The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent is the surface-guided Lamb wave ( ≲ 0.01 Hz), which we observed propagating for four (+three antipodal) passages around the Earth over six days. Based on Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally-detected infrasound (0.01–20 Hz), long-range (~10,000 km) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. We highlight exceptional observations of the atmospheric waves.

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On 15 February 2013, a large Earth‐impacting fireball disintegrated over the Ural Mountains. This extraordinary event is, together with the 1908 Tunguska fireball, among the most energetic events ever instrumentally recorded. It generated infrasound returns, after circling the globe, at distances up to ~85,000 km, and was detected at 20 infrasonic stations of the global International Monitoring System (IMS). For the first time since the establishment of the IMS infrasound network, multiple arrivals involving waves that traveled twice round the globe have been clearly identified. A preliminary estimate of the explosive energy using empirical period‐yield scaling relations gives a value of 460 kt of TNT equivalent. In the context of the future verification of the Comprehensive Nuclear‐Test‐Ban Treaty, this event provides a prominent milestone for studying in detail infrasound propagation around the globe for almost 3 days as well as for calibrating the performance of the IMS network.

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 midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute-Earth System Model-Low Resolution (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 that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

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.

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We report on a multi-technique analysis using publicly available data for investigating the huge, accidental explosion that struck the city of Beirut, Lebanon, on August 4, 2020. Its devastating shock wave led to thousands of injured with more than two hundred fatalities and caused immense damage to buildings and infrastructure. Our combined analysis of seismological, hydroacoustic, infrasonic and radar remote sensing data allows us to characterize the source as well as to estimate the explosive yield. The latter is determined within 0.13 to 2 kt TNT (kilotons of trinitrotoluene). This range is plausible given the reported 2.75 kt of ammonium nitrate as explosive source. As there are strict limitations for an on-site analysis of this catastrophic explosion, our presented approach based on data from open accessible global station networks and satellite missions is of high scientific and social relevance that furthermore is transferable to other explosions.

SUMMARY The nonlinear interaction of ocean surface waves produces coherent infrasound noise—microbaroms—between 0.1 and 0.5 Hz. Microbaroms propagate through the atmosphere over thousands of kilometres due to low absorption and efficient ducting between the ground and the stratopause. These signals are globally and permanently detected by the International Monitoring System (IMS) infrasound network, which has been established to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty. At the International Data Centre (IDC) in Vienna, where IMS data are routinely processed, microbarom detections appear in overlapping frequency bands, and are treated as false alarms. Therefore, understanding the variability in microbarom detections is essential to support the IDC in the reduction of the false alarm rate. In this study, microbarom amplitudes and the direction of arrivals at the German infrasound station IS26 were modelled. For the simulations, the source was described by an operational ocean wave interaction model, and the signal amplitude was modelled using a semi-empirical attenuation relation. This relation strongly depends on middle atmosphere (MA; i.e. 15–90 km altitude) dynamics; however, vertical temperature and wind profiles, provided by numerical weather prediction (NWP) models, exhibit significant biases and differences when compared with high-resolution light detection and ranging instrument (lidar) soundings in altitudes where infrasound signals propagate. To estimate uncertainties in the modelled amplitude, a fully autonomous lidar for MA temperature measurements was installed at IS26. Temperature and wind perturbations, considering observed biases and deviations, were added to the operational high-resolution atmospheric model analysis produced by the European Centre for Medium-Range Weather Forecasts. Such uncertainties in horizontal winds and temperature strongly impact propagation conditions, explaining almost 97 per cent of the actual detections, compared to 77 per cent when using the direct output of the NWP model only. Incorporating realistic wind and temperature uncertainties in NWP models can thus significantly improve the understanding of microbarom detections as well as the detection capability of a single station throughout the year.