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

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