Since temperature extremes have a strong impact on environment and society, it is crucial to understand their underlying mechanisms. While their relationship to the largescale atmospheric circulation has been comprehensively investigated, the role of physical processes in the formation of air masses with extreme temperatures is less well understood. This study presents a Lagrangian analysis of the 0.1% most extreme six-hourly hot and cold events in three European regions (UK, Central Europe, Balkans) for the time period 1989-2009. The results provide insight into typical transport patterns and physical processes (adiabatic compression, radiation, surface heat fluxes) occurring along the trajectories of extreme temperature air masses. Cold events in Europe are most frequently induced by advection of cold air masses from the Arctic and Russia. The transport to the target region is characterized by a temperature increase caused by adiabatic compression and, in the maritime setting of the UK, also by diabatic heating due to surface sensible heat fluxes. Despite the warming along the trajectories, the extremeness of the associated 2 m temperature increases, due to the dislocation of the air mass to regions with a milder climate. Hot events are generally associated with weaker horizontal transport, but strong adiabatic warming and local temperature increase caused by enhanced radiation and surface heat fluxes. This in situ warming is particularly strong in Central Europe. Evaluating the temperature evolution along the trajectories reveals that hot and cold extremes develop on a similar time-scale of 2-3 days. This time-scale is mostly set by physical processes for hot extremes and controlled by advective transport for cold extremes. The diagnostics applied in this study lead to an improved process understanding that can provide a basis for more accurate predictions of temperature extremes.

The authors present a global climatology of tropical cyclones (TCs) that undergo extratropical transition (ET). ET is objectively defined based on a TC’s trajectory through the cyclone phase space (CPS), which is calculated using storm tracks from 1979–2017 best track data and geopotential height fields from reanalysis datasets. Two reanalyses are used and compared for this purpose, the Japanese 55-yr Reanalysis and the ECMWF interim reanalysis. The results are used to study the seasonal and geographical distributions of storms undergoing ET and interbasin differences in the statistics of ET occurrence. About 50% of all TCs in the North Atlantic and the western North Pacific undergo ET. In the Southern Hemisphere, ET fractions range from about 20% in the south Indian Ocean and the Australian region to 45% in the South Pacific. In the majority of ETs, TCs become thermally asymmetric before forming a cold core. However, a substantial fraction of TCs take the reverse pathway, developing a cold core before becoming thermally asymmetric. This pathway is most common in the eastern North Pacific and the North Atlantic. Different ET pathways can be linked to different geographical trajectories and environmental settings. In ETs over warmer sea surface temperatures, TCs tend to lose their thermal symmetry while still maintaining a warm core. Landfalls by TCs undergoing ET occur 3–4 times per year in the North Atlantic and 7–10 times per year in the western North Pacific, while coastal regions in the Australian region are affected once every 1–2 years.

This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-yr Reanalysis (JRA-55) or the ECMWF interim reanalysis (ERA-Interim). The resulting classification into ET storms and non-ET storms underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best track classification in the western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainly due to a higher false alarm rate, particularly in the eastern North Pacific. Overall, the results show that while the CPS-based classifications are good enough to be useful for many purposes, there is almost certainly room for improvement—in the representation of the storms in reanalyses, in our objective metrics of ET, and in our scientific understanding of the ET process.