Hasil untuk "Geophysics. Cosmic physics"

Marric Stephens

Chunrui Li, Haibing Li, Marie‐Luce Chevalier et al.

Abstract The extent to which surface processes drive continental deformation remains a pivotal question in geodynamics. Here, we demonstrate that Late Quaternary lake‐water unloading is a primary driver of fault slip and rift asymmetry in southern Tibet. Since the last interglacial (∼116 ka), significant water‐level drops of large lakes have induced crustal rebound and Coulomb stress changes. At Nam Co Lake, a ∼130 m drop produced ∼0.1 MPa of stress change, preferentially reactivating the adjacent fault and contributing ∼15 m of vertical displacement ∼23% of the total near Damxung. Likewise, the southern lakes (Yamzho Yumco and Puma Yumco) caused ∼70 m of vertical displacement on the adjacent fault. We establish that climatically‐controlled lake unloading can directly shape continental rifting by selectively enhancing fault slip on the lake‐bounding side of the rift, thereby amplifying its structural asymmetry. This highlights a significant, quantifiable role of surface processes in actively shaping tectonic deformation.

Fabin Dong, Qiang Yin, Wen Hong

Multiaspect polarimetric synthetic aperture radar (SAR) captures the polarimetric properties of targets from various observational aspects. The comprehensive multiaspect scattering characteristics are valuable for man-made structure detection and classification. Typically, the anisotropic scattering of targets could be characterized by the differences in the statistical properties of polarimetric data across aspects. However, both the statistical similarities in man-made structures and variabilities in natural targets at different aspects can negatively impact the ability to distinguish between them. Consequently, relying solely on anisotropic analysis may not yield favorable man-made structure detection results. Since man-made structures usually include special shapes, such as dihedral angle, there are significant variations in scattering power across different aspects. Therefore, this article proposes an improved man-made structure detection method that integrates scattering power characteristics and anisotropic features. First, to highlight differences between aspects, this article introduces a similarity matrix to perform azimuth sequence filtering. Subsequently, anisotropic features are extracted through differences in statistical distribution, and scattering power characteristics at individual aspects, along with their variations, are extracted using the fuzzy C-means clustering combined with spatial neighborhood. Two different features are fused to distinguish man-made structures from natural targets. Finally, the most significant azimuth aspect is determined by comparing the scattering contributions of individual subapertures. Experimental verification with airborne circular polarimetric SAR data confirms that the multifeature fusion method, following azimuth sequence filtering, effectively improves the detection of man-made structures and their most anisotropic subapertures.

Tero Mielonen, Alexander Marshak, Yongxiang Hu

Qinglin Shan, Lingyu Mu, Liang Yuan et al.

Abstract Multi-cluster hydraulic fracturing represents a key technology for the exploitation of oil and gas from tight reservoirs. The ambiguous matching relationship between perforation parameters and the pump rate of fracturing fluid remains a challenge that constrains the efficient development of tight reservoirs. Based on the theory of continuous damage, a three-dimensional finite element model for the coupled calculation of seepage, stress, and damage was developed to simulate the propagation of multi-cluster hydraulic fractures. The new model characterizes the spiral distribution of perforations by means of geometric modeling and is capable of examining its influence on the morphology of hydraulic fractures near the wellbore. Furthermore, by introducing fluid pipe elements and fluid pipe connector elements, the model is capable of simultaneously attaining the distribution of hydraulic energy among different perforation clusters and different perforations within the same perforation cluster. Based on this model, under the identical cluster quantity and cluster spacing, the influence of perforation number per cluster, pump rate and in-situ stress difference on the morphology of multi-cluster hydraulic fractures is investigated. The research findings imply that a small number of perforations per cluster, such as 3 or 4, can significantly enhance the flow limited-entry effect of perforation clusters, ensuring adequate long-distance propagating hydraulic fractures under lower pump rates. A large number of perforations per cluster, such as 6 or 8, can give rise to a complex hydraulic fracture morphology near the wellbore, resulting in bifurcated secondary fractures, which can affect the propagation of multi-cluster fractures and even cause the longitudinal extension of hydraulic fractures along the wellbore direction. Under low stress difference, a high pump rate can facilitate the uniform propagation of multi-cluster hydraulic fractures, yet it can also lead to the connection of adjacent hydraulic fractures. High stress difference significantly limited the form of near-wellbore fracture complexity and the reorientation of fractures from middle clusters during propagation. The research outcomes of this study can offer a reference for the on-site fracturing design of tight reservoirs.

