г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
г. Москва и Московская область, Россия
УДК 55 Геология. Геологические и геофизические науки
УДК 550.34 Сейсмология
УДК 550.383 Главное магнитное поле Земли
ГРНТИ 89.00 КОСМИЧЕСКИЕ ИССЛЕДОВАНИЯ
ГРНТИ 89.57 Исследования Земли из космоса
ГРНТИ 89.53 Геофизические исследования космическими средствами
ГРНТИ 37.01 Общие вопросы геофизики
ГРНТИ 37.15 Геомагнетизм и высокие слои атмосферы
ГРНТИ 37.25 Океанология
ГРНТИ 37.31 Физика Земли
ГРНТИ 38.01 Общие вопросы геологии
ГРНТИ 36.00 ГЕОДЕЗИЯ. КАРТОГРАФИЯ
ГРНТИ 37.00 ГЕОФИЗИКА
ГРНТИ 38.00 ГЕОЛОГИЯ
ГРНТИ 39.00 ГЕОГРАФИЯ
ГРНТИ 52.00 ГОРНОЕ ДЕЛО
ОКСО 05.00.00 Науки о Земле
ББК 26 Науки о Земле
ТБК 63 Науки о Земле. Экология
BISAC SCI SCIENCE
Research was conducted using satellite data to study variations in parameters of various geophysical fields manifested in the lithosphere, atmosphere, and ionosphere during the preparation and occurrence of destructive earthquakes of 6 ≤ M ≤ 7.8 in Türkiye in February 2023. Precursor manifestations of these seismic events were satellite-detected in the form of anomalies in parameters of various geophysical fields, including: lineament systems, surface skin temperature and surface air temperature, relative humidity, latent heat flux, integrated flux of outgoing longwave radiation, altitude changes in ionospheric electron density, total electron content of the ionosphere, as well as aerosol optical depth. It was found that the anomalies of all studied geophysical fields detected using satellite data manifested most intensively during the period 3–13 days before the onset of seismic events.
Satellite data, anomalies of geophysical fields, earthquake precursors, geodynamics, lineaments, thermal fields, ionosphere, aerosol
1. Akhoondzadeh, M. (2015), Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010, Advances in Space Research, 55(7), 1754–1763, https://doi.org/10.1016/j.asr.2015.01.016.
2. Akhoondzadeh, M., and D. Marchetti (2023), Study of the Preparation Phase of Turkey’s Powerful Earthquake (6 February 2023) by a Geophysical Multi-Parametric Fuzzy Inference System, Remote Sensing, 15(9), 2224, https://doi.org/10.3390/rs15092224.
3. Bondur, V. G., and V. M. Smirnov (2005), Method for monitoring seismically hazardous territories by ionospheric variations recorded by satellite navigation systems, Doklady Earth Sciences, 403(5), 736–740, EDN: LJHLVP.
4. Bondur, V. G., I. A. Garagash, M. B. Gokhberg, and M. V. Rodkin (2016), The evolution of the stress state in Southern California based on the geomechanical model and current seismicity, Izvestiya, Physics of the Solid Earth, 52(1), 117–128, https://doi.org/10.1134/S1069351316010043.
5. Bondur, V. G., M. N. Tsidilina, E. V. Gaponova, and O. S. Voronova (2022), Combined Analysis of Anomalous Variations in Various Geophysical Fields during Preparation of the M5.6 Earthquake near Lake Baikal on September 22, 2020, Based on Satellite Data, Izvestiya, Atmospheric and Oceanic Physics, 58(12), 1532–1545, https://doi.org/10.1134/S0001433822120052.
6. Bondur, V. G., T. N. Chimitdorzhiev, and A. V. Dmitriev (2023), Anomalous Geodynamics before the 2023 Earthquake in Turkey According to Radar Interferometry 2018-2023, Issledovanie Zemli iz Kosmosa, 2023(3), 3–12, https://doi.org/10.31857/S0205961423030090 (in Russian).
