Nonstationary lagged relationships between the Arctic and the midlatitudes

Statistical relationships between climate variables are good source of seasonal predictability, but can we trust them to be valid in the future? In two recent papers, we investigated the stationarity of some well-known lagged relationships. The predictors were Arctic sea surface temperatures (SSTs) and sea ice cover during autumn, and the predictands were the North Atlantic Oscillation (NAO) and European temperature in winter. The reason for studying these variables was that in recent decades, reduced sea ice and above-normal SSTs in autumn have often preceded negative NAO conditions and cold temperatures in Northern Europe in the following winter. When we looked further back in time, however, we found that the relationships between SST/ice and NAO/temperatures have been highly changeable and sometimes even the complete opposite to that seen recently. One key finding was that, according to two 20th century reanalyses, the strength of the negative lagged correlation between Barents Sea SST anomalies in fall and European temperature anomalies in winter after 1979 is unprecedented since 1900. An analysis of hundreds of simulations from multiple climate models confirms that the relationships vary with time, just due to natural climate variability. This led us to question the causality and/or robustness of the links between the variables and to caution against indiscriminately predicting wintertime weather based on Arctic sea ice and SST anomalies.