From the “with models, we can make anything believable” department.
New paper argues for a stronger influence of Arctic sea-ice loss on recent Eurasian cooling, thus causing colder winters and more snow in Europe due to climate change.
A reconciled estimate of the influence of Arctic sea-ice loss on recent Eurasian cooling
Northern midlatitudes, over central Eurasia in particular, have experienced frequent severe winters in recent decades1,2,3. A remote influence of Arctic sea-ice loss has been suggested4,5,6,7,8,9,10,11,12,13,14; however, the importance of this connection remains controversial because of discrepancies among modelling and between modelling and observational studies15,16,17.
Here, using a hybrid analysis of observations and multi-model large ensembles from seven atmospheric general circulation models, we examine the cause of these differences. While all models capture the observed structure of the forced surface temperature response to sea-ice loss in the Barents–Kara Seas—including Eurasian cooling—we show that its magnitude is systematically underestimated. Owing to the varying degrees of this underestimation of sea-ice-forced signal, the signal-to-noise ratio differs markedly.
Correcting this underestimation reconciles the discrepancy between models and observations, leading to the conclusion that ~44% of the central Eurasian cooling trend for 1995–2014 is attributable to sea-ice loss in the Barents–Kara Seas.
Our results strongly suggest that anthropogenic forcing has significantly amplified the probability of severe winter occurrence in central Eurasia via enhanced melting of the Barents–Kara sea ice. The difference in underestimation of signal-to-noise ratio between models therefore calls for careful experimental design and interpretation for regional climate change attribution.
The monthly SST and SIC in HadISST33 are available from the Met Office website (www.metoffice.gov.uk/hadobs/hadisst/). The ERA-Interim reanalysis data sets44 are available from the ECMWF website (http://apps.ecmwf.int/datasets/). The six additional AGCM outputs analysed are freely available from the NOAA FACTS website (https://www.esrl.noaa.gov/psd/repository/alias/facts/). The MIROC4 AGCM output generated and analysed in this study is available from the corresponding author upon reasonable request.
Comments by climate scientist Reto Knutti on Twitter:
The tricky question is whether that is just due to a random series of unusual years or partly due to Arctic warming. In our simulations we found no link.https://t.co/2NXkdICrh6
The new paper argues the real link is stronger than in models.
— Reto Knutti ETH (@Knutti_ETH) January 15, 2019