Earth and Space Science最新文献

Regularly spaced magnetic anomaly surveys, consisting of parallel traverse lines and perpendicular (more widely spaced) tie lines, are routinely collected for multiple applications including geologic studies and, more recently, as reference for alternative magnetic navigation. A key factor in the planning of these surveys is the determination of the traverse and tie line spacing to provide acceptable sampling of the magnetic anomalies of interest. This paper revisits the “go to” reference for such survey design, a paper published by Reid in 1980. Data collection and processing has changed significantly since 1980, so it is timely to revisit these issues. The Reid (1980) analysis remains relevant for the resolution of short wavelength anomalies, but additional factors should now be considered for modern survey design and evaluation. As an example, surveys used to support alternative navigation may have different resolution requirements than surveys for shallow geologic investigation.

Passive seismic ambient noise interferometry (ANI) has shown potential for lunar seismic exploration, offering the capability to detect near-surface subsurface structures critical for future lunar mission, such as near-surface ice deposits and lava tubes, without the need for active seismic sources. Performing ANI on the Moon can be realized with a multi-agent system, in which a network of individual rovers either carry or deploy seismic receivers. However, these systems have inherent uncertainties in localization and timing. Additionally, methods used to extract dispersion curves from cross-correlations are fundamentally limited in achievable time–frequency resolution, which we demonstrate for the continuous wavelet transform (CWT). Quantifying how these factors propagate into Rayleigh wave velocity estimates is essential for accurate detection of lunar subsurface features. In this study, analytical error formulas are derived and validated through Monte Carlo simulations using passive seismic data from the Apollo 17 lunar seismic profiling experiment. Results indicate that velocity uncertainties due to localization errors remain around an acceptable $��2.2��\%�$ for realistic positional standard deviations of $��0.9��m�$ at the receiver distance of $��56.9��m�$ as in the Apollo 17 Lunar Seismic Profiling Experiment. Timing errors induced by clock instabilities are negligible. However, uncertainties in seismic travel-time estimations are significantly dominated by the resolution limits imposed by the CWT. The developed analytical uncertainty model thus provides a critical foundation for designing autonomous lunar seismic networks for future lunar missions.

Distributed Acoustic Sensing (DAS) is particularly useful for linear and spatially extensive infrastructure systems such as railway networks. To enable the effective use of DAS in earthquake early warning and disaster response applications, it is essential to understand its performance under strong-motion conditions. However, its behavior during strong shaking is still not well understood. This study investigates the performance of DAS under strong-motion conditions using large-scale vibration table experiments and numerical modeling. In these experiments, a fiber-optic cable was affixed to a shaking table and subjected to sinusoidal excitation. Remarkably, the DAS recorded measurable strain rate signals, even though the fiber moved nearly as a rigid body. At input accelerations below 400 cm/s², a linear relationship was observed between the strain rate and the co-located MEMS accelerometer data. However, this relationship deteriorated above 400 cm/s² despite the absence of cycle skipping, suggesting nonlinearity in the cable response. A simple numerical model was developed to clarify how strain is recorded during the shaking-table experiments, which assumes partial bonding between the fiber core and the outer jacket. The model represents this internal structure using Voigt elements—parallel combinations of springs and dashpots—between the core and the jacket. Simulations demonstrated that internal viscoelastic relaxation can produce measurable strain rate signals with phase coherence across adjacent DAS channels without wave propagation. These results successfully reproduced key experimental features, suggesting that internal cable mechanics, alongside wave propagation and external coupling, play a significant role in the overall strain measurement mechanism of DAS.

