Method of analysis of solar activity geoeffectiveness
| Назва | Method of analysis of solar activity geoeffectiveness |
| Назва англійською | Method of analysis of solar activity geoeffectiveness |
| Автори | Danylo Ivantyshyn |
| Принадлежність | Lviv Polytechnic National University, Lviv, Ukraine |
| Бібліографічний опис | Method of analysis of solar activity geoeffectiveness / Danylo Ivantyshyn // Scientific Journal of TNTU. — Tern.: TNTU, 2024. — Vol 113. — No 1. — P. 111–118. |
| Bibliographic description: | Ivantyshyn D. (2024) Method of analysis of solar activity geoeffectiveness. Scientific Journal of TNTU (Tern.), vol 113, no 1, pp. 111–118. |
| DOI: | https://doi.org/10.33108/visnyk_tntu2024.01.111 |
| УДК | 520.8 |
| Ключові слова | solar activity geoeffectiveness, data mining, spatial data aggregation, geoeffectiveness classification. |
The method of analysis of the solar activity geoeffectiveness and assessing its level based on the mining spatiotemporal data of geophysical field disturbances caused by the activity of the Sun is developed. At the first stage of the method, solar activity is analysed. When solar disturbances are detected, the information about solar activity and the geophysical disturbances caused by it are further jointly analysed. Further, the raw data of geophysical fields are cleaned and converted into a format suitable for analysis, as well as their time alignment is carried out, which is crucial when comparing or combining time series from different sources and with different sampling rates. After that, the data is normalized, since the data values of the geophysical fields, which are used to analysis of solar activity geoeffectiveness, are measured on different scales, have different dimensions, which requires their scaling to the conventionally general scale of the comparable range. At the next stage of the method, spatial data aggregation is implemented, which ensures the process of combining the numerical values of a group of resources into one representative value for a given period of time. As a result of aggregation of experimental data of geophysical fields, we obtain a time series of average values of these fields for each moment of time. The analysis of the solar activity geoeffectiveness on the basis of aggregated data makes it possible to estimate its level taking into account the index Dst of the geomagnetic storm, the geomagnetic index of the polar electric current AE, the magnitude of natural atmospheric infrasound and the gradient of the electrical potential of the atmosphere PG. The scale of classification of the solar activity geoeffectiveness is in the range [0, 1]. An event is considered geoeffectiveness if the aggregated signal reaches a threshold value of 0.25 on the geoeffectiveness scale. Geoeffectiveness of solar activity is classified as weak, moderate or strong if the value of the aggregated signal is, respectively, 0,25AS<0,5; 0,5AS<0,75; 0,75AS1,0. | |
| ISSN: | 2522-4433 |
| Перелік літератури |
1. Gopalswamy N. Solar connections of geoeffective magnetic structures. Journal of Atmospheric and Solar-Terrestrial Physics. 2008. Vol. 70. P. 2078–2100. URL: https://doi.org/10.1016/j.jastp.2008.06.010.
2. Gopalswamy N., Yashiro S., Akiyama S. Geoeffectiveness of halo coronal mass ejections. J. Geophys. Res. Earth Surf. 2007. Vol. 112. URL: https://doi.org/10.1029/2006JA012149
3. D.-C. Talpeanu, S. Poedts, E. D’Huys and M. Mierla. Study of the propagation, in situ signatures, and geoeffectiveness of shear-induced coronal mass ejections in different solar winds. A&A. 2022. Vol. 658. A56. URL: https://doi.org/10.1051/0004-6361/202141977.
4. Cid C., Cremades H., Aran A., Mandrini C., Sanahuja B., Schmieder B., Menvielle M., Rodriguez, L., Saiz E., Cerrato Y., et al. Can a halo CME from the limb be geoeffective? J. Geophys. Res. 2012. Vol. 117. A11102. URL: https://doi.org/10.1029/2012JA017536.
5. Menvielle M., Marchaudon A. Geomagnetic Indices in Solar-Terrestrial Physics and Space Weather. Space Weather. Astrophysics and Space Science Library. 2007. Vol. 344. Springer. Dordrecht. P. 277–288. URL: https://doi.org/10.1007/1-4020-5446-7_24.
6. Verbanac G., Živković S., Vršnak B., Bandić M. and Hojsak T. Comparison of geoeffectiveness of coronal mass ejections and corotating interaction regions. A&A. 2013. Vol. 558. A85. URL: https://doi.org/ 10.1051/0004-6361/201220417.
7. Koshovyy V., Ivantyshyn O., Mezentsev V., Rusyn B., Kalinichenko M. Influence of active cosmic factors on the dynamics of natural infrasound in the Earth’s atmosphere. Rom. Journ. Phys., 2020. Vol. 65. 813. URL: https://rjp.nipne.ro/2020_65_9-10/RomJPhys.65.813.pdf.
