Space weather and hurricanes Irma, Jose and Katia
Аутори
Vyklyuk, YaroslavRadovanović, Milan M.
Milovanović, Boško
Milenković, Milan
Petrović, Marko
Doljak, Dejan
Malinović-Milićević, Slavica
Vuković, Natalia
Vujko, Aleksandra
Matsiuk, Nataliia
Mukherjee, Saumitra
Остала ауторства
Brinks, EliasЧланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calcu...lations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes.
Кључне речи:
charged particles / atmospheric disturbances / artificial neural network / hurricanesИзвор:
Astrophysics and Space Science, 2019, 364, 154Издавач:
- Switzerland : Springer Nature
Финансирање / пројекти:
- Географија Србије (RS-47007)
DOI: 10.1007/s10509-019-3646-5
ISSN: 0004-640X
WoS: 000486264300003
Scopus: 2-s2.0-85073049971
Институција/група
Географски институт „Јован Цвијић“ САНУ / Geographical Institute Jovan Cvijić SASATY - JOUR AU - Vyklyuk, Yaroslav AU - Radovanović, Milan M. AU - Milovanović, Boško AU - Milenković, Milan AU - Petrović, Marko AU - Doljak, Dejan AU - Malinović-Milićević, Slavica AU - Vuković, Natalia AU - Vujko, Aleksandra AU - Matsiuk, Nataliia AU - Mukherjee, Saumitra PY - 2019 UR - https://dais.sanu.ac.rs/123456789/13408 AB - This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calculations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes. PB - Switzerland : Springer Nature T2 - Astrophysics and Space Science T1 - Space weather and hurricanes Irma, Jose and Katia VL - 364 IS - 154 DO - 10.1007/s10509-019-3646-5 UR - https://hdl.handle.net/21.15107/rcub_dais_13408 ER -
@article{ author = "Vyklyuk, Yaroslav and Radovanović, Milan M. and Milovanović, Boško and Milenković, Milan and Petrović, Marko and Doljak, Dejan and Malinović-Milićević, Slavica and Vuković, Natalia and Vujko, Aleksandra and Matsiuk, Nataliia and Mukherjee, Saumitra", year = "2019", abstract = "This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calculations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes.", publisher = "Switzerland : Springer Nature", journal = "Astrophysics and Space Science", title = "Space weather and hurricanes Irma, Jose and Katia", volume = "364", number = "154", doi = "10.1007/s10509-019-3646-5", url = "https://hdl.handle.net/21.15107/rcub_dais_13408" }
Vyklyuk, Y., Radovanović, M. M., Milovanović, B., Milenković, M., Petrović, M., Doljak, D., Malinović-Milićević, S., Vuković, N., Vujko, A., Matsiuk, N.,& Mukherjee, S.. (2019). Space weather and hurricanes Irma, Jose and Katia. in Astrophysics and Space Science Switzerland : Springer Nature., 364(154). https://doi.org/10.1007/s10509-019-3646-5 https://hdl.handle.net/21.15107/rcub_dais_13408
Vyklyuk Y, Radovanović MM, Milovanović B, Milenković M, Petrović M, Doljak D, Malinović-Milićević S, Vuković N, Vujko A, Matsiuk N, Mukherjee S. Space weather and hurricanes Irma, Jose and Katia. in Astrophysics and Space Science. 2019;364(154). doi:10.1007/s10509-019-3646-5 https://hdl.handle.net/21.15107/rcub_dais_13408 .
Vyklyuk, Yaroslav, Radovanović, Milan M., Milovanović, Boško, Milenković, Milan, Petrović, Marko, Doljak, Dejan, Malinović-Milićević, Slavica, Vuković, Natalia, Vujko, Aleksandra, Matsiuk, Nataliia, Mukherjee, Saumitra, "Space weather and hurricanes Irma, Jose and Katia" in Astrophysics and Space Science, 364, no. 154 (2019), https://doi.org/10.1007/s10509-019-3646-5 ., https://hdl.handle.net/21.15107/rcub_dais_13408 .