7. Cervone, G., R. P. Singh, M. Kafatos, and C. Yu (2005), Wavelet maxima curves of surface latent heat flux anomalies associated with Indian earthquakes, Natural Hazards and Earth System Sciences, 5(1), 87–99, https://doi.org/10.5194/nhess-5-87-2005.
8. Dal Zilio, L., and J.-P. Ampuero (2023), Earthquake doublet in Turkey and Syria, Communications Earth & Environment, 4(1), https://doi.org/10.1038/s43247-023-00747-z.
9. Dey, S., and R. P. Singh (2003), Surface latent heat flux as an earthquake precursor, Natural Hazards and Earth System Sciences, 3(6), 749–755, https://doi.org/10.5194/nhess-3-749-2003.
10. Federal Research Center Geophysical Survey of the RAS (2023), Catalog of the last earthquakes from 2000 to 2023, http://www.ceme.gsras.ru (in Russian), (visited on 12/08/2023).
11. Ganguly, N. D. (2016), Atmospheric changes observed during April 2015 Nepal earthquake, Journal of Atmospheric and Solar-Terrestrial Physics, 140, 16–22, https://doi.org/10.1016/j.jastp.2016.01.017.
12. Ghosh, S., S. Sasmal, M. Naja, S. Potirakis, and M. Hayakawa (2023), Study of aerosol anomaly associated with large earthquakes (M>6), Advances in Space Research, 71(1), 129–143, https://doi.org/10.1016/j.asr.2022.08.051.
13. Google Earth Engine (2023), MCD19A2 Level 2 data product 2000-2023, https://earthengine.google.com/, (visited on 12/20/2023).
14. Gvishiani, A. D., A. A. Soloviev, and B. A. Dzeboev (2020), Problem of Recognition of Strong-Earthquake-Prone Areas: a State-of-the-Art Review, Izvestiya, Physics of the Solid Earth, 56(1), 1–23, https://doi.org/10.1134/s1069351320010048.
15. Hearty, T., A. Savtchenko, M. Theobald, et al. (2013), Readme document for AIRS version 006 products, NASA, GES DISC.
16. Jiao, Z., J. Zhao, and X. Shan (2018), Pre-seismic anomalies from optical satellite observations: a review, Natural Hazards and Earth System Sciences, 18(4), 1013–1036, https://doi.org/10.5194/nhess-18-1013-2018.
17. Keilis-Borok, V., A. Gabrielov, and A. Soloviev (2009), Geo-complexity and Earthquake Prediction, in Encyclopedia of Complexity and Systems Science, pp. 4178–4194, Springer New York, https://doi.org/10.1007/978-0-387-30440-3_246.
18. Lyapustin, A., and Y. Wang (2018), MCD19A2 MODIS/Terra+Aqua Land Aerosol Optical Depth Daily L2G Global 1km SIN Grid V006, https://doi.org/10.5067/MODIS/MCD19A2.006.
19. Mikhailov, V. O., I. P. Babayants, M. S. Volkova, et al. (2023a), Reconstruction of Co-Seismic and Post-Seismic Processes for the February 6, 2023 Earthquake in Turkey from Data of Satellite SAR Interferometry, Izvestiya, Physics of the Solid Earth, 59(6), 888–898, https://doi.org/10.1134/S1069351323060113.
20. Mikhailov, V. O., I. P. Babayantz, M. S. Volkova, et al. (2023b), The February 6, 2023, Earthquakes in Turkey: A Model of the Rupture Surface Based on Satellite Radar Interferometry, Doklady Earth Sciences, 511(1), 571–577, https://doi.org/10.1134/S1028334X23600627.
21. Mogi, K. (1985), Earthquake Prediction, Academic Press, Tokyo.
22. Molchan, G., and V. Keilis-Borok (2008), Earthquake prediction: probabilistic aspect, Geophysical Journal International, 173(3), 1012–1017, https://doi.org/10.1111/j.1365-246X.2008.03785.x.
