Influence of internal variability on Arctic sea-ice trends

Swart, Neil C.; Fyfe, John C.; Hawkins, Ed; Kay, J. E.; Jahn, Alexandra

doi:10.1038/nclimate2483

Cited by 264 publications

(251 citation statements)

References 14 publications

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“…Internal variability is known to be a significant source of uncertainty in projections of Arctic climate change (Day et al 2012;Hodson et al 2012;Swart et al 2015;Jahn et al 2016). All simulations were conducted with the community earth system model, version 1, with the community atmosphere model, version 5 (CESM1-CAM5; Hurrell et al 2013).…”

Section: Cesm1 and The Large Ensemblementioning

confidence: 99%

Seasonal differences in the response of Arctic cyclones to climate change in CESM1

2017

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The dramatic warming of the Arctic over the last three decades has reduced both the thickness and extent of sea ice, opening opportunities for business in diverse sectors and increasing human exposure to meteorological hazards in the Arctic. It has been suggested that these changes in environmental conditions have led to an increase in extreme cyclones in the region, therefore increasing this hazard. In this study, we investigate the response of Arctic synoptic scale cyclones to climate change in a large initial value ensemble of future climate projections with the CESM1-CAM5 climate model (CESM-LE). We find that the response of Arctic cyclones in these simulations varies with season, with significant reductions in cyclone dynamic intensity across the Arctic basin in winter, but with contrasting increases in summer intensity within the region known as the Arctic Ocean cyclone maximum. There is also a significant reduction in winter cyclogenesis events within the Greenland-Iceland-Norwegian sea region. We conclude that these differences in the response of cyclone intensity and cyclogenesis, with season, appear to be closely linked to changes in surface temperature gradients in the high latitudes, with Arctic poleward temperature gradients increasing in summer, but decreasing in winter.

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Section: Cesm1 and The Large Ensemblementioning

confidence: 99%

Seasonal differences in the response of Arctic cyclones to climate change in CESM1

2017

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“…this including Kay et al (2011), Day et al (2012, Notz and Marotzke (2012), Stroeve et al (2012), Notz (2015), Swart et al (2015) and Zhang (2015). We are also cautious of overfitting; applying a trend correction would potentially result in an over-confident projection.…”

Section: Bias Correction Methodologymentioning

confidence: 99%

“…Blanchard-Wrigglesworth and Bitz, 2014). For September sea ice extent, Swart et al (2015) showed that the uncertainty in CMIP5 projections over the next few decades is dominated by these differences between models, termed "model uncertainty" by Sutton (2009, 2011). Uncertainty in climate projections arises from three distinct sources: (1) model uncertainty, (2) internal variability, and (3) scenario uncertainty, as discussed by Sutton (2009, 2011) for temperature and precipitation respectively.…”

Section: Introductionmentioning

confidence: 99%

Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations

2015

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Abstract. Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period and exhibit various biases when compared with the Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the spread in projections of SIT and reveals the significant contributions of climate internal variability in the first half of the century and of scenario uncertainty from the mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to reduce spread in climate projections more generally.

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“…September sea ice undergoes significant loss in projections of the twenty-first century (figure 2b), reaching near ice-free conditions in September in the middle of the twentyfirst century with the RCP8.5 forcing scenario. Significant internal variability is superimposed on this long-term ice loss with periods of decadal ice gains possible even during the twenty-first century (see also [25,26]). …”

Section: Climate Model Experiments (A) Cesm-cam5 Large Ensemblementioning

confidence: 99%

Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models

Holland

Landrum

2015

Phil. Trans. R. Soc. A.

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One contribution of 9 to a discussion meeting issue 'Arctic sea ice reduction: the evidence, models and impacts (part 1)' . We use a large ensemble of simulations from the Community Earth System Model to quantify simulated changes in the twentieth and twenty-first century Arctic surface shortwave heating associated with changing incoming solar radiation and changing ice conditions. For increases in shortwave absorption associated with albedo reductions, the relative influence of changing sea ice surface properties and changing sea ice areal coverage is assessed. Changes in the surface sea ice properties are associated with an earlier melt season onset, a longer snow-free season and enhanced surface ponding. Because many of these changes occur during peak solar insolation, they have a considerable influence on Arctic surface shortwave heating that is comparable to the influence of ice area loss in the early twenty-first century. As ice area loss continues through the twenty-first century, it overwhelms the influence of changes in the sea ice surface state, and is responsible for a majority of the net shortwave increases by the mid-twenty-first century. A comparison with the Arctic surface albedo and shortwave heating in CMIP5 models indicates a large spread in projected twenty-first century change. This is in part related to different ice loss rates among the models and different representations of the late twentieth century ice albedo and associated sea ice surface state.

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Influence of internal variability on Arctic sea-ice trends

Cited by 264 publications

References 14 publications

Seasonal differences in the response of Arctic cyclones to climate change in CESM1

Seasonal differences in the response of Arctic cyclones to climate change in CESM1

Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations

Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models

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