Toward a phase-space cartography of the short- and medium-range predictability of weather regimes

Abstract

We compare the short- and medium-range predictability of weather regimes of a quasigeostrophicmodel as defined by a hierarchical cluster algorithm and a Lyapunov-based clusteringmethod recently introduced in the literature. Both procedures lead to weather regimesdisplaying very different predictability properties on the short and medium range bases. Whilethe former does not distinguish between stable and unstable weather regimes, the latter leadsto clusters which do not display a good medium range predictability. We introduce a newclustering method taking advantages of the two previous techniques. Its application in thecontext of the quasi-geostrophic model gives rise to regimes possessing at the same time a goodmedium range skill and well separated instability properties, indicating the possibility to builda systematic cartography of the short-term predictability of weather fields in phase space.