COMPARISON OF AIR TEMPERATURE VARIATIONS ON THE AFRICAN CONTINENT AND THE SCHUMANN RESONANCE INTENSITY BY USING LONG-TERM ANTARCTIC OBSERVATIONS
Notice bibliographique
Résumé
PACS numbers: 92.60.Pw, 93.30.Bz, 93.30.Ca Purpose: Correlation study of long-term seasonal variations of intensity of the global electromagnetic (Schumann) resonance in the Earth-ionosphere cavity and the air temperature for the African center of the global thunderstorm activity. Design/methodology/approach: The correlation analysis of the time series was used. By using the 13-year data (since 2002 till 2015) of monitoring the natural ELF noise at the Ukrainian Antarctic Vernadsky station, the seasonal variations in intensity of the first Schumann resonance mode were derived, driven by the lightning activity in the African thunderstorm center. The average air temperature of the African continent over the same period was estimated from the data collected by the global network of meteorological stations. The area of maximum thunderstorm activity in Africa was approximated by a simple geometric figure. The correction was made for the source distance (the lightning discharges) when estimating the power of the first resonant maximum in the ELF signal. A stable relationship between the air temperature and the thunderstorm activity at the African continent was established as a result of correlation processing of seasonal variations in the air temperature and the field intensity. Findings: A one month lag between the annual maximum resonance intensity was found with regard to the maximum of air temperature relevant to the delay in the formation of thunderstorms during transition from the dry to the rainy seasons in Africa. The cross-correlation coefficient increases from 0.58 (without compensation) to 0.76 (delay compensated) when this delay is accounted for by the relevant shift of temperature variations. Conclusions: The technique developed can be used in finding the connection between the lightning activity of other thunderstorm centers and the corresponding regional temperature conditions. Such an approach might be used in developing the concept of Schumann resonance records as a “global thermometer”. Key words: extremely low frequency noises, Schumann resonance, global thermometer, African center of global thunderstorm activity, Antarctic Vernadsky station Manuscript submitted 26.05.2017 Radio phys. radio astron. 2017, 22(3): 201-211 REFERENCES 1. PRICE, C. and RIND, D., 1990. The effect of global warming on lightning frequencies. In: Proceedings of the AMS 16 th Conference on Severe Storms and Atmospheric Electricity. Alberta, AB,Canada: American Meteorological Society, p. 748. 2. WILLIAMS, E. R., 1992. The Shuman resonance: A global tropical thermometer. Science . vol. 256, no. 5060, pp. 1184–1186. DOI: https://doi.org/10.1126/science.256.5060.1184 3. PRICE, C., 2000. Evidence for a link between global lightning activity and upper tropospheric water vapor. Nature . vol. 406, no. 6793, pp. 290–293. DOI: https://doi.org/10.1038/35018543 4. NICKOLAENKO, A. P., HAYAKAWA, M., SEKIGUCHI, M. and HOBARA, Y., 2008. Comparison of the variations in the intensity of global electromagnetic resonance and ground surface temperature. Radiophys. Quantum Electron . vol. 51, no. 12, pp. 931–945. DOI: https://doi.org/10.1007/s11141-009-9097-z 5. JONES, P. D., WIGLEY T. M. L. and WRIGHT, P. B., 1986. Global temperature variations between 1861 and 1984. Nature . vol. 322, no. 6078, pp. 430–434. DOI: https://doi.org/10.1038/322430a0 6. SEKIGUCHI, M., HAYAKAWA, M., NICKOLAENKO, A. P. and HOBARA, Y., 2006. Evidence of a link between the intensity of Schumann resonance and global surface temperature. Ann. Geophys . vol. 24, is 7, pp. 1809–1817. DOI: https://doi.org/10.5194/angeo-24-1809-2006 7. HOBARA, Y., HARADA, T., OHTA, K., SEKIGUCHI ,M. and HAYAKAWA, M., 2011. A study of global temperature and thunderstorm activity by using the data of Schumann resonance observed at Nakatsugawa, Japan. J. Atmos. Electr . vol. 31, no. 2, pp. 111–119. DOI: https://doi.org/10.1541/jae.31. 8. PRICE, C.and ASFUR, M., 2006. Can lightning observations be used as an indicator of upper-troposheric water-vapor variability? Bull. Am. Meteorol. Soc . vol. 87, no. 3, pp. 291–298. DOI: https://doi.org/10.1175/BAMS-87-3-291 9. PRICE, C., 2016. ELF electromagnetic waves from lightning: the Shumann resonances. Atmosphere. vol. 7, no. 9, id. 116. DOI: https://doi.org/10.3390/atmos7090116 10. LYTVYNENKO, L. N. and YAMPOLSKI, YU. M., eds., 2005. Electromagnetic manifestations of geophysical effects in Antarctica . Kharkiv: IRA NAS of Ukraine, NASCU MES of Ukraint Publ. (in Russian). 11. KOLOSKOV, A. V., BEZRODNY, V. G., BUDANOV, O. V., PAZNUKHOV, V. E. and YAMPOLSKI, Y. M., 2005. Polarization Monitoring of the Schumann Resonances in the Antarctic and Restoring of the Characteristics of the Global Thunderstorm Activity. Radio Phys. Radio Astron . vol. 10, no. 1, pp. 11–29 (in Russian). 12. BLIOKH, P. V., NICKOLAENKO A. P. and FILIPPOV, YU. F., 1977. Global electromagnetic resonances in the Earth-ionosphere cavity . Kiev: Naukova Dumka Publ. (in Russian). 13. BLIOKH, P. V., NICKOLAENKO A. P. and FILIPPOV, YU. F., 1980. Schumann resonances in the Earth-ionosphere cavity . Oxford, UK: Peter Peregrinus. 14. NICKOLAENKO, A. and HAYAKAWA, M., 2014. Schumann Resonance for Tyros. Essentials of Global Electromagnetic Resonance in the Earth–Ionosphere Cavity . Tokyo–Heidelberg–N. Y. –Dordrecht–London: Springer. 15. NICKOLAENKO, A. P., SHVETS, A. V. and HAYAKAWA, M., 2016. Extremely Low Frequency (ELF) Radio Wave Propagation: A review. Int. J. Electron. Appl. Res . vol. 3 is. 2, pp. 1–91. 16. NICKOLAENKO, A. P., SHVETS, A. V. and HAYAKAWA, M., 2016. Propagation at Extremely Low-Frequency Radio Waves. In: J. WEBSTER, ed. Wiley Encyclopedia of Electrical and Electronics Engineering . Hoboken, USA: John Wiley & Sons, Inc., pp. 1–20. DOI: https://doi.org/10.1002/047134608X.W1257.pub2
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».