Attribution of Arctic sea ice decline from 1953 to 2012 to influences from natural, greenhouse-gas and anthropogenic aerosol forcing

• Main Author: Mueller, Bennit L.
• Other Authors: Gillett, N. P., Monahan, A.
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: detection and attribution; Arctic; sea ice; climate change; CMIP5; Climate change; Global warming; Sea ice
• Online Access: http://hdl.handle.net/1828/7669

By the end of 2016 surveillance and reconnaissance satellites will have been monitoring Arctic-wide sea ice conditions for decades. Situated at the boundary between atmosphere and ocean, Arctic sea ice retreat has been one of the most conspicuous indication of climate change, especially in the two most recent decades. The 2001 annual minimum extent of Arctic sea ice marks the last year above the 1981 -- 2012 long-term average extent. Ever since then only lower than average Arctic sea ice has been observed at the end of each summer's melt season. For more than a century climate scientists have postulated that the darkening of the Arctic due to retreating sea ice and therefore more exposed open ocean would be the consequence of global warming. In the first decade of the 2000s the human influence on that warming in the Arctic was indeed detected in observations and attributed to increasing atmospheric greenhouse-gas concentrations. In this study we direct our attention to a potential offsetting effect from other anthropogenic (OANT) forcing agents, mainly aerosols, that has potentially out masked a fraction of greenhouse-gas induced warming by a combined cooling effect. We acknowledge that multiple sources of uncertainty exist in our method, in particular in the observed records of Arctic sea ice and corresponding simulations from climate models. No formal detection and attribution (DA) analysis has yet been carried out to try to detect the combined cooling effect from aerosols in observations of Arctic sea ice extent. We use three publicly available observational data sets of Arctic sea ice and climate simulations from eight models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). In our detection and attribution study observations are regressed on model-derived climate response pattern, or fingerprints, under all known historical (ALL), greenhouse-gas only (GHG) and known natural-only (NAT) forcing factors using an optimal fingerprinting method. We estimate regression coefficients (scaling factors) ...