Detecting volcanic plume signatures on GNSS signal, Based on the 2014 Sakurajima Eruption

Cegla, Adam; Rohm, Witold; Lasota, Elżbieta; Biondi, Riccardo

doi:10.1016/j.asr.2021.08.034

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…As the 15 January 2022 Tonga volcanic explosion and resulting tsunami demonstrated, early warning systems targeting volcanic-tsunamis should be formulated as multi-hazard early warning systems integrated into the regional tsunami warning systems. Such a system would be composed of local volcanic and sea-level monitoring capabilities (Andronico et al, 2021;Ripepe et al, 2021;Selva et al, 2021), seismic (La Rocca et al, 2004;Pino et al, 2004), GNSS (Cegla et al, 2022;Lee et al, 2015), infrasound (Matoza et al, 2014;Kurokawa et al, 2020;Werner-Allen et al, 2005), hydroacoustic (Cecioni et al, 2014;Chadwick et al, 2012;Caplan-Auerbach et al, 2001;Caplan-Auerbach et al, 2014) and meteorological (Silvestri et al, 2019) sensors. This is in line with the target ''g'' of the Sendai Framework for Disaster Risk Reduction 2015-2030 (https:// www.undrr.org/publication/sendai-frameworkdisaster-risk-reduction-2015-2030), which emphasizes the need to substantially increase the availability of and access to multi-hazard early warning systems and disaster risk information and assessments to people by 2030.…”

Section: Discussionmentioning

confidence: 99%

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

Necmioğlu

Heidarzadeh

Vougioukalakis

et al. 2023

Pure Appl. Geophys.

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The destructive tsunami on 22 December 2018 due to the flank collapse of the Anak Krakatau volcano was a bitter reminder of large tsunami risks and of the shortcomings of the existing tsunami warning systems for atypical sources (tsunamis generated by non-seismic and complex sources). In the Mediterranean, several tsunamis were generated by landslides associated with volcanic systems in the past.The volcanic unrest experienced in 2011–2012 on the Santorini volcanic island in the Southern Aegean Sea pointed out the need to identify and quantify tsunami hazard and risk due to possible flank instability which may be triggered as a result of volcanic unrest or nearby seismotectonic activities. Inspired from this need, in this study we examined three possible landslide scenarios in Santorini Island with tsunamigenic potential. The results show that the scenarios considered in our study are able to generate significant local tsunamis impacting Santorini and the nearby islands, as well as producing significant impact along the coasts of the Southern Aegean Sea. While maximum tsunami amplitudes/arrival time ranges are 1.2 m/30-90 min for locations in the Greek-Turkish coasts in the far field, they are in the order of ≈60 m/1-2 min for some locations at the Santorini Island. The extreme tsunami amplitudes and short arrival times for locations inside the Santorini Island is a major challenge in terms of tsunami hazard warning and mitigation. As an effort to address this challenge, a discussion on the requirements for local tsunami warning system addressing atypical sources in the context of multi-hazard disaster risk reduction is also provided.

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Section: Discussionmentioning

confidence: 99%

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

Necmioğlu

Heidarzadeh

Vougioukalakis

et al. 2023

Pure Appl. Geophys.

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“…High-resolution NWM raytracing tropospheric delay has been used to evaluate and validate GNSS tropospheric delay (Andrei and Chen 2009;Li et al 2015). In addition, comparing GNSS tropospheric and NWM tropospheric delays is seemingly useful for detecting possible increases in volcanic activity (Cegla et al 2022). However, these advantages do not indicate that NWM tropospheric delays are more accurate than GNSS tropospheric delays.…”

Section: Introductionmentioning

confidence: 99%

Characteristic differences in tropospheric delay between Nevada Geodetic Laboratory products and NWM ray-tracing

et al. 2023

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Numerical weather models (NWMs) are important data sources for space geodetic techniques. Additionally, the Global Navigation Satellite System (GNSS) provides many observations to continuously improve and enhance the NWM. Existing comparative analysis experiments on NWM tropospheric and GNSS tropospheric delays suffer from being conducted in highly specific regions with limited spatial coverage; furthermore, the length of time for the experiment is too short for analyzing seasonal characteristics, and the insufficient number of stations limits spatial density, making it difficult to obtain the equipment-dependent distribution characteristics. After strict quality control and data preprocessing, we have calculated and compared the bias and standard deviation of tropospheric delay for approximately 7000 selected Nevada Geodetic Laboratory (NGL) GNSS stations in 2020 with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) hourly ray-traced tropospheric delay for the same group of stations. Characterizations in time, space, and linkage to receivers and antennas reveal positive biases of approximately 4 mm in the NGL zenith tropospheric delay (ZTD) relative to the NWM ZTD over most of the globe; moreover, there is a seasonal amplitude reaching 6 mm in the bias, and an antenna-related mean bias of approximately 1.6 mm in the NGL tropospheric delay. The obtained results can be used to provide a priori tropospheric delays with appropriate uncertainties; additionally, they can be applied to assess the suitability of using NWMs for real-time positioning solutions.

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“…Most recently, Cegla et al. (2022) investigated the 2014 Sakurajima Eruption, by a comparison of Zenith Total Delays (ZTDs) from GNSS and ray‐tracing methods.…”

Section: Introductionmentioning

confidence: 99%

“…Modeling of volcanic plumes was first shown by Houlié et al (2005a) for the eruption of Miyakejima volcano (Japan) and Mount St.Helens (Houlié et al, 2005b) and this approach was developed further by Grapenthin et al (2013). Most recently, Cegla et al (2022) investigated the 2014 Sakurajima Eruption, by a comparison of Zenith Total Delays (ZTDs) from GNSS and ray-tracing methods.…”

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confidence: 99%

Detecting Signatures of Convective Storm Events in GNSS‐SNR: Two Case Studies From Summer 2021 in Switzerland

Aichinger‐Rosenberger,

Aregger,

Kopp

et al. 2023

Geophysical Research Letters

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Global Navigation Satellite Systems (GNSS) are not only a state‐of‐the‐art sensor for positioning and navigation applications but also a valuable tool for remote sensing. Through the usage of L‐band carrier frequencies, GNSS acts as an all‐weather‐operation system, offering substantial benefits compared to optical systems. Nevertheless, severe weather can still have an impact on the strength of signals received at a ground station, as we show in this study. We investigate GNSS Signal‐to‐Noise Ratio (SNR) observations during two severe convective storm events over the city of Zurich, Switzerland. We make use of a GNSS‐SNR‐based algorithm originally developed for the detection of hail particles from volcanic eruptions. Results indicate that, although GNSS observations are considered to be fairly insensitive to the presence of hydrometeors, convective storm events are visible in SNR observations. SNR levels of affected satellites show a significant drop during event periods, which are determined by weather radar observations.

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Detecting volcanic plume signatures on GNSS signal, Based on the 2014 Sakurajima Eruption

Cited by 7 publications

References 25 publications

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

Landslide Induced Tsunami Hazard at Volcanoes: the Case of Santorini

Characteristic differences in tropospheric delay between Nevada Geodetic Laboratory products and NWM ray-tracing

Detecting Signatures of Convective Storm Events in GNSS‐SNR: Two Case Studies From Summer 2021 in Switzerland

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