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Meteor observations provide information about Solar System constituents and their influx onto Earth, their interaction processes in the atmosphere, as well as the neutral dynamics of the upper atmosphere. This study presents optical, radar, and infrasound measurements of a daytime fireball that occurred on 4 December 2020 at 13:30 UTC over Northeast Sweden. The fireball was recorded with two video cameras, allowing a trajectory determination to be made. The orbital parameters are compatible with the Northern Taurid meteor shower. The dynamic mass estimate based on the optical trajectory was found to be 0.6–1.7 kg, but this estimate can greatly vary from the true entry mass significantly due to the assumptions made. The meteor trail plasma was observed with an ionosonde as a sporadic E-like ionogram trace that lasted for 30 min. Infrasound emissions were detected at two sites, having propagation times consistent with a source location at an altitude of 80–90 km. Two VHF specular meteor radars observed a 6 minute long non-specular range spread trail echo as well as a faint head echo. Combined interferometric range-Doppler analysis of the meteor trail echoes at the two radars, allowed estimation of the mesospheric horizontal wind altitude profile, as well as tracking of the gradual deformation of the trail over time due to a prevailing neutral wind shear. This combined analysis indicates that the radar measurements of long-lived non-specular range-spread meteor trails produced by larger meteoroids can be used to measure the meteor radiant by observing the line traveled by the meteor. Furthermore, a multistatic meteor radar observation of these types of events can be used to estimate mesospheric neutral wind altitude profiles.

Seismic arrays enhance signal detection and parameter estimation by exploiting the time-delays between arriving signals on sensors at nearby locations. Parameter estimates can suffer due to both signal incoherence, with diminished waveform similarity between sensors, and aberration, with time-delays between coherent waveforms poorly represented by the wave-front model. Sensor-to-sensor correlation approaches to parameter estimation have an advantage over direct beamforming approaches in that individual sensor-pairs can be omitted without necessarily omitting entirely the data from each of the sensors involved. Specifically, we can omit correlations between sensors for which signal coherence in an optimal frequency band is anticipated to be poor or for which anomalous time-delays are anticipated. In practice, this usually means omitting correlations between more distant sensors. We present examples from International Monitoring System seismic arrays with poor parameter estimates resulting when classical f-k analysis is performed over the full array aperture. We demonstrate improved estimates and slowness grid displays using correlation beamforming restricted to correlations between sufficiently closely spaced sensors. This limited sensor-pair correlation (LSPC) approach has lower slowness resolution than would ideally be obtained by considering all sensor-pairs. However, this ideal estimate may be unattainable due to incoherence and/or aberration and the LSPC estimate can often exploit all channels, with the associated noise-suppression, while mitigating the complications arising from correlations between very distant sensors. The greatest need for the method is for short-period signals on large aperture arrays although we also demonstrate significant improvement for secondary regional phases on a small aperture array. LSPC can also provide a robust and flexible approach to parameter estimation on three-component seismic arrays.

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.