Thomas Lecocq

Between 19 and 22 January 2026, the extratropical Cyclone Harry generated the highest individual wave height ever recorded in the Mediterranean Sea, causing widespread coastal flooding and erosion across the central basin. Here we combine oceanographic and meteorological observations, high-resolution morphodynamic datasets, hydrodynamic modelling, and regional microseism analysis to show that Harry produced the most severe coastal impacts of any Mediterranean cyclone in recent decades. Process-based XBeach and HEC-RAS simulations across 19 coastal sites in Sardinia, Malta, Sicily, and Calabria reveal unprecedented inundation extents strongly modulated by local geomorphology, with submarine canyons, buried palaeo-channels, and urban infrastructure amplifying wave setup and inland flooding. Concurrently, broadband seismic records from 55 Mediterranean stations show exceptional secondary microseism amplification, with Ionian stations reaching the highest amplitudes since the beginning of seismic recordings in 1990. Harry’s Microseism Reduced Amplitude exceeded previous storms and Mediterranean cyclones by more than fourfold, highlighting escalating coastal risk under climate-driven cyclone intensification.

Identifying volcanic transitions from quiescence to unrest and tracking subsurface evolution remains critically challenging. We analyzed continuous seismic records from Askja volcano (Iceland) from 2008--2024 using coda wave interferometry to track relative seismic velocity variations (dv/v) as a proxy for subsurface changes during renewed volcanic intrusion. This analysis is complemented with three additional methods: network covariance matrix analysis, Displacement Seismic Amplitude Ratio (DSAR) single-station analysis, and sensitivity kernel analysis, alongside GNSS, earthquake catalog, and meteorological datasets. Since August 2021, dv/v measurements revealed an abrupt transition from regular seasonal oscillations (±0.2\%) to predominantly negative values reaching -0.7\% near the inflation center, coinciding with 76 cm GNSS-detected ground uplift by August 2024. DSAR indicated higher seismic attenuation near the inflation source, suggesting volatile accumulation in the shallow subsurface through June 2022, followed by marked decreases associated with depressurization. Sensitivity kernel analysis demonstrated wave sensitivity reaches down to 3 km depth, encompassing the shallow reservoir levels. Integrated seismic observations revealed magma-induced seismic velocity drops, followed by system reorganization with frequency-dependent recovery, and finally establishment of a new state with hydrothermal circulation maintaining altered seismic properties. This approach demonstrates the effectiveness of continuous seismic monitoring for detecting volcanic unrest transitions and tracking evolving subsurface processes.

Interpreting amplitudes in Distributed Acoustic Sensing (DAS) data is challenging because the recorded signal is influenced by multiple factors.To differentiate the impact of fiber orientation from site effects, we develop expressions of axial strain for different body wave polarizations. These expressions consider a linear fiber segment with any orientation in space. From these we explore array geometry properties and the potential of the DAS transfer function as a polarization filter. This last property arises from the polarity inversion characteristic of shear waves and the averaging nature of the gauge length. If the gauge length is set to be a loop instead of a linear segment then the DAS will average all azimuth for a horizontal loop, canceling SH waves. For a vertical loop, all dips are averaged canceling SV waves traveling within the loop plane. These results could reflect a link between DAS and rotational seismology. From these transfers functions, we develop a low-cost forward model based on ray theory that predicts amplitude recorded in a DAS array. Differences in amplitude between the modeled and observed wavefields relate to local site amplification from which, we create an amplitude correction factor. We evaluated this method using active seismic experiments from the PoroTomo dataset, successfully identifying regions with anomalous high amplitude responses consistent with the recordings following a magnitude 4.3. The results, together with the main elements of our approach, are transferable in many new sensing strategies, including optimization of fiber deployment geometry, generations of synthetic data and the acceleration and improvement of existing location methods through DAS-specific amplitude and phase corrections.In summary, by exploiting the known directional sensitivity of DAS, we draw new insights from amplitude variations along the fiber array, treating energy loss as equally informative as energy gain in interpreting the wavefield.

