PICO
This session invites studies focused on methods and applications for event detection and location using seismic, hydroacoustic, infrasound, and radionuclide technologies. Contributions on the enhancement of seismic velocity and regional seismic travel-time models, as well as the modeling of acoustic wave propagation, ATM of radionuclides, and contributions regarding the data fusion of various technologies are welcome. The session invites contributions on Nuclear-Test-Ban Monitoring using either IMS or OSI instrumentation, data or methods. This can be either in the context of explosion monitoring of actual or historic events or by taking into account fictitious scenarios like the National Data Centre Preparedness Exercises (NPE).
Contributions to the civil or scientific use of IMS data are encouraged. Civil applications include disaster risk reduction through early warning or hazard assessments for earthquakes, tsunamis, and volcanic activity. Earth science applications encompass analyses on different natural or anthropogenic sources as well as studies on climate change, ocean processes, solid Earth structure, and atmospheric circulation. Finally, contributions on the application of machine learning in event detection, localization, discrimination, and monitoring are highly encouraged.
Radionuclide monitoring is complementary to seismic, hydroacoustic, and infrasound wave monitoring technologies used in verification, and it is the only one that can discriminate and confirm whether an explosion detected and located is indicative of a military nuclear explosion. Therefore, to understand radioactive particles and noble gas prompt releases from underground nuclear explosions, their transport in the atmosphere to radionuclide monitoring stations, and to discriminate nuclear explosion generated radioisotopes from artificially produced ones, generated and released by nuclear reactors, particle accelerators, or radionuclide generators, one must accurately and numerically simulate the explosion phase, the interaction of the explosive energy released with the fractured hosting rock, and cavity formation, the radionuclide generation and their circulation within the cavity, and the eventual prompt release or seepage of the radionuclide gases to the atmosphere. To support this daunting task, LLNL has developed an HPC-based comprehensive numerical framework to simulate, from source-to-atmosphere, the radioisotope gas releases by coupling a non-linear explosion hydrocode to a geomechanical code that converts explosion-induced damage to rock permeability, which is a key parameter to subsurface and surface coupled gas transport codes. The resulting gas releases source to the atmosphere is then used as an input to a global atmospheric circulation code to reach the monitoring stations. We illustrate the onset of the different regimes and their combined effect of flow, heat and mass transport of different gas species, the fraction of molten rock and their impact on the noble gas fractionation. We also present a sensitivity analysis of the effect of the outer cavity boundary condition on the heat loss and cooling to the adjacent rock formation and its eventual release to the atmosphere. We demonstrate several scenarios of underground prompt releases to the atmosphere using a first-ever fully coupled prompt subsurface-to-atmospheric transport without ad-hoc boundary conditions between physics-based domains, or handshakes between different numerical codes. We also demonstrate using HPC-empowered numerical hypothetical explosion scenarios, the benefits of the proposed technology versus the common approaches. We will conclude by exploring physics informed ML schemes for developing surface responses of the end-to-end simulation framework to anthropogenic explosions. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
How to cite: Ezzedine, S., Vorobiev, O., Herbold, E., Sun, Y., Hao, Y., and Myers, S.: End-to-End HPC Numerical Simulations of Underground Explosions, Cavity Formation and Circulation Processes, Subsurface Gas Transport, and Prompt Atmospheric Releases, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14449, https://doi.org/10.5194/egusphere-egu25-14449, 2025.
The radionuclide network of the International Monitoring System for the Comprehensive Nuclear-Test-Ban Treaty is in place for the detection of tiny atmospheric traces of radioactive fission and activation products generated by nuclear explosions. Atmospheric transport modelling supports the assessment of potential source regions and checks for consistency with explosion sites.
All radionuclide station sniff for particulate radionuclides, a part of it is additionally equipped with noble gas systems measuring radioactive xenon isotopes. Those are of particular importance as they are more likely to escape from underground nuclear explosions and the inert character is advantageous for simulating atmospheric transport.
A central challenge of radioxenon monitoring remains to classify radioactive xenon emissions originating from other sources as isotope production facilities and other reactors. This attribution was also crucial for the interpretation of radioxenon detections in the aftermath of the announced North Korean nuclear test explosions.
