Skip to main content

Advertisement

Log in

Lithosphere atmosphere ionosphere coupling associated with the 2019 Mw 7.1 California earthquake using GNSS and multiple satellites

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Global Navigation Satellite System (GNSS)–based Earthquake (EQ) anomalies in the ionosphere and troposphere provide explicit evidences to study the coupling between seismic events, atmosphere, and ionosphere in epicentral breeding regions consequent to the EQ day in the preparation period. EQs are still not predicted, but the space-based EQ anomalies aid in the development of monitoring pre- and post-seismic precursors around the seismogenic zone and associated fault lineament regions. In this paper, tropospheric and ionospheric anomalies are investigated for the July 06, 2019, Mw 7.1 California EQ from GNSS tropospheric delays and Total Electron Content (TEC), respectively. We noticed that atmospheric and ionospheric anomalies from GNSS stations within 5–10 days before the main shock and storm-induced ionospheric variations occur beyond the 5th day after the EQ. Similarly, synchronized and collocated lower atmospheric anomalies are also recorded in the long-term temporal values of SO2 and SO4 within 1-month before and after July 2019, which validates the existence of Lithosphere-Atmosphere–Ionosphere Coupling (LAIC) over the EQ epicenter. On the other hand, EQ anomalies occur during quiet geomagnetic storm activity (Kp < 3; Dst < − 20 nT) and geomagnetic storm triggered high-intensity ionospheric variations during Kp > 3. All these atmospheric and ionospheric perturbations support the development in EQ precursors with satellite measurements, which are indispensable towards the forecasting of future EQ.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

The GNSS data is freely available on the UNAVCO webpage (https://www.unavco.org/data/gps-gnss/gps-gnss.html). The atmospheric data (OLR, etc.) is obtained from NASA NOAA (https://psl.noaa.gov/data/composites/day/).

References

  • Afraimovich, E. L., Ding, F., Kiryushkin, V. V., Astafyeva, E. I., Jin, S., & Sankov, V. A. (2010). TEC response to the 2008 Wenchuan earthquake in comparison with other strong earthquakes. International Journal of Remote Sensing, 31, 3601–3613.

    Article  Google Scholar 

  • Arikan, F., Erol, C. B., & Arikan, O. (2003). Regularized estimation of vertical total electron content from Global Positioning System data. Journal of Geophysical Research: Space Physics108.

  • Bartels, J., Heck, N. H., & Johnston, H. F. (1939). The three-hour-range index measuring geomagnetic activity. Terrestrial Magnetism and Atmospheric Electricity, 44, 411–454.

    Article  Google Scholar 

  • Conklin, A. R. (2013). Introduction to soil chemistry: Analysis and instrumentation. John Wiley & Sons.

  • Daneshvar, M. R. M., & Freund, F. T. (2017). Remote sensing of atmospheric and ionospheric signals prior to the Mw 8.3 Illapel earthquake, Chile 2015, in: The Chile-2015 (Illapel) Earthquake and Tsunami. Springer, pp. 157–191.

  • Davidenko, D. V., & Pulinets, S. A. (2019). Deterministic variability of the ionosphere on the eve of strong (M≥ 6) earthquakes in the regions of Greece and Italy according to long-term measurements data. Geomagnetizm i Aeronomiya, 59, 493–508.

    Article  Google Scholar 

  • De Santis, A., Marchetti, D., Spogli, L., Cianchini, G., Pavón-Carrasco, F. J., Franceschi, G. D., et al. (2019). Magnetic field and electron density data analysis from swarm satellites searching for ionospheric effects by great earthquakes: 12 Case studies from 2014 to 2016. Atmosphere (basel), 10, 371.

    Article  Google Scholar 

  • Dey, S., Sarkar, S., & Singh, R. P. (2004). Anomalous changes in column water vapor after Gujarat earthquake. Advances in Space Research, 33, 274–278.

    Article  CAS  Google Scholar 

  • Dobrovolsky, I. P., Zubkov, S. I., & Miachkin, V. I. (1979). Estimation of the size of earthquake preparation zones. Pure and Applied Geophysics, 117, 1025–1044.

    Article  Google Scholar 

  • Freund, F. (2010). Toward a unified solid state theory for pre-earthquake signals. Acta Geophysica, 58, 719–766.

    Article  Google Scholar 

  • Freund, F. T., Kulahci, I. G., Cyr, G., Ling, J., Winnick, M., Tregloan-Reed, J., & Freund, M. M. (2009). Air ionization at rock surfaces and pre-earthquake signals. Journal of Atmospheric and Solar-Terrestrial Physics, 71, 1824–1834.

    Article  CAS  Google Scholar 

  • Ganguly, N. D. (2016). Atmospheric changes observed during April 2015 Nepal earthquake. Journal of Atmospheric and Solar-Terrestrial Physics, 140, 16–22.

