A Climatology of Summer-Time Arctic Cyclones Using a Modified Phase Space

Arctic cyclones are the major weather hazard in the summer-time Arctic, associated with strong winds and the break-up and melting of sea ice. While conceptual models for mid-latitude cyclones are well established, the structural evolution of Arctic cyclones is not as well understood. We perform a climatological (1979-2021) analysis of summer-time Arctic cyclone structure in reanalysis data using a modified form of the Hart (2003) cyclone phase space. The phase space is comprised of two parameters representing aspects of cyclone structure, specifically the low-level baroclinicity and the vertical vorticity gradient (or equivalently, the extent to which the cyclone is warm-core or cold-core). Motivated by some notable Arctic cyclone cases, a classification scheme for Arctic cyclones is proposed, dependent on whether the vorticity structure during development is low-level-dominant (LLD) or upper-level-dominant (ULD). 65.5% of the cyclones are found to have LLD development, whilst 34.5% have ULD development. It is found that the LLD and ULD cyclone subsets follow distinct trajectories in the phase space. The LLD cyclones exhibit higher baroclinicity and warm-core asymmetric structures during growth, whereas the ULD cyclones exhibit more cold-core structures. However, a transition to a persistent cold-core axisymmetric structure after maturity is characteristic of summer-time Arctic cyclones, regardless of structure during development. LLD cyclones are on average stronger and preferentially track on the Russian coastline, in association with high baroclinicity in summer. In contrast, ULD cyclones tend to be longer-lived, and preferentially track on the Pacific side of the Arctic Ocean basin. This is thought to be related to cyclone interactions with tropopause polar vortices, which most commonly occur in the North American sector of the Arctic Ocean. This study provides a platform for further research into different classes of Arctic cyclones and ultimately for developing conceptual models, which are key for anticipating associated hazardous weather.