Characterizing Optimal Atlantic-European Blocking Precursors Using a Linear Inverse Model

Commonly studied atmospheric phenomena are the persistent, quasi-stationary high-pressure systems known as atmospheric blocking. During the boreal winter, these blocking anticyclones often lead to downstream cold temperature extremes and have been associated with processes varying on longer sub-seasonal timescales such as the Madden Julian oscillation (MJO) and the stratospheric polar vortex. The Atlantic-European region has recently been characterized by four types of blocked regimes, each with differing downstream sensible weather impacts and forecast skill. Key to better predictability of these Atlantic-European blocked weather regimes is identifying remote influences on sub-seasonal timescales.

Recently, linear inverse models (LIMs) have been successfully used to quantify slowly varying precursors to large-scale circulations patterns in the Northern Hemisphere. A LIM is an empirical model using lag covariance statistics to approximate dynamical properties and the evolution of specific atmospheric variables contained in a prescribed atmospheric state vector. The evolution of the state vector is approximated by separating slowly evolving linearized dynamics, as well as a linear approximation to nonlinear dynamics, from presumably unpredictable white-noise forcing. In this work, a LIM is employed to identify optimal precursors on sub-seasonal time scales for the life-cycle of Atlantic-European blocking events during the extended boreal winter (November-March). Included in the LIM are tropical heating anomalies related to the MJO or the El Niño-Southern Oscillation (ENSO), extratropical influences from Rossby wave activity, and the stratospheric polar vortex. Optimal extratropical and tropical precursors for the varying types of blocking events, as well as the LIM’s skill in forecasting European-Atlantic blocking, are presented.