Another radioactive noble gas isotope krypton-85. It is not part of the list of CTBT relevant isotopes due to its large background (half-life 10.8 years) and smaller nuclear yield. Large quantities of krypton-85 have been released into the atmosphere by nuclear fuel reprocessing both for military and civilian purposes. This created a significant atmospheric background due to the long krypton-85 half-life. In the context of discussing monitoring possibilities for a future fissile material cut-off krypton-85 is potentially suitable as indicator for the detection of clandestine plutonium separation. The “Bundesamt für Strahlenschutz” (BfS, Federal Office for Radiation Protection) has been operating a network with weekly air sample collection at up to 26 locations in Germany and worldwide since 1973. For the data from 2005-2024 backward ATM is performed for more than 10000 samples from about 10 stations. Taking advantage of the long time series we analyse if backward atmospheric transport modelling allows even in the coarse time resolution of weekly samples for attribution to different emitters on the Northern Hemisphere. The effect of the shutdown of the Selllafield reprocessing facility on the European network is analysed as example.
How to cite: Ross, J. O. and Brander, S.: Assessment of emissions from noble gas background sources: what can we learn from atmospheric transport modelling for long term krypton-85 measurements?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19799, https://doi.org/10.5194/egusphere-egu25-19799, 2025.
The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) relies on its International Monitoring System (IMS) to detect radionuclide releases, which can indicate potential nuclear tests. By using atmospheric transport modelling (ATM), the CTBTO aims to establish links between detecting stations and corresponding source locations. When detection is limited to a single event within a narrow time window or between neighbouring stations, operational analysis typically generates large possible source regions that require further refinement. Multiple detections offer a unique opportunity for a more detailed analysis, allowing advanced methods to be applied for more accurate identification of the source location.
Recently, elevated levels of radioxenon were detected at multiple IMS locations in and around the Japanese region, including Takasaki, Wake Island, and the non-IMS system at Horonobe. These detections exceeded historical levels, emphasizing the need for a more detailed analysis. The dense network of measurement stations in this area presents an opportunity to explore advanced methods for source localization, reducing the uncertainty, and to discuss the implications of these findings on the monitoring of radioxenon isotopes.
How to cite: Tipka, A., Bare, J., Schoemaker, R., and Krysta, M.: Reducing Uncertainty in Nuclear Test Detection: An Analysis of Multiple IMS Detections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20246, https://doi.org/10.5194/egusphere-egu25-20246, 2025.
In November 2024, an Ml ~1.5-2.0 underwater explosion occurred in Danish waters north of Bornholm Island. It was recorded by the Danish and Greenlandic national seismic networks as well as the Swedish national network. In addition, the event was captured by a nearby Distributed Acoustic Sensing (DAS) system deployed along a 120 km-long underwater fiber-optic cable. We investigated the event location by integrating data from these complementary recording systems, systematically assessing the trade-off between the number of DAS channels with respect to the number of permanent seismometers and the quality of the picks. Our results indicate horizontal uncertainties on the order of 2–3 km for the final event location. To further constrain the depth of the explosion and its yield, we conducted a spectral analysis of the seismograms, joined with a non-linear inversion of the P-waveforms at the closest station. The inferred source parameters are consistent with the known water depth and velocity at the explosion site, revealing that the event probably involved two distinct detonations located less than 10 m above the seafloor, each with an approximate 30 kg TNT equivalent yield. These findings highlight the advantages of combining conventional permanent seismic instrumentation with underwater DAS, thereby improving the detection and characterization of anthropogenic seismic sources and offering enhanced protection for critical submarine infrastructures.
How to cite: Mordret, A., Larsen, T., Voss, P., Jensen, E., Dahl-Jensen, T., Rinds, N., Lund, B., Roth, M., Donner, S., and Steinberg, A.: Combined (DAS/Seismometers) Seismic Analysis of an Underwater Explosion in the Baltic Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7200, https://doi.org/10.5194/egusphere-egu25-7200, 2025.
The global verification system established under the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is designed to detect all nuclear explosions on Earth. Seismic monitoring, one of the four verification technologies, relies on the International Monitoring System (IMS), a global network of sensor stations, to identify nuclear explosion signals. This study presents an application of Moment Tensor (MT) inversion analysis to assist individual States Parties through expert technical analysis (ETA) of IMS data and any additional datasets provided by the requesting State Party. MT inversion enables precise determination of parameters such as total seismic moment, focal mechanism, and source depth.