8. Tacza J., Odzimek A., Tueros Cuadros E., Raulin J.-P., Kubicki M., Fernandez G., & Marun A. Investigating effects of solar proton events and Forbush decreases on ground-level potential gradient recorded at middle and low latitudes and different altitudes. Space Weather. 2022. Vol. 20. e2021SW002944. URL: https://doi.org/10.1029/2021SW002944.
9. Elhalel G., Yair Y., Nicoll K., Price C., Reuveni Y., Harrison RG: Influence of short-term solar disturbances on the fair weather conversion current. J. Space Weather Space Clim. 2014. 4, A26. URL: https://doi.org/ 10.1051/swsc/2014022.
10. Ivantyshyn D., Burov Ye. Rozroblennia bazy danykh dlia intelektualnoi systemy doslidzhennia parametriv kosmichnoi pohody. Visnyk Informatsiini systemy ta merezhi. 2023. No. 13. P. 329–337. [In Ukrainian].
11. Han J., Kamber M., Pei J. Data mining: concepts and techniques. Elsevier Science. 2012. 3rd ed. p. cm. ISBN 978-0-12-381479-1. P. 744.
12. F. Cheng, C. Meiling, W. Xinghua, W. Jiayuan, H. Bufu. A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data. Frontiers in Energy Research. 2021. Vol. 9. URL: https://doi.org/10.3389/fenrg.2021.652801.
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| References: |
1. Gopalswamy N. Solar connections of geoeffective magnetic structures. Journal of Atmospheric and Solar-Terrestrial Physics. 2008. Vol. 70. P. 2078–2100. URL: https://doi.org/10.1016/j.jastp.2008.06.010.
2. Gopalswamy N., Yashiro S., Akiyama S. Geoeffectiveness of halo coronal mass ejections. J. Geophys. Res. Earth Surf. 2007. Vol. 112. URL: https://doi.org/10.1029/2006JA012149
3. D.-C. Talpeanu, S. Poedts, E. D’Huys and M. Mierla. Study of the propagation, in situ signatures, and geoeffectiveness of shear-induced coronal mass ejections in different solar winds. A&A. 2022. Vol. 658. A56. URL: https://doi.org/10.1051/0004-6361/202141977.
4. Cid C., Cremades H., Aran A., Mandrini C., Sanahuja B., Schmieder B., Menvielle M., Rodriguez, L., Saiz E., Cerrato Y., et al. Can a halo CME from the limb be geoeffective? J. Geophys. Res. 2012. Vol. 117. A11102. URL: https://doi.org/10.1029/2012JA017536.
5. Menvielle M., Marchaudon A. Geomagnetic Indices in Solar-Terrestrial Physics and Space Weather. Space Weather. Astrophysics and Space Science Library. 2007. Vol. 344. Springer. Dordrecht. P. 277–288. URL: https://doi.org/10.1007/1-4020-5446-7_24.
6. Verbanac G., Živković S., Vršnak B., Bandić M. and Hojsak T. Comparison of geoeffectiveness of coronal mass ejections and corotating interaction regions. A&A. 2013. Vol. 558. A85. URL: https://doi.org/ 10.1051/0004-6361/201220417.
7. Koshovyy V., Ivantyshyn O., Mezentsev V., Rusyn B., Kalinichenko M. Influence of active cosmic factors on the dynamics of natural infrasound in the Earth’s atmosphere. Rom. Journ. Phys., 2020. Vol. 65. 813. URL: https://rjp.nipne.ro/2020_65_9-10/RomJPhys.65.813.pdf.
8. Tacza J., Odzimek A., Tueros Cuadros E., Raulin J.-P., Kubicki M., Fernandez G., & Marun A. Investigating effects of solar proton events and Forbush decreases on ground-level potential gradient recorded at middle and low latitudes and different altitudes. Space Weather. 2022. Vol. 20. e2021SW002944. URL: https://doi.org/10.1029/2021SW002944.
9. Elhalel G., Yair Y., Nicoll K., Price C., Reuveni Y., Harrison RG: Influence of short-term solar disturbances on the fair weather conversion current. J. Space Weather Space Clim. 2014. 4, A26. URL: https://doi.org/ 10.1051/swsc/2014022.
10. Ivantyshyn D., Burov Ye. Rozroblennia bazy danykh dlia intelektualnoi systemy doslidzhennia parametriv kosmichnoi pohody. Visnyk Informatsiini systemy ta merezhi. 2023. No. 13. P. 329–337. [In Ukrainian].
11. Han J., Kamber M., Pei J. Data mining: concepts and techniques. Elsevier Science. 2012. 3rd ed. p. cm. ISBN 978-0-12-381479-1. P. 744.
12. F. Cheng, C. Meiling, W. Xinghua, W. Jiayuan, H. Bufu. A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data. Frontiers in Energy Research. 2021. Vol. 9. URL: https://doi.org/10.3389/fenrg.2021.652801.
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