Early-warning of landslide failure relies on understanding subsurface processes that drive slope destabilisation, including changes in moisture content or mechanical behaviour. Material heterogeneity in landslide systems causes spatiotemporal variation in these dynamic processes. There is therefore a need to develop methods that can detect and measure changes in the subsurface to inform landslide stability. Seismic monitoring can record information on the elastic behaviour of the ground in response to immediate and long-term processes, such as slope displacement and moisture variation. Here, we report on data acquired by a seismic network deployed at a slow-moving clay-rich landslide in North Yorkshire UK, representative of many landslides in clay-rich lowland slopes. The temporary network was operational for two years with the aim of understanding how the seismic response of the landslide varies between sensors deployed on parts of the landslide with distinctly different hydrogeological properties. We present an overview of the rationale and deployment procedure, as well as a preliminary assessment of data quality, event analysis, tilt observations, horizontal-to-vertical spectral ratio (H/V) ratio calculations, and ambient noise cross-correlation. We conclude that the moisture dynamics of the slope have a significant influence on observed data, and make further recommendations for the analysis of the dataset. Our study demonstrates the feasibility of analytical techniques using these data, promotes the unique dataset to foster further in-depth analysis, and encourages similar seismological deployments on active landslides.

Damaging earthquakes happened in the Hainaut coal basin (Belgium) in the 19th and 20th centuries but stopped after coal mining. We relocated 54 Hainaut earthquakes of the period 1965 and 1985 by using regional and local seismic phase measurements from recordings in and around Belgium. These new results finalise the Hainaut earthquake catalogue, derived from macroseismic data for the 1887–1965 period and instrumental records after 1965. This updated database allows us to discuss the origin of this intriguing seismicity. Computed focal depths show that the strongest earthquakes before 1985 occurred inside the Upper Palaeozoic part of the Brabant Parautochton, probably below the deepest parts of the coal mines. The shallowness of this seismicity, its spatial link with the coal basin, the compressive to strike-slip focal mechanisms of the stronger earthquakes between 1965 and 1985 and the large quantity of coal mass removal all match with worldwide observations of mining-triggered earthquakes. The earthquake mechanisms agree with the local, compressive to transpressive stress regime derived from differences in upper crustal density and topography that make the Hainaut area more sensitive to fault reactivation at shallow depths, as observed in similar tectonic settings elsewhere in the world.

The detection of volcanic unrest is a critical component of volcanic monitoring and risk mitigation, especially for volcanoes with persistent hydrothermal activity and no recent eruptions. Identifying early signs of reactivation in such systems is particularly challenging due to the complex interplay between magmatic and hydrothermal processes.Vulcano, one of the seven volcanic islands in the Aeolian archipelago (Southern Italy), is characterized by fumarolic activity and well-documented historical eruptions. The last eruptive event, occurring in 1888–1890 AD, featured episodic explosive activity of varying intensity, with the most violent explosions ejecting bombs and blocks over 1 km from the crater. Due to its small size and the proximity of active volcanic features to densely populated and tourist areas, Vulcano represents a critical site for volcanic risk management. In mid-September 2021, the island experienced significant degassing episodes at La Fossa cone, marking a period of unrest without eruptive activity. This unique scenario makes Vulcano an ideal natural laboratory for studying volcanic unrest in the absence of eruptions, providing valuable insights into the underlying magmatic-hydrothermal system.Using continuous seismic records from Vulcano, we analyze relative seismic velocity changes (dv/v) through the cross-correlation of ambient noise, employing the MSNoise package \citep{lecocq2014msnoise}. Our analysis covers the pre-unrest, unrest, and post-unrest periods from 2016 to 2024, offering a long-term perspective on the temporal evolution of the system. Preliminary results show significant changes in dv/v that appear to be related to the 2021 episode of unrest, which corresponds to increased seismic activity, variations in gas emissions, and ground deformation. Long-term monitoring of Vulcano is crucial for identifying early signs of reactivation, which can significantly improve eruption forecasting and risk mitigation strategies. These findings highlight the potential of seismic noise analysis for real-time monitoring and to advance our understanding of the dynamics of volcanic unrest.ReferencesLecocq, T., Caudron, C., & Brenguier, F. (2014). Msnoise, a python package for monitoring seismic velocity changes using ambient seismic noise. Seismological Research Letters, 85 (3), 715–726.

