Attribution of Extreme Events in Arctic Sea Ice Extent

Kirchmeier‐Young, Megan C.; Zwiers, Francis W.; Gillett, Nathan P.

doi:10.1175/jcli-d-16-0412.1

Cited by 208 publications

(169 citation statements)

References 53 publications

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“…We use two initial condition large ensembles: CanESM2, the second generation Canadian Earth System Model (Arora et al, 2011) and CESM1, the Community Earth System Model (Kay et al, 2015). The CanESM2 large ensemble (Fyfe et al, 2017;Kirchmeier-Young et al, 2017) contains 50 members with combined anthropogenic and natural forcings (ALL forcings). Historical forcing is applied through 2005,…”

Section: Model Simulationsmentioning

confidence: 99%

Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales

et al. 2019

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Event attribution, which determines how anthropogenic climate change has affected the likelihood of certain types of extreme events, is of broad interest to industries, governments, and the public. Attribution results can be highly dependent on the definition of the event and the characteristics assessed, which are part of framing the attribution question. Despite a widely acknowledged sensitivity to framing, little work has been done to document the impacts on attribution and the resulting implications. Here, we use a perfect‐model approach and large ensembles of coupled climate‐model simulations to demonstrate how event attribution depends on the spatial and temporal scales used to define the event. In general, stronger attribution is found for events defined over longer time scales and larger spatial scales due to enhanced signal‐to‐noise ratios. With strong warming trends, most regions see large changes in the likelihood of temperature extremes at all scales, even at low levels of global mean temperature increase. For precipitation extremes, spatial scale plays a strong role. It may be possible to attribute changes in likelihood for extreme precipitation events defined over larger scales, but greater levels of global warming are often required before it is possible to attribute changes in the likelihood of smaller‐scale precipitation events. Care must be taken to understand the scales used in event attribution, in order to properly understand the results.

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Section: Model Simulationsmentioning

confidence: 99%

Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales

et al. 2019

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“…Similarly, monthly average temperatures from CanESM2 ALL and NAT realizations were averaged over the land grid boxes for this region. A detection and attribution analysis was performed for the longest period available ; a thorough description of the methods applied here can be found in Kirchmeier-Young et al (2016).…”

Section: Setting Up the Event Attributionmentioning

confidence: 99%

Attributing extreme fire risk in Western Canada to human emissions

et al. 2017

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Canada is expected to see an increase in fire risk under future climate projections. Large fires, such as that near Fort McMurray, Alberta in 2016, can be devastating to the communities affected. Understanding the role of human emissions in the occurrence of such extreme fire events can lend insight into how these events might change in the future. An event attribution framework is used to quantify the influence of anthropogenic forcings on extreme fire risk in the current climate of a western Canada region. Fourteen metrics from the Canadian Forest Fire Danger Rating System are used to define the extreme fire seasons. For the majority of these metrics and during the current decade, the combined effect of anthropogenic and natural forcing is estimated to have made extreme fire risk events in the region 1.5 to 6 times as likely compared to a climate that would have been with natural forcings alone. Keywords Event attribution · Fire weather · ExtremesElectronic supplementary material The online version of this article

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“…The extent of Arctic sea ice decreased at a rate of 0.45–0.51 × 10 6 km 2 /decade between 1979 and 2012. Satellite images recorded a lowest extent of Arctic sea ice in September 2007 and followed by a new record in 2012 (Serreze et al, ; Serreze et al, ; Perovich, ; Kirchmeier‐Young et al, ). A substantial and significant decline trend for the snow cover extent (SCE) and snow depth (SD) over the North Hemisphere also has been observed in recent decades (Brown and Robinson, ; Brutel‐Vuilmet et al, ; Park et al, ).…”

Section: Introductionmentioning

confidence: 99%

Quantifying the developed and developing worlds’ carbon reduction contributions to Northern Hemisphere cryosphere change

Yang

Dong

Chou

et al. 2019

Intl Journal of Climatology

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Anthropogenically induced climate warming will not stop as long as carbon dioxide (CO2) emissions continue to increase. As positive feedback from the cryosphere can amplify climate warming in higher latitudes, adaptation to and mitigation of climate change in the cryosphere have become particularly important. In this study, we quantified the contributions of climate policies of the developed and developing worlds to moderating decreases in Northern Hemisphere sea ice and snow, using the Earth System Model of Beijing Normal University (BNU‐ESM). The results indicate that the sea ice extent and snow cover would continue to shrink as CO2 concentrations continue to increase, and the combined efforts of the developed and developing worlds could successfully reduce losses of Arctic sea ice and snow. In the medium term (before 2060), contributions of the developing world to reducing the loss of Arctic sea ice extent are expected to be 65% in JFM and 60% in JAS, while the corresponding contributions to reducing snow cover loss are 46 and 70%. These contributions from the developed world are smaller: 44% in JFM and 22% in JAS for sea ice extent and 34% in JFM and 20% in JAS for snow cover. Over the long term (until 2100), the developing world is expected to contribute 71% in JFM and 77% in JAS to reducing the Arctic sea ice losses, and its contribution to reducing snow cover loss is 73 and 66%. Similarly, the corresponding contribution for the developed world is also smaller: 36% in JFM and 24% in JAS for sea ice extent and 32% in JFM and 30% in JAS for snow cover. However, the developed and developing world achieves a combined mitigation effect of more than 90% in the near and long term.

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Attribution of Extreme Events in Arctic Sea Ice Extent

Cited by 208 publications

References 53 publications

Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales

Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales

Attributing extreme fire risk in Western Canada to human emissions

Quantifying the developed and developing worlds’ carbon reduction contributions to Northern Hemisphere cryosphere change

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