To evaluate this approach, we analyzed data from declared nuclear events in the Democratic People’s Republic of Korea (DPRK). For the most recent event, DPRK6 (2017/09/03), two methodologies were applied: (1) a regional moment tensor inversion in the time domain (TDMT, Dreger, 2003) and (2) a joint inversion using regional waveforms and teleseismic firstmotion polarities (Nayak and Dreger, 2015; Chi-Durán et al., 2024). The analysis included 4 regional waveforms (filtered between 20–50 s) and 81 teleseismic first-motion polarities from CTBTO stations. Known regional velocity models were used to model the synthetic waveforms (Ford et al., 2010; Dreger et al., 2021).
The TDMT approach achieved a high waveform fit and revealed a predominantly isotropic mechanism with a minor double-couple component. These findings are consistent with previous studies using other station datasets (e.g., Alvizuri and Tape, 2018; Chiang et al., 2018). The joint inversion further improved the waveform fit, with the isotropic component remaining dominant. The source-type lune plot confirmed a mechanism primarily characterized by isotropy. Current efforts aim to incorporate additional data, such as teleseismic waveforms, to refine the depth and other characteristics of the event across all declared DPRK events.
How to cite: Chi-Durán, R.: Moment Tensor Inversion Analysis of DPRK6 Nuclear Events Using CTBTO/IMS Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9831, https://doi.org/10.5194/egusphere-egu25-9831, 2025.
Throughout the recent period of announced nuclear testing by the Democratic People's Republic of Korea there has been a series of small magnitude seismic events detected in the vicinity of the test site. These events, reported by the International Data Centre of the Comprehensive Nuclear Test-Ban-Treaty Organisation, are only detected at regional seismic stations. It is of interest to the global CTBTO community if these events and the announced nuclear tests can be characterised using regional observations. We investigate the ratio of P- to Lg-wave amplitudes to discriminate between announced nuclear tests and presumed earthquakes in the vicinity of the test site. Investigating amplitude ratios independently at seismic stations overcomes path effects assuming that the events of interest are all located near to each other. There is a clear separation between the P/Lg ratios of announced nuclear tests and presumed earthquakes on the 3-component sensors at USRK and MDJ for events within 50km of the test site. Interestingly, the signals in the vicinity of the test site have low coherence across the USRK seismic array, likely due to effects from local geology at the array site. Effective discrimination comes from averaging the root-mean-square amplitudes of all three-components of the seismometer, and not on the beam made using vertical array elements. The Pg/Lg amplitude ratios are more consistent over the range of passbands investigated (1-18Hz) compared to Pn/Lg ratios. The P/Lg ratios of assumed mining events (the majority generating infrasound detections) in the vicinity of the test site are higher than earthquakes, however being more than 100km from the test site could generate different path effects to USRK. Discrimination between earthquakes and explosions in the vicinity of the DPRK test site using regional signals supports the technical verification of the CTBT.
© British Crown Owned Copyright 2024/AWE
How to cite: Merrett, M. and Selby, N.: The characterisation of announced nuclear tests and seismic events in the vicinity of the DPRK test site using P/Lg ratios at regional seismic stations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3160, https://doi.org/10.5194/egusphere-egu25-3160, 2025.
We present our work on training and the application of deep learning algorithms for the automated phase picking of body waves on the the IMS network. We train new IMS data based seismic phase pickers from both EQT and PhaseNet architectures. Phase picking is a necessary step before event localization and characterization and deep learning based models have been proven to perform well at this task. PhaseNet and EQTransformer are two prominent state-of-the-art phase picking algorithms that have been retrained on several different datasets.
Waveform data from primary and auxiliary stations is used in the training and evaluation. For training we use good quality picks from REB events between 2013 until 2023. We evaluate the performance in comparison with unseen evaluation REB phase picks and manual phase picks. We compare the performance with applying other pre-trained phase pickers to the IMS data to determine if already pre-trained models can be used satisfactory out of the box for seismological IMS data. We also evaluate the generalization ability of the two IMS data trained models by applying them to other non IMS seismological stations of the German Regional Seismic Network (GRSN).
We further train new phase pickers based on the PhaseNet architecture and a database of 20 years listed in the earthquake catalog of BGR. The models are trained and evaluated with manual phase picks of BGR analysts. We compare the performance of the newly trained models by also applying other pre-trained PhaseNet and EQTransformer based phase pickers on unseen data. We determine if existing pre-trained models can satisfactorily be used out of the box for phase picking on waveforms of the GRSN.
