Sudden stratospheric warmings (SSWs) are significant source of enhanced subseasonal predictability, but whether this source is untapped in operational models remains an open question. Here we report on the prediction of the SSW on 12 February 2018, its dynamical precursors, and surface climate impacts by an ensemble of dynamical forecast models. The ensemble forecast from 1 February predicted 3 times increased odds of an SSW compared to climatology, although the lead time for SSW prediction varied among individual models. Errors in the forecast location of a Ural high and underestimated magnitude of upward wave activity flux reduced SSW forecast skill. Although the SSW's downward influence was not well forecasted, the observed northern Eurasia cold anomaly following SSW was predicted, albeit with a weaker magnitude, due to persistent tropospheric anomalies. The ensemble forecast from 8 February predicted the SSW, its subsequent downward influence, and a long‐lasting cold anomaly at the surface.

El Niño-Southern Oscillation (ENSO) has significant variations and nonlinearities in its pattern and strength. ENSO events vary in their position along the equator, with some located in the central Pacific (CP) and others in the east Pacific (EP). To study how these variations are reflected in global ENSO teleconnections, both observations and idealized atmospheric general circulation model (AGCM) simulations are analyzed. Clear nonlinearities exist in observed teleconnections of sea level pressure (SLP) and precipitation. However, it is difficult to distinguish if these are caused by the different signs, strengths, or spatial patterns of events (strong El Niño events mostly being EP events and strong La Niña events mostly being CP events) or by combinations of these. Therefore, sensitivity experiments are performed with an AGCM forced with idealized EP and CP ENSO sea surface temperature (SST) patterns with varying signs and strengths. The response is generally stronger for warm events than for cold events and the teleconnection patterns vary with changing SST anomaly patterns. EP events show stronger nonlinearities than CP events. The nonlinear responses to ENSO events can be explained as a combination of nonlinear responses to a linear ENSO (fixed pattern but varying signs and strengths) and a linear response to a nonlinear ENSO (varying patterns). Any observed event is a combination of these aspects. While in most tropical regions these add up, leading to stronger nonlinear responses than expected from the single components, in some regions they cancel each other, resulting in little overall nonlinearity. This leads to strong regional differences in ENSO teleconnections.

We investigate factors influencing European winter (DJFM) air temperatures for the period 1979-2015 with the focus on changes during the recent period of rapid Arctic warming (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and backtrajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least 4 days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large-

The European Centre/Hamburg version 6 atmospheric model with a well‐defined stratosphere and an internally generated Quasi‐biennial oscillation (QBO) was used to study the relationship between the autumn Eurasian snow extent and the wintertime climate of the northern hemisphere. A positive snow cover anomaly was imposed over Eurasia in early autumn and held constant until spring. One hundred years of the snow anomaly run was compared with a 100 year control run. A dynamical response to the snow anomaly is seen in the northern polar stratosphere and troposphere during autumn and early winter, in line with previous modeling studies, and the monthly progression of the atmospheric anomalies follows the size of the surface forcing. However, this response is weaker, and occurs earlier in season, than that seen in observations. Considering the effect of QBO, we find a stratospheric vortex weakening during the easterly phase; however, the effect is weaker than that seen in observations. The strongest response of the polar vortex is found when both factors—the snow anomaly and the QBO phase—are considered together, with the response being close to an additive combination of the responses to the individual forcings. Although our study confirms the ability of snow cover variability to significantly influence the large‐scale circulation, it also demonstrates that the inclusion of a well‐resolved stratosphere is not a sufficient condition for reproducing the intensity and timing of the circulation response appearing in observations.