Lingyun Lu, Yueren Xu, Jiacheng Tang et al.

Rapidly obtaining spatial distribution maps of secondary disasters triggered by strong earthquakes is crucial for understanding the disaster-causing processes in the earthquake hazard chain and formulating effective emergency response measures and post-disaster reconstruction plans. On April 3, 2024, a MW 7.4 earthquake struck offshore east of Hualien, Taiwan, China, which triggered numerous coseismic landslides in bedrock mountain regions and severe soil liquefaction in coastal areas, resulting in significant economic losses. This study utilized post-earthquake emergency data from China's high-resolution optical satellite imagery and applied visual interpretation method to establish a partial database of secondary disasters triggered by the 2024 Hualien earthquake. A total of 5 348 coseismic landslides were identified, which were primarily distributed along the eastern slopes of the Central Mountain Range watersheds. In high mountain valleys, these landslides mainly manifest as localized bedrock collapses or slope debris flows, causing extensive damage to highways and tourism facilities. Their distribution partially overlaps with the landslide concentration zones triggered by the 1999 Chi-Chi earthquake. Additionally, 6 040 soil liquefaction events were interpreted, predominantly in the Hualien Port area and the lowland valleys of the Hualien River and concentrated within the IX-intensity zone. Widespread surface subsidence and sand ejections characterized soil liquefaction. Verified against local field investigation data in Taiwan, rapid imaging through post-earthquake remote sensing data can effectively assess the distribution of coseismic landslides and soil liquefaction within high-intensity zones. This study provides efficient and reliable data for earthquake disaster response. Moreover, the results are critical for seismic disaster mitigation in high mountain valleys and coastal lowlands.

S. Ting, H. Georgi, J. Iliopoulos et al.

Discovery of the J Particle at Brookhaven National Laboratory and the Physics of Electrons and Positrons; The Standard Model Yesterday, Today and Tomorrow; The Rise of Gauge Theories: From Many Models to One Theory; From Charm to CP Violation; When the Standard Model Was Ignored; The Discovery of the W and Z Bosons at the CERN Proton-Antiproton Collider; A Personal History of CERN Particle Colliders (1972-2022); The Age of Gravitational Wave Astronomy; Precision Physics in the Era of (HL)LHC; Recent Developments in Flavor Physics, the Unitary Triangle Fit, Anomalies and All That; About BSM Physics, with Emphasis on Flavour; The Discovery of the Antiproton between Rome and Berkeley; Raoul Gatto and Bruno Touschek: the Rise of $e+e^-$ Physics; From ADONE's Multi-Hadron Production to the J/$Ψ$ Discovery; From Bjorken Scaling to Scaling Violations

Zhang Ying, Wen Congcong, Sornette Didier et al.

Earthquake forecasting remains a significant scientific challenge, with current methods falling short of achieving the performance necessary for meaningful societal benefits. Traditional models, primarily based on past seismicity and geomechanical data, struggle to capture the complexity of seismic patterns and often overlook valuable non-seismic precursors such as geophysical, geochemical, and atmospheric anomalies. The integration of such diverse data sources into forecasting models, combined with advancements in AI technologies, offers a promising path forward. AI methods, particularly deep learning, excel at processing complex, large-scale datasets, identifying subtle patterns, and handling multidimensional relationships, making them well-suited for overcoming the limitations of conventional approaches. This review highlights the importance of combining AI with geophysical knowledge to create robust, physics-informed forecasting models. It explores current AI methods, input data types, loss functions, and practical considerations for model development, offering guidance to both geophysicists and AI researchers. While many AI-based studies oversimplify earthquake prediction, neglecting critical features such as data imbalance and spatio-temporal clustering, the integration of specialized geophysical insights into AI models can address these shortcomings. We emphasize the importance of interdisciplinary collaboration, urging geophysicists to experiment with AI architectures thoughtfully and encouraging AI experts to deepen their understanding of seismology. By bridging these disciplines, we can develop more accurate, reliable, and societally impactful earthquake forecasting tools.

Wenfang Xu, Xiaosheng Xia, Shilong Piao et al.

