two independent AGCMs are utilized in order to assess the robustness of the response across different models. The results suggest that the atmospheric impacts of Arctic sea ice loss have been manifested most strongly within the maritime and coastal Arctic and in the lowermost atmosphere. Sea ice loss has driven increased energy transfer from the ocean to the atmosphere, enhanced warming and moistening of the lower troposphere, decreased the strength of the surface temperature inversion, and increased lower-tropospheric thickness; all of these changes are most pronounced in autumn and early winter (September–December). The early winter (November–December) atmospheric circulation response resembles the negative phase of the North Atlantic Oscillation (NAO); however, the NAO-type response is quite weak and is often masked by intrinsic (unforced) atmospheric variability. Some evidence of a late winter (March–April) polar stratospheric cooling response to sea ice loss is also found, which may have important implications for polar stratospheric ozone concentrations. The attribution and quantification of other aspects of the possible atmospheric response are hindered by model sensitivities and large intrinsic variability. The potential remote responses to Arctic sea ice change are currently hard to confirm and remain uncertain.

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 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 Autumn atmospheric response to the 2007 low Arctic sea ice extent in coupled ocean–atmosphere hindcasts

2011 ◽  
Vol 38 (11-12) ◽  
pp. 2437-2448 ◽  
Author(s):  
Yvan J. Orsolini ◽  
Retish Senan ◽  
Rasmus E. Benestad ◽  
Arne Melsom
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Low Arctic ◽  
Arctic Sea Ice Extent

scholarly journals Internal Variability in Projections of Twenty-First-Century Arctic Sea Ice Loss: Role of the Large-Scale Atmospheric Circulation

2014 ◽  
Vol 27 (2) ◽  
pp. 527-550 ◽  
Author(s):  
Justin J. Wettstein ◽  
Clara Deser
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Wave Train ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Sea ◽  
Rossby Wave Train ◽  
Arctic Sea Ice Loss

Abstract Internal variability in twenty-first-century summer Arctic sea ice loss and its relationship to the large-scale atmospheric circulation is investigated in a 39-member Community Climate System Model, version 3 (CCSM3) ensemble for the period 2000–61. Each member is subject to an identical greenhouse gas emissions scenario and differs only in the atmospheric model component's initial condition. September Arctic sea ice extent trends during 2020–59 range from −2.0 × 106 to −5.7 × 106 km2 across the 39 ensemble members, indicating a substantial role for internal variability in future Arctic sea ice loss projections. A similar nearly threefold range (from −7.0 × 103 to −19 × 103 km3) is found for summer sea ice volume trends. Higher rates of summer Arctic sea ice loss in CCSM3 are associated with enhanced transpolar drift and Fram Strait ice export driven by surface wind and sea level pressure patterns. Over the Arctic, the covarying atmospheric circulation patterns resemble the so-called Arctic dipole, with maximum amplitude between April and July. Outside the Arctic, an atmospheric Rossby wave train over the Pacific sector is associated with internal ice loss variability. Interannual covariability patterns between sea ice and atmospheric circulation are similar to those based on trends, suggesting that similar processes govern internal variability over a broad range of time scales. Interannual patterns of CCSM3 ice–atmosphere covariability compare well with those in nature and in the newer CCSM4 version of the model, lending confidence to the results. Atmospheric teleconnection patterns in CCSM3 suggest that the tropical Pacific modulates Arctic sea ice variability via the aforementioned Rossby wave train. Large ensembles with other coupled models are needed to corroborate these CCSM3-based findings.

scholarly journals Simulated Atmospheric Response to Regional and Pan-Arctic Sea Ice Loss

2017 ◽  
Vol 30 (11) ◽  
pp. 3945-3962 ◽  
Author(s):  
James A. Screen
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Arctic Sea Ice ◽  
Ecological Impacts ◽  
The Arctic ◽  
Stratospheric Polar Vortex ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

Abstract The loss of Arctic sea ice is already having profound environmental, societal, and ecological impacts locally. A highly uncertain area of scientific research, however, is whether such Arctic change has a tangible effect on weather and climate at lower latitudes. There is emerging evidence that the geographical location of sea ice loss is critically important in determining the large-scale atmospheric circulation response and associated midlatitude impacts. However, such regional dependencies have not been explored in a thorough and systematic manner. To make progress on this issue, this study analyzes ensemble simulations with an atmospheric general circulation model prescribed with sea ice loss separately in nine regions of the Arctic, to elucidate the distinct responses to regional sea ice loss. The results suggest that in some regions, sea ice loss triggers large-scale dynamical responses, whereas in other regions sea ice loss induces only local thermodynamical changes. Sea ice loss in the Barents–Kara Seas is unique in driving a weakening of the stratospheric polar vortex, followed in time by a tropospheric circulation response that resembles the North Atlantic Oscillation. For October–March, the largest spatial-scale responses are driven by sea ice loss in the Barents–Kara Seas and the Sea of Okhotsk; however, different regions assume greater importance in other seasons. The atmosphere responds very differently to regional sea ice losses than to pan-Arctic sea ice loss, and the response to pan-Arctic sea ice loss cannot be obtained by the linear addition of the responses to regional sea ice losses. The results imply that diversity in past studies of the simulated response to Arctic sea ice loss can be partly explained by the different spatial patterns of sea ice loss imposed.

scholarly journals Atmospheric Response to Arctic and Antarctic Sea Ice: The Importance of Ocean–Atmosphere Coupling and the Background State

2017 ◽  
Vol 30 (12) ◽  
pp. 4547-4565 ◽  
Author(s):  
Doug M. Smith ◽  
Nick J. Dunstone ◽  
Adam A. Scaife ◽  
Emma K. Fiedler ◽  
Dan Copsey ◽  
...  
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
The North ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
The North Atlantic ◽  
Background State

The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.

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).

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