Seasonal Prediction of Northern European Winter Air Temperatures From SST Anomalies Based on Sensitivity Estimates

Abstract

The climate over Europe is significantly affected by the state of the atmospheric circulation over the North Atlantic, which in turn is influenced by various slowly varying components of the climate system. Linear models are employed to investigate how much of the European winter air temperature variability can directly be predicted from the sea surface temperature. By comparing relations from a statistical model to those from an adjoint to a linearized climate model we evaluate the ability of the lagged maximum covariance analysis to reconstruct the dynamical relation between sea surface temperature (SST) and atmosphere temperature. Applied to specific SST conditions, both approaches allow prediction of a similar and significant fraction of the air temperature variability from SST. For a 1‐month lag, extreme air temperature responses are significant and found to be associated with an omega‐blocking pattern over Scandinavia.