Hailstorms over the Yunnan-Guizhou Plateau cause significant losses in key cash crops such as tobacco, inflicting substantial economic impacts. Weining, an eastern plateau region prone to spring-summer hailstorms, requires further research on hailstorm environmental conditions to improve forecasting and disaster mitigation. This study investigates these aspects using multi-source data, objective classification, vorticity diagnostics, and machine learning (ML) to derive robust conclusions. Results show hailstorms predominantly occur in afternoon–evening producing hailstones mostly with diameters <20 mm, under five distinct low-level synoptic circulation patterns, but all sharing a common feature: a trough from the southeastern Tibetan Plateau and cyclonic vorticity associated with the Southwest Vortex near the Sichuan Basin. Spring hailstorms have stronger dynamical forcing (the plateau trough coupled with intense westerly/southwesterly inducing strong convergence), while summer hailstorms have weaker forcing but enhanced moisture transport, with 42.3% linked to tropical cyclones. XGBoost analysis of 17 environmental parameters reveals consistent enhancements in instability and hail growth environments across seasons. Key parameters, listed in order of importance, are most unstable convective available potential energy (MUCAPE), hail growth zone (HGZ), mixed layer height (MLH) and PW in spring; MLH, HGZ, MUCAPE and freezing level height (FLH) in summer, indicating seasonal thermodynamic differences. Additionally, ERA5-derived thermodynamic parameters (e.g., equilibrium level, FLH, and MUCAPE) have significant biases compared to radiosonde data, impairing ML-based importance assessment. This study overcomes limitations of single-data-source and traditional methods, providing valuable scientific insights for improving hailstorm forecasting in complex terrain. Large samples and ML ensure reliable identification of seasonal differences and objective parameter importance quantification, laying a foundation for enhancing hailstorm predictability with significance for disaster mitigation.

Hyper-velocity impacts on planetary surfaces lead to impact craters whose morphology evolves due to exogenous factors such as atmospheric processes, as well as endogenous factors including tectonic and metamorphism. On Earth, erosion processes driven by climate (fluvial, aeolian, glacial processes) progressively erase these structures, or even bury them. Nevertheless, the geophysical signature (gravity and magnetic anomalies) of impact structures often remains preserved, even after hundreds of millions of years. In this study, we model the morphological evolution of terrestrial impact craters to infer their associated gravimetric signatures. We explore different models of impact craters evolution in terms of erosion processes and composition of hosted lithologies using a Landscape Evolution Model. Our models account for erosion and sediment displacement by fluvial and hillslope processes, as well as lithospheric flexure. In addition, we compute the gravimetric anomaly disturbance over time. The case of a 30 km diameter complex impact crater is considered and submitted to erosion processes of varying nature and intensity. Our approach explicitly takes into account the physical processes driving erosion and sediment deposition. We observe that, in some cases, the rim-to-rim diameter almost doubles, while the amplitude of the negative gravimetric disturbance also increases. However, the extent of this central gravity anomaly is smaller than the apparent crater rim, and better reflects the initial crater diameter. These results offer new perspectives for systematically detecting eroded impact structures and more reliably reconstructing their original dimensions, underscoring the need to integrate topographic and geophysical data in future studies.

Hailstorms over the Yunnan-Guizhou Plateau cause significant losses in key cash crops such as tobacco, inflicting substantial economic impacts. Weining, an eastern plateau region prone to spring-summer hailstorms, requires further research on hailstorm environmental conditions to improve forecasting and disaster mitigation. This study investigates these aspects using multi-source data, objective classification, vorticity diagnostics, and machine learning (ML) to derive robust conclusions. Results show hailstorms predominantly occur in afternoon–evening producing hailstones mostly with diameters <20 mm, under five distinct low-level synoptic circulation patterns, but all sharing a common feature: a trough from the southeastern Tibetan Plateau and cyclonic vorticity associated with the Southwest Vortex near the Sichuan Basin. Spring hailstorms have stronger dynamical forcing (the plateau trough coupled with intense westerly/southwesterly inducing strong convergence), while summer hailstorms have weaker forcing but enhanced moisture transport, with 42.3% linked to tropical cyclones. XGBoost analysis of 17 environmental parameters reveals consistent enhancements in instability and hail growth environments across seasons. Key parameters, listed in order of importance, are most unstable convective available potential energy (MUCAPE), hail growth zone (HGZ), mixed layer height (MLH) and PW in spring; MLH, HGZ, MUCAPE and freezing level height (FLH) in summer, indicating seasonal thermodynamic differences. Additionally, ERA5-derived thermodynamic parameters (e.g., equilibrium level, FLH, and MUCAPE) have significant biases compared to radiosonde data, impairing ML-based importance assessment. This study overcomes limitations of single-data-source and traditional methods, providing valuable scientific insights for improving hailstorm forecasting in complex terrain. Large samples and ML ensure reliable identification of seasonal differences and objective parameter importance quantification, laying a foundation for enhancing hailstorm predictability with significance for disaster mitigation.

