Skip to main content
SpringerLink
Log in

Satellite Registration of Anomalies of Various Geophysical Fields during the Preparation of Destructive Earthquakes in Turkey in February 2023

  • USE OF SPACE INFORMATION ABOUT THE EARTH STUDYING CATASTROPHIC NATURAL PROCESSES FROM SPACE
  • Published:
Izvestiya, Atmospheric and Oceanic Physics Aims and scope Submit manuscript

Abstract

Studies of variations in the parameters of various geophysical fields during the preparation of destructive earthquakes that occurred in Turkey in February 2023 with magnitudes of 6 ≤ M ≤ 7.8 are carried out using satellite data. It has been found that anomalies of these parameters manifested themselves from 34 to 25 days before the earthquakes as a sharp decrease in the values of relative humidity (RHS) and outgoing longwave radiation (OLR), as well as in an increase in the density of local lineaments. An increase in the surface skin temperature (SST), surface air temperature (SAT), RHS, and OLR, as well as in the values of the aerosol optical depth (AOD) and ionospheric total electron content (TEC), was revealed 19–9 days before the analyzed seismic events. In the period from 5 to 2 days before these earthquakes, a decrease in the SST, SAT, the flux of OLR, and the ionospheric TEC, as well as an increase in RHS and in the length of the secants of the rose diagrams of regional lineaments, were recorded. Quantitative characteristics of these anomalies are determined.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

REFERENCES

  1. Akhoondzadeh, M., Ant colony optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010, Adv. Space Res., 2015, vol. 55, pp. 1754–1763.

    Article  Google Scholar 

  2. Akhoondzadeh, M. and Marchetti, D., Study of the preparation phase of Turkey’s powerful earthquake (6 February 2023) by a geophysical multiparametric fuzzy inference system, Remote Sens., 2023, vol. 15, p. 2224. https://doi.org/10.3390/rs15092224

    Article  Google Scholar 

  3. Akopian, S.Ts., Bondur, V.G., and Rogozhin, E.A., Technology for monitoring and forecasting strong earthquakes in Russia with the use of the seismic entropy method, Izv., Phys. Solid Earth, 2017, vol. 53, no. 1, pp. 32–51. https://doi.org/10.1134/S1069351317010025

    Article  Google Scholar 

  4. Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E., A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geosci. Remote Sens., 2002, vol. 40, no. 11, pp. 2375–2383. https://doi.org/10.1109/TGRS.2002.803792

    Article  Google Scholar 

  5. Bondur, V.G. and Gaponova, E.V., Remotely registering anomalous variations in lineament systems for the Baikal Rift zone during the M = 5.6 earthquake of September 21, 2020, Izv., Atmos. Ocean. Phys., 2021, vol. 57, no. 9, pp. 1012–1020. https://doi.org/10.1134/S0001433821090437

    Article  Google Scholar 

  6. Bondur, V.G. and Smirnov, V.M., Method for monitoring seismically hazardous territories by ionospheric variations recorded by satellite navigation systems, Dokl. Earth Sci., 2005, vol. 403, no. 5, pp. 736–740.

    Google Scholar 

  7. Bondur, V.G. and Voronova, O.S., Study of thermal fields before strong earthquakes in Turkey on March 8, 2010 (M = 6.1), and January 24, 2020 (M = 6.7), Izv., Atmos. Ocean. Phys., 2021, vol. 57, no. 9, pp. 991–10002. https://doi.org/10.1134/S0001433821090425

    Article  Google Scholar 

  8. Bondur, V.G. and Voronova, O.S., Detection from space of anomalous variations in thermal fields during seismic events in the Northern Caucasus in 2017–2022, Izv., Atmos. Ocean. Phys., 2022, vol. 58, no. 12, pp. 1546–1556. https://doi.org/10.1134/S0001433822120064

    Article  Google Scholar 

  9. Bondur, V.G. and Zverev, A.T., Satellite method of earthquake forecast based on the analysis of lineament system dynamics, Issled. Zemli Kosmosa, 2005, no. 3, pp. 37–52.

  10. Bondur, V.G. and Zverev, A.T., Mechanisms of Formation of Lineaments Recorded on Satellite Images during Monitoring of Seismic Areas, Issled. Zemli Kosmosa, 2007, no. 1, pp. 47–56.

