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Pure and Applied Geophysics

, Volume 174, Issue 10, pp 3673–3688 | Cite as

A Multi-parametric Climatological Approach to Study the 2016 Amatrice–Norcia (Central Italy) Earthquake Preparatory Phase

  • Alessandro PisciniEmail author
  • Angelo De Santis
  • Dedalo Marchetti
  • Gianfranco Cianchini
Article
Part of the following topical collections:
  1. The Central Italy Earthquake Crisis with onset August 24, 2016

Abstract

Based on observations prior to earthquakes, recent theoretical considerations suggest that some geophysical quantities reveal abnormal changes that anticipate moderate and strong earthquakes, within a defined spatial area (the so-called Dobrovolsky area) according to a lithosphere–atmosphere–ionosphere coupling model. One of the possible pre-earthquake effects could be the appearance of some climatological anomalies in the epicentral region, weeks/months before the major earthquakes. In this paper, the period of 2 months preceding the Amatrice–Norcia (Central Italy) earthquake sequence, that started on 24 August 2016 with an M6 earthquake and a few months later produced other two major shocks (i.e. an M5.9 on 26 October and then an M6.5 on 30 October), was analyzed in terms of skin temperature, total column water vapour and total column of ozone, compared with the past 37-year trend. The novelty of the method stands in the way the complete time series is reduced, where also the possible effect of global warming is properly removed. The simultaneous analysis showed the presence of persistent contemporary anomalies in all of the analysed parameters. To validate the technique, a confutation/confirmation analysis was undertaken where these parameters were successfully analyzed in the same months but considering a seismically “calm” year, when significant seismicity was not present. We also extended the analysis to all available years to construct a confusion matrix comparing the occurrence of climatological data anomalies with real seismicity. This work confirms the potentiality of multi parameters in anticipating the occurrence of large earthquakes in Central Italy, thus reinforcing the idea of considering such behaviour an effective tool for an integrated system of future earthquake prediction.

Keywords

Seismic precursors LAIC strong and intermediate earthquakes thermal precursory anomaly 

Notes

Acknowledgements

This work was undertaken in the framework of the ESA-funded project SAFE (Swarm for Earthquake study). We also thank two anonymous referees that provided, together with the Editor, some useful comments that allowed us to improve the original version of the manuscript significantly.

