| 19 Jun 2026
Seasonal Seismic Velocity Variations in the Western Bohemian Massif Using Ambient-Noise Cross-Correlation
Abstract. Changes in surface and near-surface loads, such as temperature and precipitation, can perturb crustal stress and generate measurable responses, including triggered seismicity, transient strain, and seismic velocity changes. Quantifying these responses provides a means to track the spatiotemporal evolution of stress and its coupling to fault slip and subsurface fluid processes. Traditional approaches, relying on recurring earthquakes or controlled sources, are limited by poor repeatability and high operational cost. Ambient-noise–based imaging avoids these constraints by using fixed receivers and continuous records to enable near-continuous monitoring. Here, we investigate relative seismic velocity variations (δv/v) in the western Bohemian massif using four years of ambient-noise recordings from 20 stations. We estimate δv/v in the 0.1–0.5 Hz band across three coda windows and evaluate potential environmental drivers using cross-correlation. The strongest seasonal δv/v signal is observed for station pairs with interstation distances shorter than 20 km and azimuths of 600-1200, indicating that path geometry and ambient-noise illumination strongly influence the stability of the measurements. Correlation estimates suggest that, δv/v is primarily associated with thermoelastic strain driven by atmospheric temperature variations, while groundwater-level fluctuations may contribute a weaker secondary hydrological signal whose mechanism remains ambiguous.
Review of “Seasonal Seismic Velocity Variations in theWestern Bohemian Massif Using Ambient-Noise Cross-Correlation » by Mandal et al
general comments:
This article reports on observations of relative seismic velocity changes (dv/v) derived from ambient seismic noise in the Western Bohemian Massif, Central Europe. The processing involved data optimization by selecting station pairs with limited aperture (distance) and a preferential NW-SE orientation. The results show that seasonal dv/v variations are primarily controlled by thermoelasticity, with additional contributions from hydraulic loading. The dataset and observations are valuable, the data processing is performed correctly, and the paper is well written. The article deserves publication but requests major corrections, including analyzing the data in a wider frequency band to locate the changes at depth, and performing a 2D surface wave horizontal tomography to identify the regions were changes are more significant.
specific comments:
1) Introduction: Solar radiation (radiative heat transfer) is at least as important as air temperature (convective heat transfer). Therefore, air temperature cannot be the sole source or mechanism driving ground temperature changes.
2) End of the Introduction: References to previous work using ambient seismic noise in the Bohemian Massif should be cited. Examples include (but are not limited to):
3) Section 2: Whitening should be performed before amplitude normalization, not after—especially for highly non-linear processing such as 1-bit normalization or clipping.
4) Lines 105–106: Structural changes and damage are more likely monitored by cross-correlation (CC) than by dv/v. See, for example:
A. Obermann et al., Imaging pre- and co-eruptive structural changes of a volcano with ambient seismic noise, J. Geophys. Res., 118, 6285–6294 (2013).
5) Figure 3: A larger frequency band analysis is needed. Additionally, surface wave inversion would be useful to better locate changes at depth. A horizontal 2D surface wave tomography could then be performed to identify the regions of most significant changes.
6) Line 115: A theoretical model describing the decrease of SNR with longer inter-station distance is proposed in:
E. Larose et al., Fluctuations of correlations and Green’s function reconstruction: role of scattering, J. Appl. Phys., 103, 114907 (2008).
7) Line 172: “Mostly sensitive” does not imply that the observed changes originate from that depth. A full frequency analysis, including higher frequencies, is necessary to confirm the depth sensitivity.
8) Line 175: Clarification is needed: “later in the coda” means (to a lesser extent) deeper probing, but (mostly) broader horizontal 2D probing. Given the dominance of surface waves, regions outside the network may exhibit less dv/v. A 2D surface wave dv/v tomography would be highly beneficial.
9) Line 371: 2D surface sensitivity kernels average over horizontally larger surfaces/volumes, but not necessarily deeper ones. The conclusions remain valid: the larger the volume, the smaller the fluctuations—assuming the fluctuations are local.
technical corrections:
L23-24: literature is missing
Figure 2: color lines brackets are hardly visible
L263: here we assume that the continuous solid material propagates stress, which is not 100% the case for cracked rocks and/or granular materials, and even lesss evident in soils. This assumption/limitation could be clearly stated.
L338: “short period” generally relates to the seismic spectrum (<10s), improper or missleading here