scholarly journals September Arctic sea ice minimum prediction – a skillful new statistical approach

2019 ◽  
Vol 10 (1) ◽  
pp. 189-203 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
Statistical Model ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Atmospheric Conditions ◽  
Atmospheric Parameters ◽  
Sea Ice Extent ◽  
Important Indicator

Abstract. Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation.

scholarly journals September Arctic Sea Ice minimum prediction – a new skillful statistical approach

2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
Statistical Model ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Important Indicator ◽  
Predictive Skill

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

scholarly journals A Decade of Spaceborne Observations of the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument

2016 ◽  
Vol 97 (11) ◽  
pp. 2163-2176 ◽  
Author(s):  
Abhay Devasthale ◽  
Joseph Sedlar ◽  
Brian H. Kahn ◽  
Michael Tjernström ◽  
Eric J. Fetzer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Numerical Models ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Polar Regions ◽  
Arctic Atmosphere ◽  
Warming World

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

The relative roles of Arctic and Antarctic sea-ice loss in the response to greenhouse warming

2021 ◽  
Author(s):  
Stephanie Hay ◽  
Paul Kusnher
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Climate Model Simulations ◽  
Arctic Sea Ice Loss

<p>Antarctic sea ice has gradually increased in extent over the forty-year-long satellite record, in contrast with the clear decrease in sea-ice extent seen in the Arctic over the same time period. However, state-of-the-art climate models ubiquitously project Antarctic sea-ice to decrease over the coming century, much as they do for Arctic sea-ice. Several recent years have also seen record low Antarctic sea-ice. It is therefore of interest to understand what the climate response to Antarctic sea-ice loss will be. </p><p>We have carried out new fully coupled climate model simulations to assess the response to sea-ice loss in either hemisphere separately or coincidentally under different albedo parameter settings to determine the relative importance of each. By perturbing the albedo of the snow overlying the sea ice and the albedo of the bare sea ice, we obtain a suite of simulations to assess the linearity and additivity of sea-ice loss. We find the response to sea-ice loss in each hemisphere exhibits a high degree of additivity, and can simply be decomposed into responses due to loss in each hemisphere separately. We find that the response to Antarctic sea-ice loss exceeds that of Arctic sea-ice loss in the tropics, and that Antarctic sea-ice loss leads to statistically significant Arctic warming, while the opposite is not true.</p><p>With these new simulations and one in which CO<sub>2</sub> is instantaneously doubled , we can further characterize the response to sea-ice loss from each hemisphere using an extension to classical pattern scaling that includes three controlling parameters. This allows us to simultaneously compute the sensitivity patterns to Arctic sea-ice loss, Antarctic sea-ice loss, and to tropical warming. The statistically significant response to Antarctic sea-ice loss in the Northern Hemisphere extratropics is found to be mediated by tropical warming and small amounts of Arctic sea-ice loss.</p>

Insights for the Future of Arctic Sea Ice from the CMIP6 lig127k Experiment

2020 ◽  
Author(s):  
Esther C. Brady ◽  
Bette L. Otto-Bliesner ◽  
Masa Kageyama ◽  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Temperature ◽  
Strong Negative Correlation ◽  
Central Arctic Ocean ◽  
Sea Ice Extent ◽  
Temperature Anomalies ◽  
Arctic Sea

<p>New to CMIP6 is the Tier 1 lig127k experiment, designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models and following a common experimental protocol. We present a multi-model ensemble of 17 climate models, all of which (except for two) have also completed the CMIP6 DECK experiments, looking at the lig127k Arctic’s responses across models and the relationships with each model’s Equilibrium Climate Sensitivity (ECS), preindustrial sea ice thickness and 127ka temperature anomalies.</p><p>Boreal insolation anomalies at 127 ka enhance the seasonal cycle of Arctic sea ice, though with notable differences among the models. The consensus from the lig127k sea ice distributions is a reduced minimum (August-September) summer sea ice extent in the Arctic as compared to the piControl simulations. Sea ice remains above 15% concentrations over the central Arctic Ocean in all but one of the lig127k simulations. More than half of the models simulate a retreat of the Arctic minimum ice edge similar to the average of the last 2 decades. The lig127k minimum Arctic sea ice area anomalies show a strong negative correlation with the Arctic (60-90°N) annual surface temperature anomalies but only a weak correlation with the corresponding June-July-August (JJA) temperature anomalies. Memory in the ocean and cryosphere provide feedbacks to maintain larger positive temperature anomalies, December-January-February (DJF) and annually, in the Arctic than in JJA. The models contributing to the lig127k ensemble have an ECS varying from 2.1 to 5.3°C. There is a notable relationship between the ECS and simulation of lig127k minimum Arctic sea ice area.  With very limited Arctic sea ice proxies for 127 ka, and with evolving interpretation of the relationships of these proxies with sea ice coverage, it is still difficult to rule out the high or low values of ECS from the proxy data.</p>