How to cite: Steinberg, A. and Gaebler, P.: Deep learning based phase picking on seismological IMS stations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7096, https://doi.org/10.5194/egusphere-egu25-7096, 2025.
Analysis of seismic records of local earthquakes and a series of underground chemical explosions conducted during the Source Physics Experiment (SPE) at the Nevada National Security Site (NNSS) have shown that at local distances (<200 km) the effectiveness of the single-station P/S ratio source discriminant is reduced, especially when seismic recordings from a sparse network of stations is used.
We used high performance computing to model high-frequency (0-10Hz) waveforms for 12 selected local earthquakes, with magnitudes ranging from 2.05 to 3.54, recorded by a network of seismic stations in the Rock Valley at NNSS. In addition, we performed a series of simulations of collocated isotropic and double-couple explosion sources in the Rock valley. The high-frequency wave propagation scattering was simulated by adding correlated small-scale stochastic perturbations to the Seismic Velocity Model of the Rock Valley (SVM). The recorded and synthetic waveforms were then analyzed to investigate the effects of source radiation and wave scattering effects on the simulated waveforms and P/S source discriminant.
The inclusion of correlated depth-dependent stochastic velocity perturbations in the GFM, improved the quality of simulated source radiation and local waveforms, which resulted in better reproduction of the observed spatial variations of the P/S discriminant. We found that the shallow wave scattering deforms the radiation pattern and amplitude of source generated P and S waves, thus reducing the efficiency of the P/S discriminant. Our simulations suggest that a good azimuthal stations coverage and the network averaging can improve the performance of the P/S discriminant at local distances.
How to cite: Pitarka, A., Walter, W., and Pyle, M.: Broad-band Modeling of Earthquakes in the Rock Valley, Nevada: Implication of Wave Propagation Effects on the P/S Source Discriminant , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12763, https://doi.org/10.5194/egusphere-egu25-12763, 2025.
The International Data Centre (IDC) of the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO) processes and analyses data from the International Monitoring System (IMS). This effort culminates in the daily production of the Reviewed Event Bulletin (REB), recognized as one of the most comprehensive global seismic bulletins.
This study compares the IDC REB bulletins with those produced by the National Earthquake Information Center (NEIC), one of the major organizations producing seismological bulletins, over a 20-year period (2004–2024). Specifically, we assess the consistency of events with IDC magnitudes (mb) greater than 4, identifying events that are either missed or uniquely included by the IDC. By examining discrepancies in epicenter locations, we aim to pinpoint regions with significant location differences and investigate whether these discrepancies correlate with global and regional network coverage or are randomly distributed.
Additionally, we explore potential connections between location discrepancies and the use of travel time, azimuth, and slowness correction models. Our findings aim to enhance the understanding of global seismic monitoring accuracy, contributing to improved data integration, event detection, and correction models.
How to cite: Qorbani Chegeni, E., Kebede Alamneh, F., Rambolamanana, G., and Graham, G.: Comparative Analysis of IDC REB Bulletins with NEIC Seismological Bulletin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4857, https://doi.org/10.5194/egusphere-egu25-4857, 2025.
At the International Data Centre (IDC), data received from the International Monitoring System (IMS) network goes through a three-step process (station processing, network processing and interactive review) to determine if a combination of detections can be built into an event. One of the major steps in determining if an event can be built or not, is the phase classification of the detected signals. For acoustic data, phases are determined during each process where in the first two steps, algorithms will automatically name and rename phases based on a set of criteria and thresholds. In the interactive review, analysts can change or rename phases for a final time to build or not build an event. Here, we analyze the number of phase changes at each IMS Infrasound and hydroacoustic station and compare the number of detections in each process database to examine how a detection contributes to building an event. Furthermore, the expansion of the operational stations of the IMS network is examined to understand how additional stations have altered the ability of the automatic and interactive processes to classify phases and build events. Ultimately, the results of this analysis can be used to improve the automatic IDC pipeline for acoustic phase classification and building events.
How to cite: Walsh, B. and Oliveira, T.: Understanding phase classification throughout the International Data Centre acoustic pipeline, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15641, https://doi.org/10.5194/egusphere-egu25-15641, 2025.
