CLUSTER ANALYSIS OF LIGHTNING DISCHARGES: BASED ON VEREYA-MR NETWORK DATA
Аннотация и ключевые слова
Аннотация (русский):
Monitoring thunderstorm activity can help you solve many problems such as infrastructure facility protection, warning of hazardous phenomena associated with intense precipitation, study of conditions for the occurrence of thunderstorms and the degree of their influence on human activity, as well as the influence of thunderstorm activity on the formation of near-Earth space. We investigate the characteristics of thunderstorm cells by the method of cluster analysis. We take the Vereya-MR network data accumulated over a period from 2012 to 2018 as a basis. The Vereya-MR network considered in this paper is included in networks operating in the VLF-LF range (long and super-long radio waves). Reception points equipped with recording equipment, primary information processing systems, communication systems, precision time and positioning devices based on global satellite navigation systems are located throughout Russia. In the longitudinal-latitudinal thunderstorm distributions of interest, the dependence on the location of recording devices might be manifested. We compare the behavior of thunderstorms on the entire territory of the Russian Federation with those in the Baikal natural territory. We have established the power of thunderstorms over the Baikal region is lower. The daily variation in thunderstorm cells we obtained is consistent with the data from other works. There are no differences in other thunderstorm characteristics between the regions under study. This might be due to peculiarities of the analysis method. On the basis of the work performed, we propose sites for new points of our own lightning location network, as well as additional methods of cluster analysis.

Ключевые слова:
thunderstorms, cluster analysis, lightning discharges
Текст
Текст произведения (PDF): Читать Скачать
Список литературы

1. Argunov V.V. Quasi-periodic variations of the signal amplitude of lightning discharges which are passing over the earthquake epicenters. Vestnik SVFU [NEFU Bulletin]. 2018, no. 4 (66), pp. 38-49. (In Russian).

2. Blioh P. Whistling in space.Nauchno-populyarnyy fiziko-matematicheskiy zhurnal “Kvant” [Popular scientific physics and mathematics journal “Kvant”]. 1997, no. 3, pp. 3-8. (In Russian).

3. Kononov I.I., Yusupov I.E. Cluster analysis of lightning activity. Radiotekhnika i elektronika [Radio engineering and electronics]. 2004, vol. 49, no. 3, pp. 1-9. (In Russian).

4. Konstantinova D.A., Gorbatenko V.P. Dynamics of thunderstorm activity over the Western Siberia territory. INTEREKSPO GEO-SIBIR. [INTEREXPO GEO-SIBERIA]. Novosibirsk, Siberian State University of Geosystems and Technologies, 2016, vol. 4, no. 1, pp. 96-99. (In Russian).

5. Mareev E.A., Stasenko V.N., Shatalina M.V., Dement’eva S.O., Evtushenko A.A., Svechnikova E.K., Slyunyaev N.N. Russian studies of atmospheric electricity in 2015-2018. Izvestiya RAN. Fizika atmosfery i okeana [Izvestia RAN. Physics of the Atmosphere and Ocean], 2019, vol. 55, no. 6, pp. 79-93. DOI:https://doi.org/10.31857/S0002-351555679-93. (In Russian).

6. Moskovenko V.M., Znamenshhikov B.P., Zolotarev S.V. Application of the Vereya-MR lightning-direction finding system in the interests of the Russian electric power industry. Novoe v rossiyskoy elektroenergetike [New in the Russian power industry]. 2012, no. 2, pp. 15-23. (in Russian).

7. Panyukov B.D., Buduev D.V., Malov D.N. Systems for passive monitoring of thunderstorm activity. Vestnik YuUrGU [SUSU Bulletin]. 2003, no. 8, pp. 11-20. (In Russian).

8. Ripoll J.F., Farges T., Lay E.H., Cunningham G.S. Local and statistical maps of lightning-generated wave power density estimated at the Van Allen probes footprints from the World-Wide Lightning Location Network Database. Geophys. Res. Lett. 2019, vol. 46, no. 8, pp. 4122-4133. DOI:https://doi.org/10.1029/2018GL081146.

9. Rycroft M.J., Israelsson S., Price C. The global atmospheric electric circuit, solar activity and climate change. J. Atmos. Solar-Terr. Phys. 2000, vol. 62, no. 17-18, pp. 1563-1576. DOI:https://doi.org/10.1016/S1364-6826(00)00112-7.

10. Scholkmann F., Boss J., Wolf M. An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals. Algorithms. 2012, vol. 5, pp. 588-603. DOI:https://doi.org/10.3390/a5040588.

11. Shabaganova S.N., Kozlov V.I. Application of cluster analysis to identify thunderstorms. Dinamika slozhnykh sistem - XXI vek [Dynamics of complex systems - XXI century]. 2010, no. 2, pp. 43-47. (In Russian).

12. Shabaganova S.N., Karimov R.R., Kozlov V.I., Mullayarov V.A. Characteristics of thunderstorm cells according to observations in Yakutia. Meteorologiya i gidrologiya [Meteorology and Hydrology]. 2012, no. 12, pp. 35-43. (In Russian).

13. Sinkevich A.A., Michailovsky Yu.P., Abshaev A.M. Investigation of the relationship of electrical discharges frequency with radar characteristics of multicell CB. Trudy GGO [Proceedings of the MGO]. 2018, vol. 591, pp. 25-41. (In Russian).

14. Tarabukina L.D., Kozlov V.I. Comparison of measurements by several lightning radiopulses detectors. Vestnik SVFU [NEFU Bulletin]. 2018, no. 2 (64), pp. 77-86. (In Russian).

15. Yang J., Liu N., Sato M. Characteristics of thunderstorm structure and lightning activity causing negative and positive sprites. J. Geophys. Res.: Atmos. 2018, vol. 123, pp. 8190-8207. DOI:https://doi.org/10.1029/2017JD026759.

Войти или Создать
* Забыли пароль?