scholarly journals A recent weakening of winter temperature association between Arctic and Asia

2022 ◽  
Author(s):  
Bingyi Wu ◽  
Zhenkun Li ◽  
Jennifer A. Francis ◽  
Shuoyi Ding
Keyword(s):  
Sea Ice ◽  
Phase Ii ◽  
Arctic Sea Ice ◽  
Winter Temperature ◽  
The Arctic ◽  
Arctic Warming ◽  
The Past ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss ◽  
Over Time

Abstract Arctic warming and its association with the mid-latitudes have been hot topic over the past two decades. Although many studies have explored these issues it is not clear that how their linkage has changed over time. The results show that winter low tropospheric temperatures in Asia experienced two phases over the past two decades. Phase I (2007/2008 to 2012/2013) was characterized by a warm Arctic and cold Eurasia, and phase II by a warm Arctic and warm Eurasia (2013/2014 to 2018/2019). A strengthened association in winter temperature between the Arctic and Asia occurred during phase I, followed by a weakened linkage during phase II. Simulation experiments forced by observed Arctic sea ice variability largely reproduce observed patterns, suggesting that Arctic sea ice loss contributes to phasic (or low-frequency) variations in winter atmosphere and make the Arctic-Asia temperature association fluctuate over time. The weakening of the Arctic-Asia linkage post-2012/2013 was associated with amplified and expanded Arctic warming. The corresponding anomalies in SLP resembled a positive phase North Atlantic Oscillation (NAO) during phase II. This study implies that the phasic warm Arctic-cold Eurasia and warm Arctic-warm Eurasia patterns would alternately happen in the context of Arctic sea ice loss, which increase the difficulty to correctly predict Asian winter temperature.

scholarly journals Mechanisms causing reduced Arctic sea ice loss in a coupled climate model

2012 ◽  
Vol 6 (4) ◽  
pp. 2653-2687 ◽  
Author(s):  
A. E. West ◽  
A. B. Keen ◽  
H. T. Hewitt
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Historical Record ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Slight Reduction ◽  
Coupled Climate Model ◽  
Arctic Sea ◽  
Ensembles Project ◽  
Arctic Sea Ice Loss

Abstract. The fully-coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the MOC and subpolar gyre in some integrations, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.

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>

The Robustness of Midlatitude Weather Pattern Changes due to Arctic Sea Ice Loss

2016 ◽  
Vol 29 (21) ◽  
pp. 7831-7849 ◽  
Author(s):  
Hans W. Chen ◽  
Fuqing Zhang ◽  
Richard B. Alley
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Coupled System ◽  
Circulation Pattern ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Intrinsic Variability ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

Abstract The significance and robustness of the link between Arctic sea ice loss and changes in midlatitude weather patterns is investigated through a series of model simulations from the Community Atmosphere Model, version 5.3, with systematically perturbed sea ice cover in the Arctic. Using a large ensemble of 10 sea ice scenarios and 550 simulations, it is found that prescribed Arctic sea ice anomalies produce statistically significant changes for certain metrics of the midlatitude circulation but not for others. Furthermore, the significant midlatitude circulation changes do not scale linearly with the sea ice anomalies and are not present in all scenarios, indicating that the remote atmospheric response to reduced Arctic sea ice can be statistically significant under certain conditions but is generally nonrobust. Shifts in the Northern Hemisphere polar jet stream and changes in the meridional extent of upper-level large-scale waves due to the sea ice perturbations are generally small and not clearly distinguished from intrinsic variability. Reduced Arctic sea ice may favor a circulation pattern that resembles the negative phase of the Arctic Oscillation and may increase the risk of cold outbreaks in eastern Asia by almost 50%, but this response is found in only half of the scenarios with negative sea ice anomalies. In eastern North America the frequency of extreme cold events decreases almost linearly with decreasing sea ice cover. This study’s finding of frequent significant anomalies without a robust linear response suggests interactions between variability and persistence in the coupled system, which may contribute to the lack of convergence among studies of Arctic influences on midlatitude circulation.