This work investigates the T-phase time residuals (defined as differences between the observed arrival times and their theoretical values) at IMS hydrophone stations HA11 and HA03 in the Pacific Ocean. The work is focused on T-phases from earthquakes in the Ring of Fire recorded between 2001 and 2024. Time residuals of T phases from these regions can typically range from minus 150 to 150 seconds. These disparities between expected and observed arrival times can present significant challenges when associating hydroacoustic signals to events built by automatic processing systems or by human analysts based on signals recorded by the IMS network. In this work, we shed light on the reasons for these high time-residual variabilities. We show that the time residuals in these regions depend on the location of the hypocentre along the subduction plate. Overall, time residuals go from negative (T phases arrive earlier than expected) to positive (later than expected) as the earthquake depth decreases along the subduction and approaches the Ocean Trench. We present general results for the Ring of Fire and detailed analyses for regions with different subduction angles in the trenches of Kermadec-Tonga, Mariana, Philippines, Nansei-Shoto, Kuril, Aleutian, and Peru-Chile.
How to cite: Oliveira, T., Khukhuudei, U., and Chi-Durán, R.: Time residuals at HA11 and HA03 for T-phases from deep earthquakes in the Ring of Fire, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4487, https://doi.org/10.5194/egusphere-egu25-4487, 2025.
As part of the Comprehensive Nuclear Test Ban Treaty Organisation (CTBTO), six hydroacoustic stations were installed. Although few in number, they record underwater acoustic waves that propagate over long distances via the SOFAR (SOund Fixing And Ranging) channel. Low-frequency coherent waves (< 40 Hz) are detected automatically by the PMCC (Progressive Multi-Channel Correlation) method. An average of 306 daily detections, with a Maximum Amplitude (MaxAmp) above 1 Pa, are reported. At this point, there is no identification made by any analyst of the source type (e.g. earthquake, volcanism, cryosphere, whales, airgun, anthropophonic explosion). Thus, the aim of this study is to develop an automatic source discrimination tool to support operational monitoring.
We analyze PMCC extractions from stations in the Atlantic (HA10), Indian (HA01, HA04, HA08) and Pacific (HA03, HA11) oceans over a period spanning January to Decembre 2023. The association to a source type is made in two stages. (i) We apply wave parameter and acoustic indices conditional statements to select typical signals with MaxAmp above 1.5 Pa for each type of source, except for airgun with MaxAmp of 1 Pa. (ii) The resulting catalog of extracted records are used to train a convolutional neural network of two layers and calibrate it by conformal prediction with Least Ambiguous set-value Classifier (LAC) score and a nominal error level of 0.05. All detections with a MaxAmp greater than 1 Pa are associated with one or more source types.
Over the year 2023, 111,260 coherent waves were extracted by PMCC on the 8 hydrophone triplets, of which 14,028 were associated to a source type using the ad hoc conditional statements. These records are associated to the right source type by the trained neural network at 92.5%. Overall, the classifier associated 75 ± 6% of records with one source. Significant differences in performance were observed between the hydrophone triplets. Results were lowest at hydrophone triplet HA10N (< 65%), while they were highest at HA04N (> 80%). This difference is due to the soundscape, with certain sources (earthquakes, volcanoes and croyspheres) being more difficult to discriminate. The criteria used to compile the reference catalog need to be improved to discriminate more accurately detections by source type.
How to cite: Fauvel, H., Oger, S., Cazau, D., Bazin, S., and Vergoz, J.: Automatic identification of sources recorded by the hydroacoustic stations of the International Monitoring System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11325, https://doi.org/10.5194/egusphere-egu25-11325, 2025.
Underwater communication cables are critical components of global infrastructure, carrying over 99% of international data traffic. On 14 March 2024, a significant disruption to this network occurred due to a cable break offshore Ivory Coast, leading to widespread internet outages in the west African region. To investigate the cause of this cable break, we analyze hydroacoustic data recorded between 6 March and 22 March on the two hydrophone triads (H10N and H10S) installed near Ascension Island by the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). We detect a low-frequency (< 60 Hz) signal on three northern and two southern triad hydrophones on 12 March 2024. The signal had a duration of 85 seconds on the north triad compared to 45 seconds on the south triad. We used the Generalized Cross-Correlation with Phase Transform method to show that the detected signal originated at a bearing of 38.8 ± 4.6°, consistent with the location of the cable break off Ivory Coast, and with steep bathymetric slopes mapped in the Trou Sans Fond Canyon. We do not observe associated signals on the nearby land-based seismic stations in Ghana and Ivory Coast, confirming the marine origin of this event. Additionally, template matching shows that the same signal was not recorded in the preceding and following 8 days, implying that this event was an isolated case. Given the scarcity of natural earthquakes offshore Ivory Coast, this combination of evidence suggests that the hydroacoustic signals are likely caused by a submarine landslide in the Trou Sans Fond Canyon. Our results show that investigating the causative submarine landslide events is also needed to realize the potential of these hydroacoustic methods for hazard risk assessment.
