Toward a new estimate of "time of emergence" of anthropogenic warming: Insights from dynamical adjustment and a large initial-condition model ensemble

• Published in: Journal of Climate
• Other Authors: Lehner, Flavio (author), Deser, Clara (author), Terray, Laurent (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2017
• Subjects: Sea ice
• Online Access: https://doi.org/10.1175/JCLI-D-16-0792.1

Time of emergence of anthropogenic climate change is a crucial metric in risk assessments surrounding future climate predictions. However, internal climate variability impairs the ability to make accurate statements about when climate change emerges from a background reference state. None of the existing efforts to explore uncertainties in time of emergence has explicitly explored the role of internal atmospheric circulation variability. Here a dynamical adjustment method based on constructed circulation analogs is used to provide new estimates of time of emergence of anthropogenic warming over North America and Europe from both a local and spatially aggregated perspective. After removing the effects of internal atmospheric circulation variability, the emergence of anthropogenic warming occurs on average two decades earlier in winter and one decade earlier in summer over North America and Europe. Dynamical adjustment increases the percentage of land area over which warming has emerged by about 30% and 15% in winter (10% and 5% in summer) over North America and Europe, respectively. Using a large ensemble of simulations with a climate model, evidence is provided that thermodynamic factors related to variations in snow cover, sea ice, and soil moisture are important drivers of the remaining uncertainty in time of emergence. Model biases in variability lead to an underestimation (13%-22% over North America and <5% over Europe) of the land fraction emerged by 2010 in summer, indicating that the forced warming signal emerges earlier in observations than suggested by models. The results herein illustrate opportunities for future detection and attribution studies to improve physical understanding by explicitly accounting for internal atmospheric circulation variability.