  11. Bondur, V.G., Krapivin, V.F., and Savinykh, V.P., Monitoring i prognozirovanie prirodnykh katastrof (Monitoring and Forecast of Natural Catastrophes), Moscow: Nauchnyi mir, 2009.

  12. Bondur, V.G., Garagash, I.A., Gokhberg, M.B., Lapshin, V.M., and Nechaev, Yu.V., Connection between variations of the stress-strain state of the Earth’s crust and seismic activity: The example of Southern California, Dokl. Earth. Sci., 2010, vol. 430, no. 3, pp. 147–150. https://doi.org/10.1134/S1028334X10010320

    Article  Google Scholar 

  13. Bondur, V.G., Garagash, I.A., Gokhberg, M.B., and Rodkin, M.V., The evolution of the stress state in Southern California based on the geomechanical model and current seismicity, Izv., Phys. Solid Earth, 2016a, vol. 52, no. 1, pp. 117–128. https://doi.org/10.1134/S1069351316010043

    Article  Google Scholar 

  14. Bondur, V.G., Garagash, I.A., and Gokhberg, M.B., Large-scale interaction of seismically active tectonic provinces: The example of Southern California, Dokl. Earth Sci., 2016b, vol. 466, no. 2, pp. 183–186. https://doi.org/10.1134/S1028334X16020100

    Article  Google Scholar 

  15. Bondur, V.G., Zverev, A.T., and Gaponova, E., Precursor variability of lineament systems detected using satellite images during strong earthquakes, Izv., Atmos. Ocean. Phys., 2019, vol. 55, no. 9, pp. 1283–1291. https://doi.org/10.1134/S0001433819090123

    Article  Google Scholar 

  16. Bondur, V.G., Tsidilina, M.N., Gaponova, E.V., and Voronova, O.S., Joint analysis of anomalies of different geophysical fields, recorded from space before strong earthquakes in California, Izv., Atmos. Ocean. Phys., 2020a, vol. 56, no. 9, pp. 1502–1519. https://doi.org/10.1134/S000143382012035X

    Article  Google Scholar 

  17. Bondur, V.G., Gokhberg, M.B., Garagash, I.A., and Alekseev, D.A., Revealing short-term precursors of the strong M > 7 earthquakes in Southern California from the simulated stress-strain state patterns exploiting geomechanical model and seismic catalog data, Front. Earth Sci., 2020b, vol. 8, p. 571700. https://doi.org/10.3389/feart.2020.571700

    Article  Google Scholar 

  18. Bondur, V.G., Chimitdorzhiev, T.N., Tubanov, Ts.A., Dmitriev, A.V., and Dagurov, P.N., Analysis of the block-fault structure dynamics in the area of earthquakes in 2008 and 2020 near southern Lake Baikal by the methods of satellite radiointerferometry, Dokl. Earth Sci., 2021a, vol. 499, no. 2, pp. 648–653. https://doi.org/10.1134/S1028334X21080031

    Article  Google Scholar 

  19. Bondur, V.G., Tsidilina, M.N., Voronova, O.S., and Feoktistova, N.V., A study from space of anomalous variations of various geophysical fields during the preparation of a series of strong earthquakes in Italy in 2016–2017, Izv., Atmos. Ocean. Phys., 2021b, vol. 57, no. 12, pp. 1604–1620. https://doi.org/10.1134/S0001433821120057

    Article  Google Scholar 

  20. Bondur, V.G., Tsidilina, M.N., Gaponova, E.V., and Voronova, O.S., 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, Izv., Atmos. Ocean. Phys., 2022, vol. 58, no. 12, pp. 1532–1545. https://doi.org/10.1134/S0001433822120052

    Article  Google Scholar 

  21. Bondur, V.G., Chimitdorzhiev, T.N., and Dmitriev, A.V., Anomalous geodynamics before the 2023 earthquake in Turkey according to radar interferometry 2018–2023, Izv., Atmos. Ocean. Phys., 2023, vol. 59, no. 9.

