arXiv subjects

Anatoly Petrukovich

Publications and source records attributed to Anatoly Petrukovich.

3 recordsLinked to original sources

arXiv2024

Embedded coherent structures from MHD to sub-ion scales in turbulent solar wind at 0.17 au

We study intermittent coherent structures in solar wind magnetic turbulence from MHD to kinetic plasma scales using Parker Solar Probe data during its first perihelion (at 0.17 au), when the satellite was in the Alfvénic slow wind of 340 km/s. The coherent structures are energetic events localized in time and covering wide range of scales. We detect them using Morlet wavelets. For the first time, we apply a multi-scale analyses in physical space to study these structures. At MHD scales within the inertial range, times scales $τ\in (1, 10^{2} )$ s, we find (i) current sheets including switchback boundaries and (ii) Alfvén vortices. Within these events, there are embedded structures at smaller scales: typically Alfvén vortices at ion scales, $τ\in (0.08, 1)$ s, and a compressible vortices at sub-ion scales, $τ\in (8,80)$ ms. The number of coherent structures grows toward smaller scales: we observe about $\sim 200$ events during 5 h time interval at MHD scales, $\sim 10^{3}$ events ai ion scales and $\sim 10^{4}$ events at sub-ion scales. In general, there are multiple structures of ion and sub-ion scales embedded within one MHD structure. There are also examples of ion and sub-ion scales structures outside of MHD structures. To quantify the relative importance of different type of structures, we do a statistical comparison of the observed structures with the expectations of models of the current sheets and vortices. This comparison is based on amplitude anisotropy of magnetic fluctuations within the structures. The results show the dominance of Alfvén vortices at all scales in contrast to the widespread view of dominance of current sheets. This means that Alfvén vortices are important building blocs of solar wind turbulence.

astro-ph.SR↗

arXiv2020

Clustering of fast Coronal Mass Ejections during the solar cycles 23 and 24 and implications for CME-CME interactions

We study the clustering properties of fast Coronal Mass Ejections (CMEs) that occurred during solar cycles 23 and 24. We apply two methods: the Max spectrum method can detect the predominant clusters and the de-clustering threshold time method provides details on the typical clustering properties and time scales. Our analysis shows that during the different phases of solar cycles 23 and 24, CMEs with speed $\geq 1000\ km/s$ preferentially occur as isolated events and in clusters with on average two members. However, clusters with more members appear particularly during the maximum phases of the solar cycles. Over the total period and in the maximum phases of solar cycles 23 and 24, about 50% are isolated events, 18% (12%) occur in clusters with 2 (3) members, and another 20% in larger clusters $\geq 4$, whereas in solar minimum fast CMEs tend to occur more frequently as isolated events (62%). During different solar cycle phases, the typical de-clustering time scales of fast CMEs are $τ_c=28-32\ hrs$, irrespective of the very different occurrence frequencies of CMEs during solar minimum and maximum. These findings suggest that $τ_c$ for extreme events may reflect the characteristic energy build-up time for large flare and CME-prolific active ARs. Associating statistically the clustering properties of fast CMEs with the Disturbance storm index Dst at Earth suggests that fast CMEs occuring in clusters tend to produce larger geomagnetic storms than isolated fast CMEs. This may be related to CME-CME interaction producing a more complex and stronger interaction with the Earth magnetosphere.

astro-ph.SR↗

arXiv2018

Geomagnetic storm forecasting service StormFocus: 5 years online

Forecasting geomagnetic storms is highly important for many space weather applications. In this study we review performance of the geomagnetic storm forecasting service StormFocus during 2011--2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by $Dst$ index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.

physics.space-ph↗