    Article  CAS  Google Scholar 

  • Geller, R. J., Jackson, D. D., Kagan, Y. Y., & Mulargia, F. (1997). Earthquakes cannot be predicted. Science (80-.)275, 1616.

  • Gorny, V. I., Salman, A. G., Tronin, A. A., & Shilin, B. V. (2020). Terrestrial outgoing infrared radiation as an indicator of seismic activity. arXiv Prepr. arXiv2001.11762.

  • Hayakawa, M., & Molchanov, O. A. (2002). Seismo Electromagnetics: Lithosphere-Atmosphere-Ionosphere Coupling.

  • Jiao, Z.-H., Zhao, J., & Shan, X. (2018). Pre-seismic anomalies from optical satellite observations: A review. Natural Hazards and Earth Systems Sciences, 18, 1013–1036.

    Article  Google Scholar 

  • Jin, S., Han, L., & Cho, J. (2011). Lower atmospheric anomalies following the 2008 Wenchuan Earthquake observed by GPS measurements. Journal of Atmospheric and Solar-Terrestrial Physics, 73, 810–814.

    Article  Google Scholar 

  • Kiyani, A., Shah, M., Ahmed, A., Shah, H. H., Hameed, S., Adil, M. A., & Naqvi, N. A. (2020). Seismo ionospheric anomalies possibly associated with the 2018 Mw 8.2 Fiji earthquake detected with GNSS TEC. Journal of Geodynamics, 140, 101782.

  • Klobuchar, J. A. (1987). Ionospheric time-delay algorithm for single-frequency GPS users. IEEE Transactions on aerospace and electronic systems, AES-23, 325–331. https://doi.org/10.1109/TAES.1987.310829

  • Kuo, C. L., Huba, J. D., Joyce, G., & Lee, L. C. (2011). Ionosphere plasma bubbles and density variations induced by pre‐earthquake rock currents and associated surface charges. Journal of Geophysical Research: Space Physics, 116.

  • Kuo, C. L., Lee, L. C., & Huba, J. D. (2014). An improved coupling model for the lithosphere-atmosphere-ionosphere system. Journal of Geophysical Research: Space Physics, 119, 3189–3205.

    Google Scholar 

  • Liu, X., Zhang, Q., Shah, M., & Hong, Z. (2017). Atmospheric-ionospheric disturbances following the April 2015 Calbuco volcano from GPS and OMI observations. Advances in Space Research, 60, 2836–2846.

    Article  CAS  Google Scholar 

  • Loewe, C. A., & Prölss, G. W. (1997). Classification and mean behavior of magnetic storms. Journal of Geophysical Research: Space Physics, 102, 14209–14213.

    Article  Google Scholar 

  • Marchetti, D., De Santis, A., Shen, X., Campuzano, S. A., Perrone, L., Piscini, A., Di Giovambattista, R., Jin, S., Ippolito, A., & Cianchini, G. (2020). Possible lithosphere-atmosphere-ionosphere coupling effects prior to the 2018 Mw= 7.5 Indonesia earthquake from seismic, atmospheric and ionospheric data. Journal of Asian Earth Sciences188, 104097.

  • Mehdi, S., Sultana, D., & Shah, M. (2019). Atmospheric anomalies associated with 2011 M w 9.1 Japan earthquake using remote sensing, in: 2019 Sixth International Conference on Aerospace Science and Engineering (ICASE). IEEE, pp. 1–4.

  • Niell, A. E. (1996). Global mapping functions for the atmosphere delay at radio wavelengths. Journal of Geophysical Research: Solid Earth, 101, 3227–3246.

    Article  Google Scholar 

  • Ouzounov, D., Liu, D., Chunli, K., Cervone, G., Kafatos, M., & Taylor, P. (2007). Outgoing long wave radiation variability from IR satellite data prior to major earthquakes. Tectonophysics, 431, 211–220.

    Article  Google Scholar 

  • Ouzounov, D., Pulinets, S., Guiliani, G., Velichkova-Iotsova, S., Kafatos, M., Taylor, P. (2020). Pre-earthquake processes associated with the M6. 4 of Nov 26, 2017 In Albania. A multi parameters analysis., in: EGU General Assembly Conference Abstracts. p. 6251.

  • Pulinets, S. & Boyarchuk, K. (2004). Ionospheric precursors of earthquakes. Springer Science & Business Media.

  • Pulinets, S., & Ouzounov, D. (2011). Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model–An unified concept for earthquake precursors validation. Journal of Asian Earth Sciences, 41, 371–382.

    Article  Google Scholar 

  • Qi, Y., Wu, L., He, M., & Mao, W. (2020). Spatio-temporally weighted two-step method for retrieving seismic MBT anomaly: May 2008 Wenchuan earthquake sequence being a case. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 382–391.