  22. Dal Zilio, L. and Ampuero, J.P., Earthquake doublet in Turkey and Syria, Commun. Earth Environ., 2023, vol. 4, p. 71. https://doi.org/10.1038/s43247-023-00747-z

    Article  Google Scholar 

  23. Earthquake Early Warning Service. http://www.ceme.gsras. ru/new/ssd_news.htm. Accessed March 28, 2023.

  24. Ferretti, A., Prati, C., and Rocca, F., Permanent scatterers in SAR interferometry, IEEE Trans. Geosci. Remote Sens., 2001, vol. 39, pp. 8–20. https://doi.org/10.1109/36.898661

    Article  Google Scholar 

  25. Ganguly, N.D., Atmospheric changes observed during April 2015 Nepal earthquake, J. Atmos. Sol. Terr. Phys., 2016, vol. 140, pp. 16–22. https://doi.org/10.1016/j.jastp.2016.01.017

    Article  Google Scholar 

  26. Ghosh, S., Sasmal, S., Naja, M., Potirakis, S., and Hayakawa, M., Study of aerosol anomaly associated with large earthquakes (M>6), Adv. Space Res., 2023, vol. 71, no. 1, pp. 129–143. https://doi.org/10.1016/j.asr.2022.08.051

    Article  Google Scholar 

  27. Hearty, T., Savtchenko, A., Theobald, M., Ding, F., Esfandiari, E., and Vollmer, B., Readme document for AIRS version 006 products, NASA GES DISC Goddard Earth Sci. Data and Inf. Serv. Cent., Greenbelt, Md., 2013.

    Google Scholar 

  28. Keilis-Borok,V., Gabrielov, A., and Soloviev, A., Geo-complexity and earthquake prediction, in Encyclopedia of Complexity and Systems Science, Meyers, R. Ed., New York: Springer, 2009, pp. 4178–4194.

    Google Scholar 

  29. Kissin, I.G., On the system approach in the problem of forecasting the earthquakes, Izv., Phys. Solid Earth, 2013, vol. 49, no. 4, pp. 587–600. https://doi.org/10.1134/S1069351313040058

    Article  Google Scholar 

  30. Koronovskii, N.V., Zlatopol’skii, A.A., and Ivanchenko, G.N., Automated decoding of space imagery for structural analysis, Issled. Zemli Kosmosa, 1986, no. 1, pp. 111–118.

  31. Kronberg, P., Fernerkundung der Erde: Grundlagen und Methoden des Remote Sensing in der Geologie, Stuttgart: Enke, 1985; Moscow: Mir, 1988.

  32. Lyapustin, A. and Wang, Y., MCD19A2 MODIS/Terra + Aqua land aerosol optical depth daily L2G global 1km SIN grid v006 [data set], NASA EOSDIS Land Processes DAAC, 2018. https://doi.org/10.5067/MODIS/MCD19A2.006

  33. Ministry of the Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters. https://mchs.gov.ru/. Accessed March 28, 2023.

  34. Mehta, A., & Susskind, J. Outgoing longwave radiation from the TOVS Pathfinder Path A data set, J. Geophys. Res.: Atmos., 1999, vol. 104, no. D10, pp. 12193–12212. https://doi.org/10.1029/1999jd900059

    Article  Google Scholar 

  35. Mikhailov, V.O., Nazaryan, A.N., Smirnov, V.B., Kiseleva, E.A., Tikhotskii, S.A., Smol’yaninova, E.I., Timoshkina, E.P., Polyakov, S.A., Diament, M., and Shapiro, N., Joint inversion of the differential satellite interferometry and GPS data: A case study of Altai (Chuia) earthquake of September 27, 2003, Izv., Phys. Solid Earth, 2010, vol. 46, no. 2, pp. 91–103.

    Article  Google Scholar 

  36. Mogi, K., Earthquake Prediction, Tokyo: Academic Press, 1985.

    Google Scholar 

  37. Molchan, G. and Keilis-Borok, V., Earthquake prediction: Probabilistic aspect, Geophys. J. Int., 2008, vol. 173, no. 3, pp. 1012–1017.

    Article  Google Scholar 

  38. Noll, C., The crustal dynamics data information system: A resource to support scientific analysis using space geodesy, Adv. Space Res., 2010, vol. 45, no. 12, pp. 1421–1440. https://doi.org/10.1016/j.asr.2010.01.018

    Article  Google Scholar 

  39. Okada, Y., Mukai, S., and Singh, R.P., Changes in atmospheric aerosol parameters after Gujarat earthquake of January 26, 2001, Adv. Space Res., 2004, no. 3, pp. 254–258. https://doi.org/10.1016/S0273-1177(03)00474-5

  40. Pulinets, S. and Ouzounov, D., Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model: An unified concept for earthquake precursors validation, J. Asian Earth Sci., 2011, nos. 4–5, pp. 371–382.

