Energetic particle investigation using the ERNE instrument

During solar flares and coronal mass ejections, nuclei and electrons accelerated to high energies are injected into interplanetary space. These accelerated particles can be detected at the SOHO satellite by the ERNE instrument. From the data produced by the instrument, it is possible to identify the particles and to calculate their energy and direction of propagation. Depending on variable coronal/interplanetary conditions, different kinds of effects on the energetic particle transport can be predicted. The problems of interest include, for example, the effects of particle properties (mass, charge, energy, and propagation direction) on the particle transport, the particle energy changes in the transport process, and the effects the energetic particles have on the solar-wind plasma. The evolution of the distribution function of the energetic particles can be measured with ERNE to a better accuracy than ever before. This gives us the opportunity to contribute significantly to the modeling of interplanetary transport and acceleration. Once the acceleration/transport bias has been removed, the acceleration-site abundance of elements and their isotopes can be studied in detail and compared with spectroscopic observations.     

Evaluating direct and indirect evidence of climatic change by Hölder regularity and order pattern in time series

The several competing reconstructions of Northern Hemisphere temperature variability exists with partly conflicting evidence. Here we considered a specific problem of choosing “the best” reconstruction, in a frame of assumptions, that they are produced by smooth dynamical system as well as instrumental time series. Using some sophisticated measures of similarity, we could not match to all existing hemispheric paleoclimate reconstructions with hypothesis about any deterministic system which can produced its as typical projection of their trajectories. The results cast doubt on the conventional techniques frequently used to reconstruct past climate variability.