Lars Ceranna

A 500-kiloton airburst over Chelyabinsk and an enhanced hazard from small impactors

Most large (over a kilometre in diameter) near-Earth asteroids are now known, but recognition that airbursts (or fireballs resulting from nuclear-weapon-sized detonations of meteoroids in the atmosphere) have the potential to do greater damage than previously thought has shifted an increasing portion of the residual impact risk (the risk of impact from an unknown object) to smaller objects. Above the threshold size of impactor at which the atmosphere absorbs sufficient energy to prevent a ground impact, most of the damage is thought to be caused by the airburst shock wave, but owing to lack of observations this is uncertain. Here we report an analysis of the damage from the airburst of an asteroid about 19 metres (17 to 20 metres) in diameter southeast of Chelyabinsk, Russia, on 15 February 2013, estimated to have an energy equivalent of approximately 500 (±100) kilotons of trinitrotoluene (TNT, where 1 kiloton of TNT = 4.185×1012 joules). We show that a widely referenced technique of estimating airburst damage does not reproduce the observations, and that the mathematical relations based on the effects of nuclear weapons—almost always used with this technique—overestimate blast damage. This suggests that earlier damage estimates near the threshold impactor size are too high. We performed a global survey of airbursts of a kiloton or more (including Chelyabinsk), and find that the number of impactors with diameters of tens of metres may be an order of magnitude higher than estimates based on other techniques. This suggests a non-equilibrium (if the population were in a long-term collisional steady state the size-frequency distribution would either follow a single power law or there must be a size-dependent bias in other surveys) in the near-Earth asteroid population for objects 10 to 50 metres in diameter, and shifts more of the residual impact risk to these sizes.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data constrained assimilation systems in the middle atmosphere at northern hemisphere mid-latitudes. Systematic comparisons between observations, the Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System (IFS) cycles 38r1 and 38r2, the NASAs Modern Era Retrospective analysis for Research and Applications (MERRA) re-analyses and the free running climate Max Planck Institute Earth System Model (MPI-ESM-LR) are carried out in both temporal and spectral domains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15-20 days. At shorter time-scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project (ARISE) that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Coherent ambient infrasound recorded by the International Monitoring System