References

  1. Akselevich, V. I., & Tertyshnikov, A. V. (1995). Methodology of ecological monitoring data application to seismic forecasting. Atmospheric and Oceanic Optics, 8(7), 567.Google Scholar
  2. Aliano, C., Corrado, R., Filizzola, C., Genzano, N., Pergola, N., & Tramutoli, V. (2008). Robust TIR satellite techniques for monitoring earthquake active regions: limits, main achievements and perspectives. Annals of Geophysics, 51(1), 303–318.Google Scholar
  3. Blackett, M., Wooster, M. J., & Malamud, B. D. (2011). Exploring land surface temperature earthquake precursors: a focus on the Gujarat (India) earthquake of 2001. Geophysical Research Letters, 38, L15303.Google Scholar
  4. Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B., & Jones, P. D. (2006). Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. Journal of Geophysical Research, 111, D12106. doi: 10.1029/2005JD006548.CrossRefGoogle Scholar
  5. Cervone, G., Singh, R. P., Kafatos, M., & Yu, C. (2005). Wavelet maxima curves of surface latent heat flux anomalies associated with Indian earthquakes. Natural Hazards and Earth System Sciences, 5, 87–99.CrossRefGoogle Scholar
  6. Chiarabba, C., Amato, A., Anselmi, M., Baccheschi, P., Bianchi, I., Cattaneo, M., et al. (2009). The 2009 L’Aquila (central Italy) MW 6.3 earthquake: main shock and aftershocks. Geophysical Research Letters, 36, L18308. doi: 10.1029/2009GL039627.CrossRefGoogle Scholar
  7. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37–46.CrossRefGoogle Scholar
  8. De Santis, A., De Franceschi, G., Spogli, L., Perrone, L., Alfonsi, L., Qamili, E., Cianchini. G., Di Giovambattista, R., Salvi, S., Filippi, E., Pavón-Carrasco, F.J., Monna, S., Piscini, A., Battiston, R., Vitale, V., Picozza, P.G., Conti, L., Parrot, M., Pinçon, J-L., Balasis, G., Tavani, M., Argan, A., Piano, G., Rainone, M.L., Liu, W., Tao, D. (2015). Geospace perturbations induced by the Earth: the state of the art and future trends. Physics and Chemistry of the Earth, 8586, 17–33. doi: 10.1016/j.pce.2015.05.00485-86.CrossRefGoogle Scholar
  9. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137, 553–597. doi: 10.1002/qj.828.CrossRefGoogle Scholar
  10. Dey, S., Sarkar, S., & Singh, R. P. (2004). Anomalous changes in column water vapour after Gujarat earthquake. Advances in Space Research, 33(3), 274–278.CrossRefGoogle Scholar
  11. Dey, S., & Singh, R. P. (2003). Surface latent heat flux as an earthquake precursor. Natural Hazards and Earth Systems Sciences, 3, 749–755.CrossRefGoogle Scholar
  12. Dobrovolsky, I. P., Zubkov, S. I., & Miachkin, V. I. (1979). Estimation of the size of earthquake preparation zones. PAGEOPH, 117, 1025. doi: 10.1007/BF00876083.CrossRefGoogle Scholar
  13. Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27, 861–874.CrossRefGoogle Scholar
  14. Freund, F. T., Takeuchi, A., Lau, B. W. S., Al-Manaseer, A., Fu, C. C., Bryant, N. A., et al. (2007). Stimulated infrared emission from rocks: assessing a stress indicator. eEarth, 2, 7–16.CrossRefGoogle Scholar
  15. Gorny, V. I., Sal’man, A. G., Tronin, A. A., & Shilin, B. V. (1988). Outgoing terrestrial infrared radiation as an indicator of seismic activity. Akademiia Nauk SSSR, Doklady, 301 (1), 67–69 (ISSN 0002-3264). (in Russian).Google Scholar
  16. Harrison, R. G., Aplin, K. L., & Rycroft, M. J. (2014). Earthquake-cloud coupling through the global atmospheric electric circuit. Natural Hazards and Earth Systems Sciences, 14, 773–777.CrossRefGoogle Scholar
  17. Holliday, J. R., Nanjo, K. Z., Tiampo, K. F., Rundle, J. B., & Turcotte, D. L. (2005). Earthquake forecasting and its verification. Nonlinear Processes in Geophysics, 12, 965–977.CrossRefGoogle Scholar
  18. Ma, Y., Zhao, Y., Liu, S., & Wu, L. (2010). Possible abnormal phenomenon of the atmospheric water vapor before Hengchun earthquake. PIERS Online, 6(1), 21–25. doi: 10.2529/PIERS090907094618.CrossRefGoogle Scholar
  19. Ouzounov, D., & Freund, F. T. (2004). Mid-infrared emission prior to strong earthquakes analyzed remote sensing data. Advances in Space Research, 33, 268–273.CrossRefGoogle Scholar
