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In the past few decades, boreal summers have been characterized by an increasing number of extreme weather events in the Northern Hemisphere extratropics, including persistent heat waves, droughts and heavy rainfall events with significant social, economic, and environmental impacts. Many of these events have been associated with the presence of anomalous large-scale atmospheric circulation patterns, in particular, persistent blocking situations, i.e., nearly stationary spatial patterns of air pressure. To contribute to a better understanding of the emergence and dynamical properties of such situations, we construct complex networks representing the atmospheric circulation based on Lagrangian trajectory data of passive tracers advected within the atmospheric flow. For these Lagrangian flow networks, we study the spatial patterns of selected node properties prior to, during, and after different atmospheric blocking events in Northern Hemisphere summer. We highlight the specific network characteristics associated with the sequence of strong blocking episodes over Europe during summer 2010 as an illustrative example. Our results demonstrate the ability of the node degree, entropy, and harmonic closeness centrality based on outgoing links to trace important spatiotemporal characteristics of atmospheric blocking events. In particular, all three measures capture the effective separation of the stationary pressure cell forming the blocking high from the normal westerly flow and the deviation of the main atmospheric currents around it. Our results suggest the utility of further exploiting the Lagrangian flow network approach to atmospheric circulation in future targeted diagnostic and prognostic studies.
As the frequency and severity of mid-latitude extreme weather events such as heat waves, droughts, and heavy rainfall events are projected to further increase with ongoing climate change, developing reliable forecasts of such events is becoming a gradually more pressing issue. However, while the quality of predictions has been improving considerably on short-term (up to 2 weeks lead time) and seasonal time scales (beyond 3 months), sub-seasonal forecasting (from 2 weeks to about 3 months) remains a challenging task. This results in part from a limited understanding and representation of phenomena that could potentially increase the predictability at these sub-seasonal scales. One type of such phenomena is atmospheric blocking events. These large-scale, nearly stationary, atmospheric pressure patterns can remain in place for several days or even weeks, disturbing the usual westerly driven circulation and the resulting succession of weather regimes over the mid-latitudes. Despite numerous studies, a comprehensive theory explaining the emergence of blocking-related circulation anomalies and allowing an early forecasting of incipient blocking situations remains to be found. In this work, we utilize a network-based approach, so-called Lagrangian flow networks, for studying the atmospheric circulation associated with blocking situations during Northern hemisphere summer. We discuss the ability of different network measures to detect and track important spatial characteristics of blocking events, suggesting the potential of complex network approaches to provide key elements for future diagnostic and prognostic studies of atmospheric blocking events
