An insight on Co-Seismic Ionospheric Disturbances: from first observations to new challenges
Creators: name: RAVANELLI, Michela
Publisher: name: Zenodo
Year: 2024

description:  

An insight on Co-Seismic Ionospheric Disturbances: from first observations to new challenges 

Michela Ravanelli

The idea that earthquakes can create disturbances in the upper atmosphere, specifically in the ionosphere, has been known since the 1960s. This was first observed using ionosondes and Doppler sounders after the great Alaska earthquake in 1964.

However, the widespread observation of the ionospheric response to earthquakes or co-seismic ionospheric disturbances (CSID) has only become possible with the advent of GPS and more generally GNSS satellites. GNSS technology, thus, enables the investigation of Total Electron Content (TEC), which corresponds to the number of electrons along the direct signal path in the ionosphere between the satellite and the receiver.

This field of study, known as GNSS Ionospheric Seismology, has seen significant advancements over the past decades, analyzing the ionospheric signatures of the most impacting earthquakes. Among those one, we report the 2004 Sumatra-Andaman earthquake, the 2011 Tohoku-Oki earthquake, the 2012 Haida-Gwaii earthquake and tsunami, the 2015 Illapel earthquake, the 2015 Gorkha earthquake, and the 2016 Kaikoura earthquake.

In detail, these studies highlighted several kinds of CSIDs according to their generation mechanism.



Near-Field CSIDs are triggered by the co-seismic vertical crustal displacements that are generated by shock acoustic waves, showing N waveform, velocities with a speed ranging between 600m/s and 100 m/s, observed in 10–15 min after the main shock and within 600–700 km from the epicenter.

Far-field CSIDs are generated by Raylegh waves that further induce acoustic-gravity waves, observed thousands of kilometers away from the epicenter since they travel at 3-4 km/s. Far-field CSIDs can be also generated by air surface waves.

Epicentral area CSIDs are due to atmospheric resonance of the acoustic-gravity waves emitted from the epicentral movement. The TEC oscillations associated with these disturbances have a common period of around 4 minutes and can persist for several hours after the earthquake.


 

Furthermore, it's crucial to emphasize the significant role played by both seismic and non-seismic factors in generating CSIDs.

In detail, near-field CSID amplitude increases roughly linearly with the magnitude of an earthquake. However, there is a lower threshold for earthquake magnitude (~6.5), below which TEC perturbations cannot be detected using GPS. Fault mechanism, including both dip-slip and strike-slip, also influences the CSID waveforms. CSIDs also allow to retrieve information on seismic source i.e., the magnitude of the co-seismic vertical crustal displacements and the fault dimensions.

Non-seismic factors are then represented by local atmospheric conditions (ionospheric background conditions), satellite-receiver geometry and the geomagnetic field.

Nowadays, to enhance the imaging of the ionosphere using GNSS, TEC observations from non-geodetic receivers like shipborne GNSS, low-cost receivers, and smartphones are being explored. Additionally, the use of TEC estimates from dual-frequency GNSS geostationary satellites for natural hazards monitoring is now well-established.

Finally, the large amount of TEC data leave room for the application of data-driven algorithms. Machine learning algorithms can facilitate the detection of CSIDs, a task that has traditionally relied on human experts. Several approaches, including classification algorithms and deep learning algorithms, are currently being tested.