The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height (SSH) observations from the Ka-band Radar Interferometer (KaRIn), with the potential to improve our understanding of ocean circulation dynamics. A key objective of SWOT is to convert SSH measurements into ocean currents, a process that requires rigorous validation beyond direct SSH assessment. In this study, we evaluated SWOT-derived geostrophic velocities in the California Current System (CCS) at 125.044$��°�$W, 35.917$��°�$N by comparing them with in situ velocity measurements from a moored current meter array during the post-launch Calibration and Validation (CalVal) phase (April 1–4 July 2023). During this period, SWOT operated in a special 1-day repeat orbit, providing daily sampling that is not representative of the nominal 21-day science orbit. To derive reliable velocities, SSH fields were low-pass filtered at 70 km to suppress noise and unbalanced motions. Compared to the in situ velocities, SWOT explained up to 80% (43%) of the meridional (zonal) variance, outperforming DUACS, which explained 63% (15%). SWOT also better captured variability at periods longer than 6–10 days and resolved sharper mesoscale features than the DUACS gridded product, which resolves signals with time scales greater than 25–30 days. When the comparison was repeated using only one SWOT snapshot every 21 days, mimicking the science-phase orbit, SWOT still retained meaningful skill in representing the velocity field. These results demonstrate SWOT's ability to improve mesoscale and large-scale velocity estimation, while also highlighting the challenges in regions with strong internal gravity waves.

Microphysical characteristics of warm-rain precipitation that occurred in Fuzhou region during warm seasons of 2022 and 2023 have been investigated by using polarimetric radar data. Results of a modified warm-rain identification algorithm indicate positive Z_DR variation in the liquid layer should be added as a criterion to prevent events dominated by breakup-coalescence balance being mistakenly classified as warm-rain events, causing the inaccuracy of quantitative precipitation estimation (QPE). Comparative analysis suggests that stratiform, convective and warm-rain precipitation are distinguishable in Cao and Zhang parameter space due to the nature of clustering within concentrated ranges. Convection during certain life stage exhibits similar feature as warm-rain precipitation in Kumjian and Ryzhkov (KR) parameter space, whereas initial Z_DR and vertical variations of Z_H and Z_DR could be useful to separate these two precipitation types. Vertical profiles of polarimetric variables (Z_H, Z_DR, K_DP) in warm-rain precipitation all increase toward the ground, which is associated with lower echo-top and storm-top freezing levels than convective precipitation. Microphsysical processes above the melting layer significantly influence the precipitation growth processes below according to analysis of two typhoon-related cases. Some insights are gained to the development of a warm-rain identification algorithm, such as monotonically increase of Z_H and Z_DR in the liquid layer and suitable range of initial Z_DR, in addition, synoptic environmental conditions, e.g., vertical velocity, lifting condensation level and moisture flux, could serve as auxiliary conditions to accurately identify warm-rain processes, but further research is needed to determine how to utilize them specifically.

A small-volume 6,000 m³ rockslide struck the Lorgino hamlet of Crevoladossola (NW Italy) just before 23:00 UTC on 26 January 2023, at the boundary of a nearby marble quarry. The rockslide severely damaged the mining infrastructure and halted operations for months, fortunately without causing injuries or casualties. An on-site seismic array, previously installed to monitor the quarry activity, recorded neatly the rockslide signal. We analyzed this complex 15-s signal, using a 3D force-time function approach. By combining seismic inversion results with ad-hoc geomechanical analysis and detailed photogrammetric surveys, we gained a comprehensive understanding of the ongoing rockslide mechanisms. Our results link waveform properties to single-force inversion results, providing new insights into the dynamics and energy-transfer mechanisms of the rockslide. The first sliding mass governs low-frequency seismic radiation, while higher-frequency signals (up to 5 Hz) are generated by individual blocks or late block clusters. The integrated approach, applied for the first time on our knowledge at such a small scale revealed the potentiality of these combined tools for rockslide monitoring and hazard mitigation.