GEOPHYSICAL RESEARCH LETTERS, VOL. 40, doi:10.1029/2012GL054329, 2013 Coherent ambient infrasound recorded by the International Monitoring System Robin S. Matoza, 1,2 Matthieu Landes, 1 Alexis Le Pichon, 1 Lars Ceranna, 3 and David Brown 4 Received 22 October 2012; revised 4 December 2012; accepted 4 December 2012. 2011] and severe weather [Hetzer et al., 2008]. The capability of the IMS infrasonic network to detect signals of interest exhibits significant spatiotemporal variation, which is in part controlled by station-specific ambient infrasonic noise [Le Pichon et al., 2009; Green and Bowers, 2010]. [ 3 ] Each station of the IMS infrasonic network is a micro- barometer or microphone array, with at least four sensor elements spatially separated with apertures of up to a few kilometers. The arrays are designed such that wind noise will be incoherent (not spatially correlated) between elements, while real acoustic waves will be coherent (spatially correlated). [ 4 ] Wind is the dominant noise source in the frequency band 0.01–5 Hz [Walker and Hedlin, 2010]. At a given infrasound station, wind variations can account for 4 orders of magnitude dif- ference in the background noise power spectral density (PSD) at a particular frequency [Hedlin et al., 2002; Bowman et al., 2005; Brown et al., 2011]. Wind noise PSD probability varies with time of day, season, and geographic location [Bowman et al., 2005]. Previous IMS infrasound noise studies [e.g., Bowman et al., 2005] have considered raw ambient PSD probability without dis- tinguishing between incoherent wind noise and ambient coherent infrasonic signals generated by repetitive natural or anthropo- genic processes. However, it is well known that repetitive coher- ent infrasonic signals (sometimes called “clutter”) present practical constraints on identifying target infrasonic signals of interest [e.g., Evers and Haak, 2001; Hetzer and Waxler, 2009]. [ 5 ] Here we present summary statistics of coherent infra- sound recorded by the IMS network during 2005–2010, identified by systematic broadband (0.01 to 5 Hz) array pro- cessing. Our work represents a first attempt at statistically and systematically characterizing coherent ambient infra- sound recorded by the IMS. [ 1 ] The ability of the International Monitoring System (IMS) infrasound network to detect atmospheric nuclear explosions and other signals of interest is strongly dependent on station- specific ambient noise. This ambient noise includes both incoherent wind noise and real coherent infrasonic waves. Previous ambient infrasound noise models have not distinguished between incoherent and coherent components. We present a first attempt at statistically and systematically characterizing coherent infrasound recorded by the IMS. We perform broadband (0.01–5 Hz) array processing with the IMS continuous waveform archive (39 stations from 1 April 2005 to 31 December 2010) using an implementation of the Progressive Multi-Channel Correlation algorithm in log- frequency space. From these results, we estimate multi-year 5th, 50th, and 95th percentiles of the RMS pressure of coherent signals in 15 frequency bands for each station. We compare the resulting coherent infrasound models with raw power spectral density noise models, which inherently include both incoherent and coherent components. Our results indicate that IMS arrays consistently record coherent ambient infrasound across the broad frequency range from 0.01 to 5 Hz when wind noise levels permit. The multi-year averaging emphasizes continuous signals such as oceanic microbaroms, as well as persistent transient signals such as repetitive volcanic, surf, thunder, or anthropogenic activity. Systematic characterization of coherent infrasound detection is important for quantifying a station’s recording envi- ronment, signal-to-noise ratio as a function of frequency and direction, and overall performance, which all influence the detection probability of specific signals of interest. Citation: Matoza, R. S., Landes, M., Le Pichon, A., Ceranna, L., and Brown, D. (2013), Coherent ambient infrasound recorded by the International Monitoring System, Geophys. Res. Lett. 40, doi: 10.1029/2012GL054329. 2. Data and Methods [ 6 ] We consider data from 39 IMS infrasound stations (Figures 1a and 1b) from 1 April 2005 to 31 December 2010. The 39 stations represent the 42 IMS stations certified as of 1 December 2010 minus 3 stations for which problems were en- countered with metadata or data availability. Since the IMS net- work is currently under construction, data availability varies throughout the time period considered (Figure 1b). Each station consists of an array of at least four sensors with a flat response from 0.01 to 8 Hz (sampled at 20 Hz) and a sensitivity of about 0.1 mPa/count. Array aperture, geometry, and number of ele- ments (Figure 1a) varies between stations of the IMS network [Christie and Campus, 2010]; this is the principal limitation to systematic data analysis. However, in aiming to make our results as comparable as possible between stations, we perform data processing with the same parameters for all stations. [ 7 ] We perform array processing using the Progressive Multi-Channel Correlation algorithm (PMCC) [Cansi, 1995]. PMCC estimates wavefront parameters (e.g., back azimuth, 1. Introduction [ 2 ] The International Monitoring System (IMS) global infrasonic network is designed to detect atmospheric nuclear explosions anywhere on the planet [Christie and Campus, 2010]. The network also has potential application in monitoring natural hazards such as large volcanic explosions [Matoza et al., CEA/DAM/DIF, Arpajon, France. Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA. BGR, Hannover, Germany. CTBTO, Vienna, Austria. Corresponding author: R. S. Matoza, Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093-0225, USA. (rmatoza@ucsd.edu) ©2012. American Geophysical Union. All Rights Reserved. /0094-8276/13/10.1029/2012GL054329,

Contribution of Infrasound Monitoring for Atmospheric Remote Sensing

A number of International Monitoring System (IMS) type infrasound stations are now operating for many years. Continuous automatic processing of the data is being performed in the [0.02–4] Hz frequency band in order to detect and characterize coherent infrasonic waves. A large number of detections are associated with natural phenomena. Ocean wave interactions are quasi-permanent sources of infrasonic waves detected on a global scale. Their monitoring reveals clear periodic trends in the detected bearings and signal amplitude, providing further confirmation that long-range propagation strongly depends on the atmospheric conditions. Ocean swells are then valuable sources for global atmospheric monitoring since pressure waves can be generated continuously over long duration, allowing investigations in the seasonal and diurnal fluctuations of the atmosphere. Signals from volcanic eruptions also offer a unique opportunity for atmospheric studies. At large propagation ranges from volcanoes, infrasound measurements can be used as input of inversion procedures to delineate the vertical structure of the wind in a range of altitude where ground-based or satellite measurements are rare. Such studies provide new insights on quantitative relationships between infrasonic observables and atmospheric specifications.

Global Scale Monitoring of Acoustic and Gravity Waves for the Study of the Atmospheric Dynamics

The development of the Infrasound International Monitoring System, used for the verification of the Comprehensive nuclear Test Ban Treaty, represents a powerful tool to measure permanently, at a global scale and over large periods of time, the characteristics of the waves and dynamics of the atmosphere in relation with the climate. The first way is to monitor quasi-continuous infrasound sources such as ocean swells or volcanic eruptions to determine the fluctuations of the stratosphere and mesosphere in relation to the activity of planetary waves and large scale polar disturbances such as Vortex Intensification or Sudden Stratospheric Warming. The second way is to monitor gravity waves which are observed in the lower frequency range of the infrasound data. Large scale waves, mainly produced in tropical regions, influence the mean circulation of the middle atmosphere by transporting moment and energy from tropical to polar regions with a possible role on tropospheric climate. This paper demonstrates through different examples the potential of the network to observe these waves as well as changes in the atmospheric wave guide in relation to atmospheric parameters. As the network will provide long duration observations, it is suggested to use them to study the atmosphere in relation with the climate evolution.