Abstract It is well known that global warming increases the atmospheric water vapor content, which results in substantial changes in the hydrological cycle. Using five observational data sets, the results show that an increasing trend of near‐surface water vapor pressure (AVP) over land and ocean was significant from 1975 to 1998, while such an increasing trend in AVP subsequently weakened from 1999 to 2019. This phenomenon is associated with decreased oceanic evaporation and land surface evapotranspiration in response to recent climate variations. One consequence of such a phenomenon is a large increase in near‐surface vapor pressure deficit (VPD), which in turn increases atmospheric demand for water vapor and thus aridity and drought over land. This result emphasizes the importance of water vapor change under global warming.

Wei Chen, Jiesi Luo, Jim Ray et al.

While the geodetic excitation χ(t) of polar motion p(t) is essential to improve our understanding of global mass redistributions and relative motions with respect to the terrestrial frame, the widely adopted method to derive χ(t) from p(t) has biases in both amplitude and phase responses. This study has developed a new simple but more accurate method based on the combination of the frequency- and time-domain Liouville's equation (FTLE). The FTLE method has been validated not only with 6-h sampled synthetic excitation series but also with daily and 6-h sampled polar motion measurements as well as χ(t) produced by the interactive webpage tool of the International Earth Rotation and Reference Systems Service (IERS). Numerical comparisons demonstrate that χ(t) derived from the FTLE method has superior performances in both the time and frequency domains with respect to that obtained from the widely adopted method or the IERS webpage tool, provided that the input p(t) series has a length around or more than 25 years, which presents no practical limitations since the necessary polar motion data are readily available. The FTLE code is provided in the form of MatLab function.

M. Pettine, S. Imbeah, J. Rathbun et al.

Abstract Juno has allowed clear, high‐resolution imaging of Io's polar volcanoes using the Jovian Infrared Auroral Mapper (JIRAM) instrument. We have used data from JIRAM's M‐band (4.78 μm) imager from 11 Juno orbits to construct a global map of volcanic flux. This map provides short‐term insight into the spatial distribution of volcanoes and the ways in which high‐ and low‐latitude volcanoes differ. Using spherical harmonic analysis, we quantitatively compare our volcanic flux map to the surface heat flow distribution expected from models of Io's tidal heat deposition (summarized in de Kleer, Park, et al. (2019, https://doi.org/10.26206/d4wc‐6v82). Our observations confirm previously detected systems of bright volcanoes at high latitudes. Our study finds that both poles are comparably active and that the observed flux distribution is inconsistent with an asthenospheric heating model, although the south pole is viewed too infrequently to establish reliable trends.

Andrea Giammanco, Marwa Al Moussawi, Matthieu Boone et al.

In cultural heritage conservation, it is increasingly common to rely on non-destructive imaging methods based on the absorption or scattering of photons ($X$ or $γ$ rays) or neutrons. However, physical and practical issues limit these techniques: their penetration depth may be insufficient for large and dense objects, they require transporting the objects of interest to dedicated laboratories, artificial radiation is hazardous and may induce activation in the material under study. Muons are elementary particles abundantly and freely produced in cosmic-ray interactions in the atmosphere. Their absorption and scattering in matter are characteristically dependent on the density and elemental composition of the material that they traverse, which offers the possibility of exploiting them for sub-surface remote imaging. This novel technique, nicknamed "muography", has been applied in use cases ranging from geophysics to archaeology to nuclear safety, but it has been so far under-explored for a vast category of cultural heritage objects that are relatively large (from decimeters to human size) and dense (stone, metals). The development of portable muon detectors makes muography particularly competitive in cases where the items to be analysed are not transportable, or set up in a confined environment. This document reviews the relevant literature, presents some exemplary use cases, and critically assesses the strengths and weaknesses of muography in this context.

François Rincon

Fangwen Yang, Pengfei He, Haiyong Ding et al.