23. Noll, C. E. (2010), The crustal dynamics data information system: A resource to support scientific analysis using space geodesy, Advances in Space Research, 45(12), 1421–1440, https://doi.org/10.1016/j.asr.2010.01.018.
24. Okada, Y., S. Mukai, and R. P. Singh (2004), Changes in atmospheric aerosol parameters after Gujarat earthquake of January 26, 2001, Advances in Space Research, 33(3), 254–258, https://doi.org/10.1016/S0273-1177(03)00474-5.
25. Pulinets, S., and D. Ouzounov (2011), Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model - An unified concept for earthquake precursors validation, Journal of Asian Earth Sciences, 41(4–5), 371–382, https://doi.org/10.1016/j.jseaes.2010.03.005.
26. Pulinets, S. A., D. Ouzounov, A. V. Karelin, K. A. Boyarchuk, and L. A. Pokhmelnykh (2006), The physical nature of thermal anomalies observed before strong earthquakes, Physics and Chemistry of the Earth, Parts A/B/C, 31(4–9), 143–153, https://doi.org/10.1016/j.pce.2006.02.042.
27. Ruzhich, V. V., L. P. Berzhinskaya, E. A. Levina, and E. I. Ponomareva (2023), On the causes and consequences of two devastating earthquakes in the Türkiye on February 6, 2023, Geology and Environment, 3, 22–34, https://doi.org/10.26516/2541-9641.2023.1.22.
28. Saha, S., S. Moorthi, H.-L. Pan, et al. (2010), The NCEP Climate Forecast System Reanalysis, Bulletin of the American Meteorological Society, 91(8), 1015–1058, https://doi.org/10.1175/2010bams3001.1.
29. Smirnov, V. M., and E. V. Smirnova (2008), Investigation of the Possibility of Satellite Navigation System Application for Seismic Event Monitoring, Electromechanics problems, 105, 94–104 (in Russian), EDN: KDSVGL.
30. Sobolev, G. A., and A. V. Ponomarev (2003), Earthquake physics and precursors, Nauka, Moscow (in Russian), EDN: RVEBFL.
31. Soloviev, A. A., and A. I. Gorshkov (2017), Modeling the dynamics of the block structure and seismicity of the Caucasus, Izvestiya, Physics of the Solid Earth, 53(3), 321–331, https://doi.org/10.1134/S1069351317030120.
32. Trifonov, V. G. (2017), Neotectonics of Mobile Belts, in Transactions of the Geological Institute, 614, p. 180, GEOS, Moscow (in Russian), EDN: RTGVPV.
33. Tronin, A. A. (2000), Thermal IR satellite sensor data application for earthquake research in China, International Journal of Remote Sensing, 21(16), 3169–3177, https://doi.org/10.1080/01431160050145054.
34. United States Geological Survey (2023), Catalog of the last earthquakes from 2000 to 2023, https://earthquake.usgs.gov, (visited on 12/08/2023).
35. World Data System (2023), World Data Center for Geomagnetism, Kyoto, http://wdc.kugi.kyoto-u.ac.jp/index.html, (visited on 11/20/2023).
36. Xiong, P., X. H. Shen, Y. X. Bi, et al. (2010), Study of outgoing longwave radiation anomalies associated with Haiti earthquake, Natural Hazards and Earth System Sciences, 10(10), 2169–2178, https://doi.org/10.5194/nhess-10-2169-2010.
37. Xu, Y., T. Li, X. Tang, X. Zhang, H. Fan, and Y. Wang (2022), Research on the Applicability of DInSAR, Stacking-InSAR and SBAS-InSAR for Mining Region Subsidence Detection in the Datong Coalfield, Remote Sensing, 14(14), 3314, https://doi.org/10.3390/rs14143314.
38. Zhang, L., K. Dai, J. Deng, et al. (2021), Identifying potential landslides by stacking-insar in southwestern china and its performance comparison with sbas-insar, Remote Sensing, 13(18), 3662, https://doi.org/10.3390/rs13183662.