CTBT infrasound network performance to detect the 2013 Russian fireball event

The explosive fragmentation of the 2013 Chelyabinsk meteorite generated a large airburst with an equivalent yield of 500 kT TNT. It is the most energetic event recorded by the infrasound component of the Comprehensive Nuclear-Test-Ban Treaty-International Monitoring System (CTBT-IMS), globally detected by 20 out of 42 operational stations. This study performs a station-by-station estimation of the IMS detection capability to explain infrasound detections and nondetections from short to long distances, using the Chelyabinsk meteorite as global reference event. Investigated parameters influencing the detection capability are the directivity of the line source signal, the ducting of acoustic energy, and the individual noise conditions at each station. Findings include a clear detection preference for stations perpendicular to the meteorite trajectory, even over large distances. Only a weak influence of stratospheric ducting is observed for this low-frequency case. Furthermore, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

Ground Truth Events: Assessing the Capability of Infrasound Networks Using High Resolution Data Analyses

The purpose of building and maintaining an infrasound network is to be able to detect, identify, and locate low-frequency atmospheric pressure disturbances. In order to assess the capability of such a network, and to recognise potential weaknesses, the system must be tested using signals from well understood sources. Events which generate such signals are referred to as ground truth and are defined as being events for which the source location, origin time and acoustic generation mechanism are known through independent means. In ideal circumstances, a measure of the source magnitude should also be ascertained, and parameters influencing the acoustic radiation pattern such as local terrain and ground cover should be identified. Similar to seismic ground truth parameters (e.g., Bondar et al. 2004a), the infrasound ground truth parameters are associated with only the source. Meteorological parameters which influence the propagation of the acoustic waves (e.g., temperature and wind) are not considered ground truth, and it is often the accuracy of these atmospheric parameters that we wish to test using signals from ground truth events.

Remote Infrasound Monitoring of Mount Etna: Observed and Predicted Network Detection Capability

Volcanic eruptions are valuable calibrating sources of infrasonic waves worldwide detected by the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO) and other experimental stations. In this study, we assess the detection capability of the European infrasound network to remotely detect the eruptive activity of Mount Etna. This well-instrumented volcano offers a unique opportunity to validate attenuation models using multi-year near-and far-field recordings. The seasonal trend in the number of detections of Etna at the IS48 IMS station (Tunisia) is correlated to fine temporal fluctuations of the stratospheric waveguide structure. This observed trend correlates well with the variation of the effective sound speed ratio which is a proxy for the combined effects of refraction due to sound speed gradients and advection due to along-path wind on infrasound propagation. Modeling results are consistent with the observed detection capability of the existing regional network. In summer, during the downwind season, a minimum detectable amplitude of ~10 Pa at a reference distance of 1 km from the source is predicted. In winter, when upwind propagation prevails, detection thresholds increase up to ~100 Pa. However, when adding four experimental arrays to the IMS network, the corresponding thresholds decrease down to ~20 Pa in winter. The simulation results provide here a realistic description of long- to mid-range infrasound propagation and allow predicting fine temporal fluctuations in the European infrasound network performance with potential application for civil aviation safety.

Toward an Improved Representation of Middle Atmospheric Dynamics Thanks to the ARISE Project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions.

Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile

The two major explosive phases of the 22–23 April 2015 eruption of Calbuco volcano, Chile produced powerful seismicity and infrasound. The eruption was recorded on seismo-acoustic stations out to 1,540 km and on 5 stations (IS02, IS08, IS09, IS27, and IS49) of the International Monitoring System (IMS) infrasound network at distances from 1,525 to 5,122 km. The remote IMS infrasound stations provide an accurate explosion chronology consistent with the regional and local seismo-acoustic data, and with previous studies of lightning and plume observations. We use the IMS network to detect and locate the eruption signals using a brute-force, grid-search, cross-bearings approach. After incorporating azimuth deviation corrections from stratospheric cross-winds using 3D ray-tracing, the estimated source location is 172 km from true. This case study highlights the significant capability of the IMS infrasound network to provide automated detection, characterization, and timing estimates of global explosive volcanic activity. Augmenting the IMS with regional seismo-acoustic networks will dramatically enhance volcanic signal detection, reduce latency, and improve discrimination capability.