Comprehensive analysis of tornado statistics in comparison to earthquakes: intensity and temporal behaviour

Tornadoes and earthquakes are characterised by a high variability in their properties concerning intensity, geometric properties and temporal behaviour. Earthquakes are known for power-law behaviour in their intensity (Gutenberg–Richter law) and temporal statistics (e.g. Omori law and interevent waiting times). The observed similarity of high variability of these two phenomena motivated us to compare the statistical behaviour of tornadoes using seismological methods and quest for power-law behaviour. In general, the statistics of tornadoes show power-law behaviour partly coextensive with characteristic scales when the temporal resolution is high (10 to 60 min). These characteristic scales match with the typical diurnal behaviour of tornadoes, which is characterised by a maximum of tornado occurrences in the late afternoon hours. Furthermore, the distributions support the observation that tornadoes cluster in time. Finally, we shortly discuss a possible similar underlying structure composed of heterogeneous, coupled, interactive threshold oscillators that possibly explains the observed behaviour

Solar Coronal Plumes

Polar plumes are thin long ray-like structures that project beyond the limb of the Sun polar regions, maintaining their identity over distances of several solar radii. Plumes have been first observed in white-light (WL) images of the Sun, but, with the advent of the space era, they have been identified also in X-ray and UV wavelengths (XUV) and, possibly, even in in situ data. This review traces the history of plumes, from the time they have been first imaged, to the complex means by which nowadays we attempt to reconstruct their 3-D structure. Spectroscopic techniques allowed us also to infer the physical parameters of plumes and estimate their electron and kinetic temperatures and their densities. However, perhaps the most interesting problem we need to solve is the role they cover in the solar wind origin and acceleration: Does the solar wind emanate from plumes or from the ambient coronal hole wherein they are embedded? Do plumes have a role in solar wind acceleration and mass loading? Answers to these questions are still somewhat ambiguous and theoretical modeling does not provide definite answers either. Recent data, with an unprecedented high spatial and temporal resolution, provide new information on the fine structure of plumes, their temporal evolution and relationship with other transient phenomena that may shed further light on these elusive features

Statistical and dynamical analyses of atmospheric blocking with an idealized point vortex model

We investigate a reduced point vortex model for a statistical and dynamical analysis of atmospheric blocking phenomena. Thereby, we consider high-over-low and omega blocking as equilibria of two and three point vortices. Based on fields of the kinematic vorticity number, two novel methods, the contour and the trapezoid method, are introduced in order to identify the vortices that form the blocking pattern as well as their local positions and circulation magnitudes. Using an instantaneous blocking index a total number of 347 blocking periods were identified in NCEP-NCAR Reanalysis data for the Euro-Atlantic region during the time period 1990-2012. This procedure provides the basis to corroborate the applicability of the point vortex model to atmospheric blocking in a statistical framework. The calculated translation speed of the point vortex systems associated with the atmospheric blocking appears to match the zonal mean velocity reasonably well. This model explains the stationary behaviour of blocking patterns. A comparison between the theoretical and a statistical model further reveals that the circulation of the blocking high follows the principles of the point vortex model to a large extent. However, the low-pressure-systems behave more variable. Moreover, the stability of point vortex equilibria is analysed regarding the relative distances by considering linear stability analysis and simulations. This reveals, that the point vortex blocking model corresponds to an unstable saddle point. Also, a possible transition between high-overlow and omega blocking situations is indicated. Furthermore, we take viscosity and a Brownian motion into account to simulate the influence of the smaller, subgrid-scale disturbances. As a result a clustering near the equilibrium state emerges indicating the persistence of the atmospheric blocking pattern

Occurrence and transition probabilities of omega and high-over-low blocking in the Euro-Atlantic region

Stationary, long-lasting blocked weather patterns can lead to extreme conditions such as anomalously high temperatures or heavy rainfall. The exact locations of such extremes depend on the location of the vortices that form the block. There are two main types of blocking: (i) a high-over-low block with a high located poleward of an isolated low and (ii) an omega block with two lows that lie southeast and southwest of the blocking high in the Northern Hemisphere. In this work, we refine a novel method based on the kinematic vorticity number and the point vortex theory that allows us to distinguish between these two blocking types. Based on the National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis 2 data, we study the trends of the occurrence probability and the onset (formation), decay (offset) and transition probabilities of high-over-low and omega blocking in the 30-year period from 1990 to 2019 in the Northern Hemisphere (90∘ W–90∘ E) and in the Euro-Atlantic sector (40∘ W–30∘ E). First, we use logistic regression to investigate long-term changes in blocking probabilities for full years, seasons and months. While trends are small for annual values, changes in occurrence probability are more visible and also more diverse when broken down to seasonal and monthly resolution, showing a prominent increase in February and March and a decrease in December. A three-state multinomial regression describing the occurrence of omega and high-over-low blocking reveals different trends for both types. Particularly the February and December changes are dominated by the omega blocking type. Additionally, we use Markov models to describe transition probabilities for a two-state (unblocked, blocked) and a three-state (unblocked, omega block, high-over-low block) Markov model. We find the largest changes in transition probabilities in the summer season, where the transition probabilities towards omega blocks significantly increase, while the unblocked state becomes less probable. Prominent in winter are decreasing probabilities for transitions from omega to high-over-low and persistence of the latter. Moreover, we show that omega blocking is more likely to occur and to be more persistent than the high-over-low blocking pattern