The Seasonal Atmospheric Response to Projected Arctic Sea Ice Loss in the Late Twenty-First Century

2010 ◽  
Vol 23 (2) ◽  
pp. 333-351 ◽  
Author(s):  
Clara Deser ◽  
Robert Tomas ◽  
Michael Alexander ◽  
David Lawrence
Keyword(s):  
Sea Ice ◽  
High Latitude ◽  
Vertical Structure ◽  
Arctic Sea Ice ◽  
First Century ◽  
The Arctic ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Twenty First Century ◽  
Arctic Sea Ice Loss

Abstract The authors investigate the atmospheric response to projected Arctic sea ice loss at the end of the twenty-first century using an atmospheric general circulation model (GCM) coupled to a land surface model. The response was obtained from two 60-yr integrations: one with a repeating seasonal cycle of specified sea ice conditions for the late twentieth century (1980–99) and one with that of sea ice conditions for the late twenty-first century (2080–99). In both integrations, a repeating seasonal cycle of SSTs for 1980–99 was prescribed to isolate the impact of projected future sea ice loss. Note that greenhouse gas concentrations remained fixed at 1980–99 levels in both sets of experiments. The twentieth- and twenty-first-century sea ice (and SST) conditions were obtained from ensemble mean integrations of a coupled GCM under historical forcing and Special Report on Emissions Scenarios (SRES) A1B scenario forcing, respectively. The loss of Arctic sea ice is greatest in summer and fall, yet the response of the net surface energy budget over the Arctic Ocean is largest in winter. Air temperature and precipitation responses also maximize in winter, both over the Arctic Ocean and over the adjacent high-latitude continents. Snow depths increase over Siberia and northern Canada because of the enhanced winter precipitation. Atmospheric warming over the high-latitude continents is mainly confined to the boundary layer (below ∼850 hPa) and to regions with a strong low-level temperature inversion. Enhanced warm air advection by submonthly transient motions is the primary mechanism for the terrestrial warming. A significant large-scale atmospheric circulation response is found during winter, with a baroclinic (equivalent barotropic) vertical structure over the Arctic in November–December (January–March). This response resembles the negative phase of the North Atlantic Oscillation in February only. Comparison with the fully coupled model reveals that Arctic sea ice loss accounts for most of the seasonal, spatial, and vertical structure of the high-latitude warming response to greenhouse gas forcing at the end of the twenty-first century.

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.

Transient climate response to Arctic sea-ice loss with two ice-constraining methods

2021 ◽  
pp. 1-50
Author(s):  
Amélie Simon ◽  
Guillaume Gastineau ◽  
Claude Frankignoul ◽  
Clément Rousset ◽  
Francis Codron
Keyword(s):  
Thermal Conductivity ◽  
Sea Ice ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
Climate Impacts ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic ◽  
Arctic Sea Ice Loss

AbstractThe impact of Arctic sea-ice loss on the ocean and atmosphere is investigated focusing on a gradual reduction of Arctic sea-ice by 20% on annual mean, occurring within 30 years, starting from present-day conditions. Two ice-constraining methods are explored to melt Arctic sea-ice in a coupled climate model, while keeping present-day conditions for external forcing. The first method uses a reduction of sea-ice albedo, which modifies the incoming surface shortwave radiation. The second method uses a reduction of thermal conductivity, which changes the heat conduction flux inside ice. Reduced thermal conductivity inhibits oceanic cooling in winter and sea-ice basal growth, reducing seasonality of sea-ice thickness. For similar Arctic sea-ice area loss, decreasing the albedo induces larger Arctic warming than reducing the conductivity, especially in spring. Both ice-constraining methods produce similar climate impacts, but with smaller anomalies when reducing the conductivity. In the Arctic, the sea-ice loss leads to an increase of the North Atlantic water inflow in the Barents Sea and Eastern Arctic, while the salinity decreases and the gyre intensifies in the Beaufort Sea. In the North Atlantic, the subtropical gyre shifts southward and the Atlantic meridional overturning circulation weakens. A dipole of sea-level pressure anomalies sets up in winter over Northern Siberia and the North Atlantic, which resembles the negative phase of the North Atlantic Oscillation. In the tropics, the Atlantic Intertropical Convergence Zone shifts southward as the South Atlantic Ocean warms. In addition, Walker circulation reorganizes and the Southeastern Pacific Ocean cools.

