Two‐Mode Ionospheric Disturbances Following the 2005 Northern California Offshore Earthquake From GPS Measurements

Jin, Shuanggen

doi:10.1029/2017ja025001

Cited by 21 publications

(13 citation statements)

References 33 publications

(45 reference statements)

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“…The “splitting” of CSID into faster and slower modes was explained by the difference in their propagation speed. The occurrence of multiple modes was later confirmed for several other large earthquakes, including the great Tohoku‐oki earthquake of 11 March 2011 (e.g., Galvan et al, ; Jin et al, ; Kakinami et al, ; Liu et al, ; Rolland, Lognonné, Astafyeva, et al, ), the M7.8 April 2015 Nepal earthquake (Reddy & Seemala, ; Tulasi Ram et al, ), and the 2005 Northern California offshore earthquake (Jin, ). Figure b shows multiple‐mode CSID observed by Satellite G15 after the Tohoku‐oki earthquake observed by Galvan et al ().…”

Section: Ionospheric Response To Earthquakes and Tsunamismentioning

confidence: 89%

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Ionospheric Detection of Natural Hazards

Astafyeva

2019

Reviews of Geophysics

201

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: Ionospheric Response To Earthquakes and Tsunamismentioning

confidence: 89%

“…Both acoustic and gravity waves are amplified with the altitude because of the exponential decrease of the atmospheric density with height. (Jin, 2018). Figure 6b shows multiple-mode CSID observed by Satellite G15 after the Tohoku-oki earthquake observed by Galvan et al (2012).…”

Section: Csid and Their Main Features: Ground-based Observationsmentioning

confidence: 99%

Ionospheric Detection of Natural Hazards

Astafyeva

2019

Reviews of Geophysics

201

167

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“…Nowadays, denser Global Positioning System (GPS) observations provide important data for the study of ionospheric variations, allowing the continuous monitoring of large-scale ionospheric disturbances caused by typhoons [11][12][13][14] and earthquakes [15][16][17]. The characteristics of traveling ionospheric disturbances (TIDs) are consistent with the theory of gravity waves.…”

Section: Introductionmentioning

confidence: 83%

Traveling Ionospheric Disturbances Characteristics during the 2018 Typhoon Maria from GPS Observations

Wen

Jin

2020

Remote Sensing

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Typhoons often occur and may cause huge loss of life and damage of infrastructures, but they are still difficult to precisely monitor and predict by traditional in-situ measurements. Nowadays, ionospheric disturbances at a large-scale following typhoons can be monitored using ground-based dual-frequency Global Positioning System (GPS) observations. In this paper the responses of ionospheric total electron content (TEC) to Typhoon Maria on 10 July 2018 are studied by using about 150 stations of the GPS network in Taiwan. The results show that two significant ionospheric disturbances on the southwest side of the typhoon eye were found between 10:00 and 12:00 UTC. This was the stage of severe typhoon and the ionospheric disturbances propagated at speeds of 118.09 and 186.17 m/s, respectively. Both traveling ionospheric disturbances reached up to 0.2 TECU and the amplitudes were slightly different. The change in the filtered TEC time series during the typhoon was further analyzed with the azimuth. It can be seen that the TEC disturbance anomalies were primarily concentrated in a range of between −0.2 and 0.2 TECU and mainly located at 135–300° in the azimuth, namely the southwest side of the typhoon eye. The corresponding frequency spectrum of the two TEC time series was about 1.6 mHz, which is consistent with the frequency of gravity waves. Therefore, the upward propagating gravity wave was the main cause of the traveling ionospheric disturbance during Typhoon Maria.

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“…Nowadays, Global Navigation Satellite Systems (GNSS) observations provide various ways to estimate geophysical parameters, and one of the most important parameters is the total electron content (TEC) measurements for Earth's ionosphere research [1][2][3][4][5][6]. Due to the frequency dispersive property of the ionosphere, the ionospheric delay experienced by electromagnetic signals can be estimated by dual-frequency measurements.…”

Section: Introductionmentioning

confidence: 99%

Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter

2020

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The differential code bias (DCB) of the Global Navigation Satellite Systems (GNSS) receiver should be precisely corrected when conducting ionospheric remote sensing and precise point positioning. The DCBs can usually be estimated by the ground GNSS network based on the parameterization of the global ionosphere together with the global ionospheric map (GIM). In order to reduce the spatial-temporal complexities, various algorithms based on GIM and local ionospheric modeling are conducted, but rely on station selection. In this paper, we present a recursive method to estimate the DCBs of Global Positioning System (GPS) satellites based on a recursive filter and independent reference station selection procedure. The satellite and receiver DCBs are estimated once per local day and aligned with the DCB product provided by the Center for Orbit Determination in Europe (CODE). From the statistical analysis with CODE DCB products, the results show that the accuracy of GPS satellite DCB estimates obtained by the recursive method can reach about 0.10 ns under solar quiet condition. The influence of stations with bad performances on DCB estimation can be reduced through the independent iterative reference selection. The accuracy of local ionospheric modeling based on recursive filter is less than 2 Total Electron Content Unit (TECU) in the monthly median sense. The performance of the recursive method is also evaluated under different solar conditions and the results show that the local ionospheric modeling is sensitive to solar conditions. Moreover, the recursive method has the potential to be implemented in the near real-time DCB estimation and GNSS data quality check.

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Two‐Mode Ionospheric Disturbances Following the 2005 Northern California Offshore Earthquake From GPS Measurements

Cited by 21 publications

References 33 publications

Ionospheric Detection of Natural Hazards

Ionospheric Detection of Natural Hazards

Traveling Ionospheric Disturbances Characteristics during the 2018 Typhoon Maria from GPS Observations

Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter

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