Forecasting extreme weather relies on the intrinsic predictability of the atmospheric flow, the model resolution needed to represent key processes, and the quality of the initial conditions used to initiate forecasts. In the seminar, I shall present a unified multiscale perspective showing how recent work from my group links these elements into a coherent framework for understanding predictability in the Mediterranean region.
We shall begin at the large scale, where dynamical-systems diagnostics show that Atlantic–European weather regimes are dynamically grounded states with characteristic stability and persistence. These regimes shape the background flow in which Mediterranean extremes develop, thereby defining the intrinsic limits and opportunities for extended-range predictability.1 This large-scale structure naturally informs how specific high-impact systems evolve.
At the synoptic scale, a newly developed Lagrangian framework allows us to analyze Mediterranean cyclones within their full potential-vorticity (PV) architecture. The same dynamical features that govern regime persistence help explain why some cyclones maintain long predictability horizons while others amplify uncertainty rapidly, depending on their depth, PV structure, and regional context.2 This insight flows directly into our analysis of compound “wet” and “windy’’ extremes, which preferentially arise during particularly persistent atmospheric configurations, effectively the multivariate expression of the dynamical behaviour captured at both the regime and cyclone scales.3
At the mesoscale, realizing this dynamical predictability in practice requires sufficient model resolution. High-resolution simulations are essential for capturing sea-breeze interactions, mountain–valley circulations, and other thermally driven flows that modulate extremes in the Eastern Mediterranean, features that coarse reanalysis systematically underestimate.4
Finally, we turn to improving the accuracy of initial conditions. Here, Syncope, a high-frequency acoustic sensing system, resolves boundary-layer gusts and turbulence structures that are overlooked by operational networks, providing more realistic near-surface information for initializing numerical weather prediction model simulations.5
Together, these studies form a consistent multiscale narrative showing how advances in dynamical understanding, high-resolution modelling, and improved boundary-layer observations can jointly advance the predictability of extreme weather.
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