  41. Pulinets, S.A., Ouzounov, D., Karelin, A.V., Boyarchuk, K.A., and Pokhmelnykh, L.A., The physical nature of thermal anomalies observed before strong earthquakes, Phys. Chem. Earth, Parts A/B/C, 2006, vol. 31, nos. 4–9, pp. 143–153. https://doi.org/10.1016/j.pce.2006.02.042

    Article  Google Scholar 

  42. Pulinets, S.A., Bondur, V.G., Tsidilina, M.N., and Gaponova, M.V., Verification of the concept of seismoionospheric coupling under quiet heliogeomagnetic conditions, using the Wenchuan (China) earthquake of May 12, 2008, as an example, Geomagn. Aeron. (Engl. Transl.), 2010, vol. 50, no. 2, pp. 231–242.

  43. Pulinets, S., Tsidilina, M., Ouzounov, D., and Davidenko, D., From Hector Mine M7.1 to Ridgecrest M7.1 earthquake: A look from a 20-year perspective, Atmosphere, 2021, vol. 12, p. 262. https://doi.org/10.3390/atmos12020262

    Article  Google Scholar 

  44. Ruzmaikin, A., Aumann, H.H., and Manning, E.M., Relative humidity in the troposphere with AIRS, J. Atmos. Sci., 2014, vol. 71, no. 7, pp. 2516–2533. https://doi.org/10.1175/jas-d-13-0363.1

    Article  Google Scholar 

  45. Sobolev, G.A. and Ponomarev, A.V., Fizika zemletryasenii i predvestniki (Earthquake Physics and Precursors), Moscow: Nauka, 2003.

  46. Trifonov, V.G., Neotektonika podvizhnykh poyasov (Neotectonics of Mobile Belts), Degtyarev, K.E., Ed., Moscow: GEOS, 2017.

    Google Scholar 

  47. Tronin, A.A., Satellite remote sensing in seismology: A review, Remote Sens., 2010, vol. 2, no. 1, pp. 124–150.

    Article  Google Scholar 

  48. Xu, Y., Li, T., Tang, X., Zhang, X., Fan, H., and Wang, Y., Research on the applicability of DInSAR, Stacking-InSAR and SBAS-InSAR for mining region subsidence detection in the Datong coalfield, Remote Sens., 2022, vol. 14, p. 3314. https://doi.org/10.3390/rs14143314

    Article  Google Scholar 

  49. Zhang, L., Dai, K., Deng, J., Ge, D., Liang, R., Li, W., and Xu, Q., Identifying potential landslides by Stacking-InSAR in Southwestern China and its performance comparison with SBAS-InSAR, Remote Sens., 2021, vol. 13, p. 3662. https://doi.org/10.3390/rs13183662

    Article  Google Scholar 

  50. Zhu, F. and Jiang, Y., Investigation of GIM-TEC disturbances before M ≥ 6.0 inland earthquakes during 2003–2017, Sci. Rep., 2020, vol. 10, p. 18038. https://doi.org/10.1038/s41598-020-74995-w

    Article  Google Scholar 

  51. Zlatopolskii, A.A., Technique for measuring the orientation characteristics of remote sensing data (LESSA technology, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2008, vol. 1, no. 5, pp. 102–112.

    Google Scholar 

Download references

Funding

This study was carried out in the AEROCOSMOS Research Institute as part of project no. 122011800095-3.

Author information

Authors and Affiliations

  1. AEROCOSMOS Institute for Scientific Research of Aerospace Monitoring, 105064, Moscow, Russia

    V. G. Bondur, M. N. Tsidilina, E. V. Gaponova, O. S. Voronova, M. V. Gaponova, N. V. Feoktistova & A. L. Zima

Authors
  1. V. G. Bondur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. N. Tsidilina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. V. Gaponova
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. O. S. Voronova
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. V. Gaponova
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. N. V. Feoktistova
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A. L. Zima
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. G. Bondur.

Ethics declarations

The authors of this work declare that they have no conflicts of interest.

Additional information

Translated by A. Nikol’skii

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bondur, V., Tsidilina, M., Gaponova, E. et al. Satellite Registration of Anomalies of Various Geophysical Fields during the Preparation of Destructive Earthquakes in Turkey in February 2023. Izv. Atmos. Ocean. Phys. 59, 1009–1027 (2023). https://doi.org/10.1134/S0001433823090049

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0001433823090049

Keywords:

Search

Navigation