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.

Assessment of the Regional Arctic System Model Intra-Annual Ensemble Predictions of Arctic Sea Ice

2020 ◽  
Author(s):  
Wieslaw Maslowski ◽  
Younjoo Lee ◽  
Anthony Craig ◽  
Mark Seefeldt ◽  
Robert Osinski ◽  
...  
Keyword(s):  
Sea Ice ◽  
Time Scales ◽  
Weather Prediction ◽  
Arctic Sea Ice ◽  
System Model ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
The Past ◽  
Arctic Sea

<p>The Regional Arctic System Model (RASM) has been developed and used to investigate the past to present evolution of the Arctic climate system and to address increasing demands for Arctic forecasts beyond synoptic time scales. RASM is a fully coupled ice-ocean-atmosphere-land hydrology model configured over the pan-Arctic domain with horizontal resolution of 50 km or 25 km for the atmosphere and land and 9.3 km or 2.4 km for the ocean and sea ice components. As a regional model, RASM requires boundary conditions along its lateral boundaries and in the upper atmosphere, which for simulations of the past to present are derived from global atmospheric reanalyses, such as the National Center for Environmental Predictions (NCEP) Coupled Forecast System version 2 and Reanalysis (CFSv2/CFSR). This dynamical downscaling approach allows comparison of RASM results with observations, in place and time, to diagnose and reduce model biases. This in turn allows a unique capability not available in global weather prediction and Earth system models to produce realistic and physically consistent initial conditions for prediction without data assimilation.</p><p>More recently, we have developed a new capability for an intra-annual (up to 6 months) ensemble prediction of the Arctic sea ice and climate using RASM forced with the routinely produced (every 6 hours) NCEP CFSv2 global 9-month forecasts. RASM intra-annual ensemble forecasts have been initialized on the 1<sup>st</sup> of each month starting in 2019 with forcing for each ensemble member derived from CSFv2 forecasts, 24-hr apart from the month preceding the initial forecast date.  Several key processes and feedbacks will be discussed with regard to their impact on model physics, the representation of initial state and ensemble prediction skill of Arctic sea ice variability at time scales from synoptic to decadal. The skill of RASM ensemble forecasts will be assessed against available satellite observations with reference to reanalysis as well as hindcast data using several metrics, including the standard deviation, root mean square difference, Taylor diagrams and integrated ice-edge error.</p>

scholarly journals The Role of Extratropical Ocean Warming in the Coupled Climate Response to Arctic Sea Ice Loss

2018 ◽  
Vol 31 (22) ◽  
pp. 9193-9206 ◽  
Author(s):  
Russell Blackport ◽  
Paul J. Kushner
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
General Circulation ◽  
Arctic Sea Ice ◽  
Ocean Warming ◽  
The Arctic ◽  
Climate Response ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

The role of extratropical ocean warming in the coupled climate response to Arctic sea ice loss is investigated using coupled atmosphere–ocean general circulation model (AOGCM) and uncoupled atmospheric-only (AGCM) experiments. Coupled AOGCM experiments driven by sea ice albedo reduction and greenhouse gas–dominated radiative forcing are used to diagnose the extratropical sea surface temperature (SST) response to sea ice loss. Sea ice loss is then imposed in AGCM experiments both with and without these extratropical SST changes, which are found to extend beyond the regions where sea ice is lost. Sea ice loss in isolation drives warming that is confined to the Arctic lower troposphere and only a weak atmospheric circulation response. When the extratropical SST response caused by sea ice loss is also included in the forcing, the warming extends into the Arctic midtroposphere during winter. This coincides with a stronger atmospheric circulation response, including an equatorward shift in the eddy-driven jet, a deepening of the Aleutian low, and an expansion of the Siberian high. Similar results are found whether the extratropical SST forcing is taken directly from the AOGCM driven by sea ice loss, or whether they are diagnosed using a two-parameter pattern scaling technique where tropical adjustment to sea ice loss is removed. These results suggest that AGCM experiments that are driven by sea ice loss and only local SST increases will underestimate the Arctic midtroposphere warming and atmospheric circulation response to sea ice loss, compared to AOGCM simulations and the real world.

Sign in / Sign up

Export Citation Format

Share Document