scholarly journals Arctic sea-ice change: a grand challenge of climate science

2010 ◽  
Vol 56 (200) ◽  
pp. 1115-1121 ◽  
Author(s):  
Vladimir M. Kattsov ◽  
Vladimir E. Ryabinin ◽  
James E. Overland ◽  
Mark C. Serreze ◽  
Martin Visbeck ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Science ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Grand Challenge ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Instrumental Records

AbstractOver the period of modern satellite observations, Arctic sea-ice extent at the end of the melt season (September) has declined at a rate of >11% per decade, and there is evidence that the rate of decline has accelerated during the last decade. While climate models project further decreases in sea- ice mass and extent through the 21st century, the model ensemble mean trend over the period of instrumental records is smaller than observed. Possible reasons for the apparent discrepancy between observations and model simulations include observational uncertainties, vigorous unforced climate variability in the high latitudes, and limitations and shortcomings of the models stemming in particular from gaps in understanding physical process. The economic significance of a seasonally sea-ice-free future Arctic, the increased connectivity of a warmer Arctic with changes in global climate, and large uncertainties in magnitude and timing of these impacts make the problem of rapid sea-ice loss in the Arctic a grand challenge of climate science. Meaningful prediction/projection of the Arctic sea-ice conditions for the coming decades and beyond requires determining priorities for observations and model development, evaluation of the ability of climate models to reproduce the observed sea-ice behavior as a part of the broader climate system, improved attribution of the causes of Arctic sea-ice change, and improved understanding of the predictability of sea-ice conditions on seasonal through centennial timescales in the wider context of the polar climate predictability.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2012 ◽  
Vol 6 (5) ◽  
pp. 3963-3998 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Assessment and Ranking of Climate Models in Arctic Sea Ice Cover Simulation: From CMIP5 to CMIP6

2021 ◽  
Vol 34 (9) ◽  
pp. 3609-3627
Author(s):  
Zili Shen ◽  
Anmin Duan ◽  
Dongliang Li ◽  
Jinxiao Li
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Substantial Reduction ◽  
Coupled Model ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea

AbstractThe capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.

scholarly journals Comparing and contrasting the behaviour of Arctic and Antarctic sea ice over the 35 year period 1979-2013

2015 ◽  
Vol 56 (69) ◽  
pp. 18-28 ◽  
Author(s):  
Ian Simmonds
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Trend ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

AbstractWe examine the evolution of sea-ice extent (SIE) over both polar regions for 35 years from November 1978 to December 2013, as well as for the global total ice (Arctic plus Antarctic). Our examination confirms the ongoing loss of Arctic sea ice, and we find significant (p˂ 0.001) negative trends in all months, seasons and in the annual mean. The greatest rate of decrease occurs in September, and corresponds to a loss of 3 x 106 km2 over 35 years. The Antarctic shows positive trends in all seasons and for the annual mean (p˂0.01), with summer attaining a reduced significance (p˂0.10). Based on our longer record (which includes the remarkable year 2013) the positive Antarctic ice trends can no longer be considered ‘small’, and the positive trend in the annual mean of (15.29 ± 3.85) x 103 km2 a–1 is almost one-third of the magnitude of the Arctic annual mean decrease. The global annual mean SIE series exhibits a trend of (–35.29 ± 5.75) x 103 km2 a-1 (p<0.01). Finally we offer some thoughts as to why the SIE trends in the Coupled Model Intercomparison Phase 5 (CMIP5) simulations differ from the observed Antarctic increases.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2013 ◽  
Vol 7 (1) ◽  
pp. 321-332 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice loss has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead–lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

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