Net primary productivity (NPP), as an indicator of ecological functioning, plays an important role in regional and global carbon cycles. Although many studies have estimated the NPP of vegetation on the Qinghai Plateau (QP), the existing NPP datasets over the QP are either of low spatial resolution or limited-duration time-series. These shortcomings restrict our ability to explore the spatial distribution and long-term trends of NPP at a finer scale. To address this gap, we present a new monthly NPP dataset (QP_NPP30) at a high spatial resolution (30 m) over the QP for the period 1987&#x2013;2021. We constructed this dataset using the Carnegie-Ames-Stanford-Approach (CASA) model and multisource data, including reconstructed normalized difference vegetation index (NDVI) data, reanalysis data, land cover, and other ancillary data. To reconstruct the NDVI, a harmonic regression model based on the Google Earth Engine (GEE) was applied to the NDVI time series data. Statistical analysis of QP_NPP30 showed that the NPP in the QP has increased over the past 35 years (0.92 <inline-formula><tex-math notation="LaTeX">$g C/m^{2}/yr$</tex-math></inline-formula>). Furthermore, we found that NPP is concentrated in June, July, and August, accounting for approximately 73&#x0025; of the annual total. To validate our dataset, we compared it with measured NPP and with the MODIS NPP product (MOD-NPP). Our results demonstrated that QP_NPP30 has similar spatial patterns to MOD-NPP, but offers richer spatial detail. Specifically, QP_NPP30 has a higher accuracy than MOD-NPP, by comparing with the measured data (r &#x003D; 0.695, RMSE &#x003D; 132.823 <inline-formula><tex-math notation="LaTeX">$g C/m^{2}/yr$</tex-math></inline-formula> for QP_NPP30; r &#x003D; 0.328, RMSE &#x003D; 158.586 <inline-formula><tex-math notation="LaTeX">$g C/m^{2}/yr$</tex-math></inline-formula> for MOD-NPP).

A. Haddad, C. Chiarabba, M. Lazar et al.

Abstract The Dead Sea Fault (DSF) is a crustal‐scale continental transform fault separating the African and the Arabian plates. Neogene to Quaternary volcanic activity is well‐spread in Northern Israel. Yet, the origin of the magmas that fed the eruptions is still unpinned. Our local earthquake tomography depicts velocity distributions typical of rifting settings. At 9 km depth, a prominent high Vp/Vs anomaly marks the presence of cooling melts. We propose that protracted transtension along the DSF caused crustal thinning promoting the emplacement of magmatic bodies. Crustal emplacements of magmas in Northern Israel reconcile multiple observations, including the high geothermal gradient, the prominent magnetic anomalies and the traces of mantle‐derived fluids in the springs across the Sea of Galilee. We provide a compelling evidence for rifting in segments of the DSF and identify the potential source of magmatism that fed part of the volcanic activity of the area.

Sergio J. Sciutto, Luis A. Anchordoqui, Carlos Garcia Canal et al.

We investigate the observed muon deficit in air shower simulations when compared to ultrahigh-energy cosmic ray (UHECR) data. Gleaned from the observed enhancement of strangeness production in ALICE data, the associated $π\leftrightarrow K$ swap is taken as a cornerstone to resolve the muon puzzle via its corresponding impact on the shower evolution. We develop a phenomenological model in terms of the $π\leftrightarrow K$ swapping probability $F_s$. We provide a parametrization of $F_s (E^{\rm (proj)}, η)$ that can accommodate the UHECR data, where $E^{\rm (proj)}$ is the projectile energy and $η$ the pseudorapidity. We also explore a future game plan for model improvement using the colossal amount of data to be collected by LHC neutrino detectors at the Forward Physics Facility (FPF). We calculate the corresponding sensitivity to $F_s$ and show that the FPF experiments will be able to probe the model phase space.

Pranab J. Deka, Ralf Kissmann, Lukas Einkemmer

Anisotropic diffusion is imperative in understanding cosmic ray diffusion across the Galaxy, the heliosphere, and the interplay of cosmic rays with the Galactic magnetic field. This diffusion term contributes to the highly stiff nature of the cosmic ray transport equation. To conduct numerical simulations of time-dependent cosmic ray transport, implicit integrators (namely, Crank-Nicolson (CN)) have been traditionally favoured over the CFL-bound explicit integrators in order to be able to take large step sizes. We propose exponential methods to treat the linear anisotropc diffusion equation in the presence of advection and time-independent and time-dependent sources. These methods allow us to take even larger step sizes that can substantially speed-up the simulations whilst generating highly accurate solutions. In or subsequent work, we will use these exponential solvers in the Picard code to study anisotropic cosmic ray diffusion and we will consider additional physical processes such as continuous momentum losses and reacceleration.