    Article  Google Scholar 

  • Rikitake, T. (1987). Earthquake precursors in Japan: Precursor time and detectability. Tectonophysics, 136, 265–282.

    Article  Google Scholar 

  • Rishbeth, H. (2007). Do earthquake precursors really exist? Eos. Transactions. American Geophysical Union, 88, 296.

    Article  Google Scholar 

  • Roma-Dollase, D., Hernández-Pajares, M., Krankowski, A., Kotulak, K., Ghoddousi-Fard, R., Yuan, Y., Li, Z., Zhang, H., Shi, C., & Wang, C. (2018). Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle. Journal of Geodesy, 92, 691–706.

    Article  Google Scholar 

  • Sezen, U., Arikan, F., Arikan, O., Ugurlu, O., & Sadeghimorad, A. (2013). Online, automatic, near-real time estimation of GPS-TEC: IONOLAB-TEC. Space Weather, 11, 297–305.

    Article  Google Scholar 

  • Shah, M., & Jin, S. (2015). Statistical characteristics of seismo-ionospheric GPS TEC disturbances prior to global Mw≥ 5.0 earthquakes (1998–2014). Journal of Geodynamics, 92, 42–49.

    Article  Google Scholar 

  • Shah, M., Khan, M., Ullah, H., & Ali, S. (2018). Thermal anomalies prior to the 2015 Gorkha (Nepal) earthquake from MODIS land surface temperature and outgoing longwave radiators. Geodynamics & Tectonophysics, 9(1), 123–138.

    Article  Google Scholar 

  • Shah, M., Tariq, M. A., Ahmad, J., Naqvi, N. A., & Jin, S. (2019a). Seismo ionospheric anomalies before the 2007 M7. 7 Chile earthquake from GPS TEC and DEMETER. Journal of Geodynamics, 127, 42–51.

    Article  Google Scholar 

  • Shah, M., Tariq, M. A., & Naqvi, N. A. (2019b). Atmospheric anomalies associated with Mw>6.0 earthquakes in Pakistan and Iran during 2010‒2017. Journal of Atmospheric and Solar-Terrestrial Physics, 191, 105056. https://doi.org/10.1016/j.jastp.2019.06.003

  • Shah, M., Ahmed, A., Ehsan, M., Khan, M., Tariq, M. A., Calabia, A., & ur Rahman, Z. (2020a). Total electron content anomalies associated with earthquakes occurred during 1998–2019. Acta Astronaut.

  • Shah, M., Aibar, A. C., Tariq, M. A., Ahmed, J., & Ahmed, A. (2020b). Possible ionosphere and atmosphere precursory analysis related to Mw> 6.0 earthquakes in Japan. Remote Sensing of Environment, 239, 111620.

  • Shah, M., Inyurt, S., Ehsan, M., Ahmed, A., Shakir, M., Ullah, S., & Iqbal, M. S. (2020c). Seismo ionospheric anomalies in Turkey associated with Mw≥ 6.0 earthquakes detected by GPS stations and GIM TEC. Advances in Space Research.

  • Shah, M., Qureshi, R. U., Khan, N. G., Ehsan, M., & Yan, J. (2021a). Artificial neural network based thermal anomalies associated with earthquakes in Pakistan from MODIS LST. Journal of Atmospheric and Solar-Terrestrial Physics, 215, 105568.

  • Shah, M., Ehsan, M., Abbas, A., Ahmed, A., & Jamjareegulgarn, P. (2021b). Possible thermal anomalies associated with global terrestrial earthquakes during 2000–2019 based on MODIS-LST, in IEEE Geoscience and Remote Sensing Lettershttps://doi.org/10.1109/LGRS.2021.3084930

  • Tariq, M. A., Shah, M., Hernández-Pajares, M., & Iqbal, T. (2019). Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017. Advances in Space Research, 63, 2088–2099.

    Article  Google Scholar 

Download references

Acknowledgements

We wish to acknowledge the USGS, NASA, and NOAA online data centers for global transmission of reanalysis data. We are also thankful to UNAVCO for providing preprocessed tropospheric delay data and GPS RINEX files which were used for TEC calculation using software provided by IONOLAB. The authors are also thankful to IONOLAB for providing support and useful software. We are also thankful to NCGSA for providing support in conducting the research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Munawar Shah.

Additional information

Publisher's Note

Springer Nature 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

Mehdi, S., Shah, M. & Naqvi, N.A. Lithosphere atmosphere ionosphere coupling associated with the 2019 Mw 7.1 California earthquake using GNSS and multiple satellites. Environ Monit Assess 193, 501 (2021). https://doi.org/10.1007/s10661-021-09278-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-021-09278-6

Keywords

Navigation