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Detecting recurrent weather patterns and understanding the transitionsbetween such regimes are key to advancing our knowledge on the low-frequencyvariability of the atmosphere and have important implications in terms ofweather and climate-related risks. We adapt an analysis pipeline inspired byMarkov State Modelling and detect in an unsupervised manner the dominant wintermid-latitude Northern Hemisphere weather patterns in the Atlantic and Pacificsectors, defined by the slowest decaying modes of a suitable projection on adiscrete basis of the weather dynamics. When focusing on a longitudinal windowof 60$^\circ$, we recognise, first and foremost, a longitude-dependent estimateof the slowest relaxation times, which are often related with transitionsbetween blocked regimes and zonal flow. We analyze in detail the Atlantic andPacific sectors, finding, additionally, clear evidence of the strong connectionbetween blockings in the two regions. When the analysis is performed in abroader geographical region of the Atlantic sector, we detect teleconnectionpatterns like the North Atlantic Oscillation and a large-scale mode ofvariability alternating between Scandinavian and Greenland blocking. Theapproach proposed here has great potential for intercomparing climate modelsand for assessing the impact of climate change on the low-frequency variabilityof the atmosphere.

Agnostic detection of large-scale weather patterns in the northern hemisphere: from blockings to teleconnections