Davide Faranda, Gabriele Messori, Tommaso Alberti et al.

Statistical physics and dynamical systems theory are key tools to study high-impact geophysical events such as temperature extremes, cyclones, thunderstorms, geomagnetic storms and many more. Despite the intrinsic differences between these events, they all originate as temporary deviations from the typical trajectories of a geophysical system, resulting in well-organised, coherent structures at characteristic spatial and temporal scales. While statistical extreme value analysis techniques are capable to provide return times and probabilities of occurrence of certain geophysical events, they are not apt to account for their underlying physics. Their focus is to compute the probability of occurrence of events that are large or small with respect to some specific observable (e.g. temperature, precipitation, solar wind), rather than to relate rare or extreme phenomena to the underlying anomalous geophysical regimes. This paper outlines this knowledge gap, presenting some related challenges, new formalisms and briefly commenting on how stochastic approaches tailored to the study of extreme geophysical events can help to advance their understanding.

Anonymous

M. Kellinsalmi, M. Kellinsalmi, A. Viljanen et al.

<p>Solar eruptions and other types of space weather effects can pose a hazard to the high voltage power grids via geomagnetically induced currents (GICs). In worst cases, they can even cause large-scale power outages. GICs are a complex phenomenon, closely related to the time derivative of the geomagnetic field. However, the behavior of the time derivative is chaotic and has proven to be tricky to predict. In our study, we look at the dynamics of the geomagnetic field during active space weather. We try to characterize the magnetic field behavior, to better understand the drivers behind strong GIC events. We use geomagnetic data from the IMAGE (International Monitor for Auroral Geomagnetic Effect) magnetometer network between 1996 and 2018. The measured geomagnetic field is primarily produced by currents in the ionosphere and magnetosphere, and secondarily by currents in the conducting ground. We use the separated magnetic field in our analysis. The separation of the field means that the measured magnetic field is computationally divided into external and internal parts corresponding to the ionospheric and telluric origin, respectively. We study the yearly directional distributions of the baseline subtracted, separated horizontal geomagnetic field, <span class="inline-formula">Δ<strong><em>H</em></strong></span>, and its time derivative, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">Δ</mi><mi mathvariant="bold-italic">H</mi><mo>/</mo><mi mathvariant="normal">d</mi><mi>t</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="0cb995efbf642b0e6b7fb6d764f44f72"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="angeo-40-545-2022-ie00001.svg" width="41pt" height="14pt" src="angeo-40-545-2022-ie00001.png"/></svg:svg></span></span>. The yearly distributions do not have a clear solar cycle dependency. The internal field distributions are more scattered than the external field. There are also clear, station-specific differences in the distributions related to sharp conductivity contrasts between continental and ocean regions or to inland conductivity anomalies. One of our main findings is that the direction of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">Δ</mi><mi mathvariant="bold-italic">H</mi><mo>/</mo><mi mathvariant="normal">d</mi><mi>t</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="0f243ef2bfdb532cd1f6a3da416df089"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="angeo-40-545-2022-ie00002.svg" width="41pt" height="14pt" src="angeo-40-545-2022-ie00002.png"/></svg:svg></span></span> has a very short “reset time“, around 2 min, but <span class="inline-formula">Δ<strong><em>H</em></strong></span> does not have this kind of behavior. These results hold true even with less active space weather conditions. We conclude that this result gives insight into the time scale of ionospheric current systems, which are the primary driver behind the time derivative's behavior. It also emphasizes a very short persistence of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">Δ</mi><mi mathvariant="bold-italic">H</mi><mo>/</mo><mi mathvariant="normal">d</mi><mi>t</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="a8daa986013cdafc8a26d66c9167a967"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="angeo-40-545-2022-ie00003.svg" width="41pt" height="14pt" src="angeo-40-545-2022-ie00003.png"/></svg:svg></span></span> compared to <span class="inline-formula">Δ<strong><em>H</em></strong></span>, and highlights the challenges in forecasting <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">Δ</mi><mi mathvariant="bold-italic">H</mi><mo>/</mo><mi mathvariant="normal">d</mi><mi>t</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="83cb461cf598c875c92001a7bac04b61"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="angeo-40-545-2022-ie00004.svg" width="41pt" height="14pt" src="angeo-40-545-2022-ie00004.png"/></svg:svg></span></span> (and GIC).</p>