How to cite: Ingale, V. V., Parnell-Turner, R., Fan, W., Talling, P. J., and Neasham, J.: Hydroacoustic observations of a submarine landslide along Trou Sans Fond Canyon offshore Ivory Coast in March 2024 on CTBTO network, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5270, https://doi.org/10.5194/egusphere-egu25-5270, 2025.
The oceans are filled with acoustic waves, which are trapped in a low-velocity layer at about 1 km water depth. The sound speed of these waves strongly depends on the temperature. An increase in temperature will lead to an increase in the sound speed and hence shorter travel times. IMS hydro-acoustic stations measure these waves continuously and travel times can be obtained through the cross correlation of transient signals between different hydrophones. IMS hydro-acoustic station H10 near Ascension Island has been operational for nearly two decades. Although in place to detect nuclear-test explosion for the CTBT, H10 appeared well equipped to measure deep ocean temperature change. A decrease in the travel time between the two arrays was derived, being -0.002 s/yr. This corresponds to a deep ocean warming of 0.007 degC/yr, at about 900m water depth. As such, acoustic waves provide an independent and passively acquired measure of the temperature change in the deep ocean.
How to cite: Evers, L. G.: Decadal observations of deep ocean temperature change passively probed with acoustic waves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2547, https://doi.org/10.5194/egusphere-egu25-2547, 2025.
Large meteoroids entering Earth’s atmosphere are a well-known source of infrasound. During the supersonic entry of space material into the atmosphere, shock waves are emitted from the trajectory as a line source. Explosive fragmentation of the meteoroid may additionally produce one or multiple point source events. Both types of shock waves propagate as low-frequency acoustic waves, also known as infrasound, within the atmosphere and to the Earth’s surface. Such infrasound signals can be detected by adequate instrumentation at distances of hundreds to thousands of kilometers, after long range sound propagation within atmospheric ducts.
Using microbarometer arrays of national observation networks, like e.g. the Central and Eastern European Infrasound Network, and the International Monitoring System for the Comprehensive Nuclear-Test-Ban Treaty, such meteoroid events can be remotely identified, localized and characterized. Array signal processing using the Progressive Multi-Channel Correlation method and propagation modeling using Ray-Tracing and Parabolic Equation approaches are applied to estimate the origin of the acoustic signals along the meteoroid trajectories and to derive information about entry parameters and explosive yield.
This study focuses on the infrasound observation, event analysis and sound propagation of recent meteoroid events, including the Southern Atlantic Ocean fireball on the 7th of February, 2022, the El Hakimia fireball over Northern Algeria on the 7th of May, 2023 and the Ribbeck fireball over Eastern Germany on the 21st of January, 2024.
How to cite: Pilger, C. and Hupe, P.: Infrasound observation and propagation of recent meteoroid events , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8540, https://doi.org/10.5194/egusphere-egu25-8540, 2025.
Infrasound measurements play a critical role in global bolide detection and accurate location determination. However, significant mismatches frequently emerge between observed back azimuth angles and theoretical predictions derived from a bolide’s brightest emission point, especially under shallow entry conditions. In such instances, elongated acoustic traces across multiple trajectory segments induce large variations in back azimuth residuals. An investigation to quantifies the effects of varying entry angles on azimuth deviations over distances up to 15,000 km was carried out. The results show that shallow-angle entries can produce substantial discrepancies, complicating reliable geolocation at extended ranges. Conversely, steeper trajectories yield more consistent azimuth measurements, minimizing uncertainties. These findings demonstrate the necessity of incorporating entry geometry in infrasound analyses to refine bolide detection and bolster planetary defense. Additionally, this framework offers important considerations for other high-energy atmospheric phenomena, such as spacecraft re-entries, where accurate geolocation remains paramount.
SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.
How to cite: Silber, E.: Reducing uncertainties in bolide and space debris detection: The role of entry geometry in infrasound analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4030, https://doi.org/10.5194/egusphere-egu25-4030, 2025.