  20. Ouzounov, D., Liu, D. F., Kang, C. L., & Taylor, P. (2007). The outgoing long-wave radiation variability prior to the major earthquake by analyzing IR satellite data. Tectonophysics, 421, 211–220.CrossRefGoogle Scholar
  21. Piroddi, L., Ranieri, G., Freund, F., & Trogu, A. (2014). Geology, tectonics and topography underlined by L’Aquila earthquake TIR precursors. Geophysical Journal International, 197(3), 1532–1536. doi: 10.1093/gji/ggu123.CrossRefGoogle Scholar
  22. Pulinets, S., & Ouzounov, D. (2011). Lithosphere–atmosphere–ionosphere coupling (LAIC) model-an unified concept for earthquake precursors validation. Journal of Asian Earth Sciences, 41(4–5), 371–382.CrossRefGoogle Scholar
  23. Qiang, Z. J., Xu, X. D., & Dian, C. G. (1991). Thermal infrared anomaly precursor of impending earthquakes. Chinese Science Bulletin, 36, 319–323.Google Scholar
  24. Qin, K., Guo, G. M., & Wu, L. X. (2009). Surface latent heat flux anomalies preceding inland earthquakes in China. Earthquake Science, 22(5), 555–562.CrossRefGoogle Scholar
  25. Qin, K., Wu, L. X., De Santis, A., Meng, J., Ma, W. Y., & Cianchini, G. (2012). Quasi-synchronous multi-parameter anomalies associated with the 2010–2011 New Zealand earthquake sequence. Natural Hazards and Earth Systems Sciences, 12, 1059–1072.CrossRefGoogle Scholar
  26. Rikitake, T. (1987). Earthquake precursors in Japan: precursor time and detectability. Tectonophysics, 136, 265–282.CrossRefGoogle Scholar
  27. Rovida, A., Locati, M., Camassi, R., Lolli, B., & Gasperini, P. (2016). CPTI15, the 2015 version of the parametric catalogue of Italian earthquakes. Istituto Nazionale di Geofisica e Vulcanologia. doi: 10.6092/INGV.IT-CPTI15.Google Scholar
  28. Saraf, A. K., & Choudhury, S. (2005). Cover: satellite detects surface thermal anomalies associated with the Algerian earthquakes of May 2003. International Journal of Remote Sensing, 26(13), 2705–2713. doi: 10.1080/01431160310001642359.CrossRefGoogle Scholar
  29. Scholz, C. H. (2002). Mechanics of earthquakes and faulting (2nd ed.). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  30. Shearer, P. M. (2009). Introduction to seismology (2nd ed., p. 396). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  31. Takashi, M., & Tadashi, T. (2010). Detection algorithm of earthquake-related rock failures from satelliteborne microwave radiometer data. IEEE Transactions on Geoscience and Remote Sensing, 48, 1768–1776.CrossRefGoogle Scholar
  32. Tanimoto, T., Heki, K., & Artru-Lambin, J. (2015). Interaction of solid earth, atmosphere, and ionosphere. In G. Schubert (Ed.), Treatise on geophysics (2nd ed., Vol. 4, pp. 421–443). Oxford: Elsevier.CrossRefGoogle Scholar
  33. Tinti, E., Scognamiglio, L., Michelini, A., & Cocco, M. (2016). Slip heterogeneity and directivity of the ML 6.0, 2016, Amatrice earthquake estimated with rapid finite-fault inversion. Geophysical Research Letters. doi: 10.1002/2016GL071263.Google Scholar
  34. Tramutoli, V., Bello, G. D., Pergola, N., & Piscitelli, S. (2001). Robust satellite techniques for remote sensing of seismically active areas. Annali di Geofisica, 44(2), 295–312.Google Scholar
  35. Tronin, A. A. (1996). Satellite thermal survey-a new tool for the study of seismoactive regions. International Journal of Remote Sensing, 41, 1439–1455.CrossRefGoogle Scholar
  36. Tronin, A. A. (2002). Atmosphere–litosphere coupling. Thermal anomalies on the Earth surface in seismic processes. In M. Hayakawa & O. A. Molchanov (Eds.), Seismo electromagnetics: lithosphere–atmosphere–ionosphere coupling (pp. 173–176). TERRAPUB: Tokyo.Google Scholar
  37. Wu, L., Zheng, S., De Santis, A., Qin, K., Di Mauro, R., Liu, S., et al. (2016). Geosphere coupling and hydrothermal anomalies before the 2009 Mw 6.3 L’Aquila earthquake in Italy. Natural Hazards and Earth Systems Sciences, 16, 1859–1880. doi: 10.5194/nhess-16-1859-2016.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alessandro Piscini
    • 1
    Email author
  • Angelo De Santis
    • 1
  • Dedalo Marchetti
    • 1
  • Gianfranco Cianchini
    • 1
  1. 1.Istituto Nazionale di Geofisica e VulcanologiaRomeItaly

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