Upper Atmospheric Responses to Surface Disturbances: An Observational Perspective

Meng, Xing; Vergados, Panagiotis; Komjáthy, A.; Verkhoglyadova, Olga

doi:10.1029/2019rs006858

Cited by 65 publications

(61 citation statements)

References 191 publications

(265 reference statements)

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“…Impulsive forcing from the Earth's surface occurring due to earthquakes, explosions, volcanic eruptions, tsunamis, and so forth triggers atmospheric pressure waves. Depending on their frequencies, these atmospheric waves can be distinguished as acoustic and gravity waves (Figure ; Blanc, ; Huang et al, ; Meng et al, ). The acoustic waves are characterized by frequencies higher than the acoustic cutoff frequency (ω a ), that is, higher than ~3.3 mHz.…”

Section: Introductionmentioning

confidence: 99%

Ionospheric Detection of Natural Hazards

Astafyeva

2019

Reviews of Geophysics

218

167

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Natural hazards (NH), such as earthquakes, tsunamis, volcanic eruptions, and severe tropospheric weather events, generate acoustic and gravity waves that propagate upward and cause perturbations in the atmosphere and ionosphere. The first NH-related ionospheric disturbances were detected after the great 1964 Alaskan earthquake by ionosondes and Doppler sounders. Since then, many other observations confirmed the responsiveness of the ionosphere to NH. Within the last two decades, outstanding progress has been made in this area owing to the development of networks of ground-based dual-frequency Global Navigation Satellite Systems (GNSS) receivers. The use of GNSS-sounding has substantially enlarged our knowledge about the solid earth/ocean/atmosphere/ionosphere coupling and NH-related ionospheric disturbances and their main features. Moreover, recent results have demonstrated that it is possible to localize NH from their ionospheric signatures and also, if/when applicable, to obtain the information about the NH source (i.e., the source location and extension and the source onset time). Although all these results were obtained in retrospective studies, they have opened an exciting possibility for future ionosphere-based detection and monitoring of NH in near-real time. This article reviews the recent developments in the area of ionospheric detection of earthquakes, tsunamis, and volcanic eruptions, and it discusses the future perspectives for this novel discipline. Plain Language SummaryThe ionosphere is the ionized region of the Earth's atmosphere that is located between~60 and~800 km of altitude. The ionosphere is largely impacted by the solar and magnetic activities, as well as by the neutral atmosphere. Besides these large-scale and global processes influencing from above, the ionosphere can be more "locally" perturbed from below by geophysical phenomena (e.g., earthquakes, tsunamis, volcanic eruptions, and severe tropospheric weather events) and by man-made events (e.g., explosions, rocket and missile launches, and mine blasts). From below, the disturbances arrive in the ionosphere as acoustic and gravity waves. Upon their upward propagation, these waves grow in amplitude up to a million times owing to the exponential decrease of the atmospheric density with height. Consequently, the acoustic and gravity waves generated at the Earth's surface may provoke significant perturbations in the upper atmosphere and ionosphere. In the ionosphere, the perturbations can be detected by ionospheric sounding tools, such as GNSS receivers, ionosondes, and airglow cameras.

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Section: Introductionmentioning

confidence: 99%

Ionospheric Detection of Natural Hazards

Astafyeva

2019

Reviews of Geophysics

218

167

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“…These facts corroborate the larger ground deformation and energy propagation in the west and southwest of the epicenter. Due to the decreasing background air density, the amplitudes of CID grow exponentially with the altitude to conserve energy when the acoustic waves propagate upward into the atmosphere (Meng et al., 2019). Therefore, the CID with propagation along the southwest direction will have a more intense ionospheric response and larger amplitude after amplification.…”

Section: Resultsmentioning

confidence: 99%

Two‐Azimuth Co‐Seismic Ionospheric Disturbances Following the 2020 Jamaica Earthquake From GPS Observations

Chai

Jin

2021

JGR Space Physics

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Co‐seismic ionospheric disturbance (CID) may provide insights on understanding the coupled nature of earthquake–atmosphere geophysical processes. In this study, the CIDs following the Mw 7.7 Jamaica earthquake on January 28, 2020 are detected about 12 min after the main shock by the dual‐frequency Global Positioning System measurements. Significant CIDs at two azimuths are observed from satellite PRN03, 04 and 26 with spreading out at 3.54, 3.51 and 3.48 km/s respectively, which are close to the spreading speeds of Rayleigh waves recorded by the seismographs. The significant CID signals are found in south near‐field area and southwest far‐field area. Furthermore, CID characteristics are analyzed in terms of amplitude, elevation and azimuth angle, waveform, and frequency domain. Results show that CIDs are observed by PRN03, 04 and 26 at low elevation angles (<35°) in infrasonic wave frequency domain and the average negative amplitudes of CIDs observed by PRN26 are larger than −0.08 TECU, while the CID amplitudes observed by PRN03 and PRN04 are about −0.05 and −0.07 TECU, respectively. Moreover, the azimuthal asymmetry of CID amplitude in SW and SE azimuths and different initial polarities in disturbance signals are found and discussed from tectonic and nontectonic factors. The relations among CID, Rayleigh wave and focal mechanism are interpreted. The upward propagating secondary acoustic wave triggered by the seismic Rayleigh wave from earthquake is the main source of CIDs. These results confirm that strike‐slip earthquake can also generate pronounced co‐seismic ionospheric disturbances.

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“…The threshold for the correlated data series depends on the standard deviation of dTEC/dt series: (2) where -the standard deviation of dTEC/dt series at GNSS sites. The standard deviation is an indicator of data noisiness.…”

Section: Real-time Detection Of Co-seismic Travelling Ionospheric Disturbances From Tec Data Seriesmentioning

confidence: 99%

Determining spatio-temporal characteristics of Coseismic Travelling Ionospheric Disturbances (CTID) in near real-time

Maletckii¹,

Astafyeva²

2021

Preprint

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Earthquakes are known to generate ionospheric disturbances that are commonly referred to as co-seismic travelling ionospheric disturbances (CTID). In this work, for the first time, we present a novel method that enables to automatically detect CTID in ionospheric GNSS-data, and to determine their spatio-temporal characteristics (velocity and azimuth of propagation) in near-real time (NRT), i.e., less than 15 minutes after an earthquake. The obtained instantaneous velocities allow us to understand the evolution of CTID and to estimate the location of the CTID source in NRT. Furthermore, also for the first time, we developed a concept of real-time traveltime diagrams that aid to verify the correlation with the source and to estimate additionally the propagation speed of the observed CTID. We apply our methods to the Mw7.4 Sanriku earthquake of 09/03/2011 and the Mw9.0 Tohoku earthquake of 11/03/2011, and we make a NRT analysis of the dynamics of CTID driven by these seismic events. We show that the best results are achieved with high-rate 1Hz data. While the first tests are made on CTID, our method is also applicable for detection and determining of spatio-temporal characteristics of other travelling ionospheric disturbances that often occur in the ionosphere driven by many geophysical phenomena.

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Upper Atmospheric Responses to Surface Disturbances: An Observational Perspective

Cited by 65 publications

References 191 publications

Ionospheric Detection of Natural Hazards

Ionospheric Detection of Natural Hazards

Two‐Azimuth Co‐Seismic Ionospheric Disturbances Following the 2020 Jamaica Earthquake From GPS Observations

Determining spatio-temporal characteristics of Coseismic Travelling Ionospheric Disturbances (CTID) in near real-time

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