Globally, the encroachment of human activities on protected areas is accelerating, posing new challenges for biodiversity conservation. As the United Nations’ 2030 goal of protecting 30% of the planet's landmass for nature draws closer, understanding the lesser-known dimensions of human disturbances becomes critical. Anthropogenic seismic noise, such as that produced by mining, oil drilling, and heavy infrastructure development, represents a largely unexplored but potentially substantial threat to sensitive ecosystems. Recent studies have revealed that large mammals, including elephants, are sensitive to seismic waves, detecting seismic signals and potentially using them for long-distance communication.This research explores the interplay between seismology and conservation biology by investigating the impact of seismic noise from extractive operations on wildlife spatial behavior and habitat use in Murchison Falls National Park, Uganda. Using seismometers, camera traps, and machine learning models, this study uncovers correlations between seismic activity patterns and shifts in large mammal movements. The findings highlight how seismic disturbances propagate into wildlife behavior, contributing to an emerging understanding of how human activities affect ecosystems beyond visible or audible dimensions. By bridging the fields of geophysics and biodiversity conservation, this research underscores the need for holistic environmental impact assessments in protected areas and provides a foundation for mitigating seismic noise effects on biodiversity.

The water cycle impacts geophysical signals, influencing our ability to monitor subsurface hydrology. At the Membach geophysical station in Belgium, we integrate gravity and ambient seismic noise data to study hydrological variations and develop a numerical hydrological model at a local scale. Our findings reveal that gravity observations at Membach station exhibit gradual changes, reaching a peak at ± 2-day after rainfall, reflecting subsurface water redistribution and storage processes. Concurrently, increased soil saturation corresponds with a decrease in HVSR (Horizontal-to-Vertical Spectral Ratio), indicating reduced stiffness and changes in seismic wave propagation. Furthermore, relative velocity changes (dv/v) show frequency-dependent time delays, with deeper layers exhibiting slower responses compared to shallower regions. These results highlight the dynamic relationship between rainfall, soil saturation, and geophysical responses, providing new insights into critical zone processes. By combining gravimetry and ambient seismic noise, we address challenges in studying deep and complex subsurface zones, where traditional hydrological methods often fall short. This approach not only enhances our understanding of subsurface hydrology but also improves water resource management and critical zone studies. The integration of geophysical methods offers a comprehensive framework for monitoring hydrological dynamics, advancing our ability to interpret geophysical signals influenced by the water cycle and providing a valuable tool for managing environmental and climatic impacts on subsurface water storage.

Co‐eruptive volcanic tremor during the 2021 Fagradalsfjall eruption in Iceland (19 March–18 September 2021) is characterized using seismic and visual data recorded close to the eruption site and across the Reykjanes Peninsula. An automatic seismic network‐based approach reveals several tremor patterns associated with seven phases of the eruption, including (a) continuous tremor located beneath the eruption site and attributed to pressure changes in the shallow vent system(s) in phases I, III, and VII, and (b) two patterns of minute‐ and hour‐long intermittent tremor in May (phase II) and July–August (phases IV–VI), respectively. The first intermittent pattern of minute‐long tremor bursts associated with pulsating lava fountains in May is attributed to magma degassing in a shallow reservoir (top 100 m) connected to a top‐conduit. The progressive enlargement of both the top‐conduit and shallow reservoir with time is estimated quantitatively using a collapsing foam model. Sudden changes of their geometries, as detected from tremor characteristics, are systematically associated with observed crater collapse events. The second intermittent pattern of cyclic hour‐long tremor episodes associated with episodic effusive activity in July–August is attributed to magma flowing and cooling in the feeder dike connected to a sill at 5 km depth. The sill is fed by a constant influx of magma from the deeper plumbing system and stores magma during low discharge periods. The observed cyclicity of both the eruptive activity and the tremor is interpreted quantitatively with a sill‐dike model accounting for magma cooling and induced cyclic viscosity changes in the dike.