Arctic amplification of anthropogenic forcing: A vector autoregressive analysis

Abstract

On 15 September 2020, Arctic sea ice extent (SIE) ranked second-to-lowest in history and keeps trending downward. The understanding of how feedback loops amplify the effects of external CO2forcing is still limited.We propose the VARCTIC model, which is a vector autoregression (VAR) designed to capture and extrapolate Arctic feedback loops. VARs are dynamic simultaneous systems of equations, routinely estimated to predict and understand the interactions of multiple macroeconomic time series. The VARCTIC is a parsimonious compromise between full-blown climate models and purely statistical approaches that usually offer little explanation of the underlying mechanism. Our completely unconditional forecast has SIE hitting 0 in September by the 2060s. Impulse response functions reveal that anthropogenic CO2emission shocks have an unusually durable effect on SIE-a property shared by no other shock. Wefind albedo- and thickness-based feedbacks to be the main amplification channels through which CO2anomalies impact SIE in the short andmediumruns. Furthermore, conditional forecast analyses reveal that the future path of SIE crucially depends on the evolution of CO2emissions, with outcomes ranging from recovering SIE to it reaching 0 in the 2050s. Finally, albedo and thickness feedbacks are shown to play an important role in accelerating the speed at which predicted SIE is heading toward 0.