Publication date: 1 September 2025
Source: Advances in Space Research, Volume 76, Issue 5
Author(s): Shayan Shirafkan, Mohammad Ali Sharifi, Santiago Belda, Seyed Mohsen Khazraei, Alireza Amiri-Simkooei, Sadegh Modiri
Publication date: 1 September 2025
Source: Advances in Space Research, Volume 76, Issue 5
Author(s): Simon J. Köhn, Ana C.M. Fernandes, Casper S. Fibæk, Karina Nielsen
Publication date: 1 September 2025
Source: Advances in Space Research, Volume 76, Issue 5
Author(s): Christopher J. Banks, Francisco Mir Calafat, Alessandro Di Bella
The rise in global mean sea level (GMSL) is a critical indicator of climate change. Hong Kong Polytechnic University (PolyU) researchers have utilized advanced space geodetic technologies to deliver the first precise 30-year (1993–2022) record of global ocean mass change (also known as barystatic sea level), revealing its dominant role in driving GMSL rise.
Natural hydrogen from deep underground could be an important building block for the sustainable energy system of the future, but it is currently still difficult to predict where and at what depth elevated concentrations are located. New study results from the Department of Geology at the University of Vienna could make such predictions easier in the future. So-called "fairy circles"—round patches with vegetation damage—could be helpful indicators. This is because these "fairy circles" subside due to the seepage of natural hydrogen.
One of the worst earthquakes in European history ripped through Portugal in 1755, causing a tsunami, fires and shaking that killed tens of thousands of people and caused widespread destruction. Another less well-documented earthquake occurred in the same region in 1356, and a more recent 7.9 magnitude earthquake occurred in 1969. The most recent event was recorded by seismic instruments and has been found to have originated from the flat Horseshoe Abyssal Plain, which is not near any known major tectonic faults.
In recent years, Pacific island nations have earned global credibility as champions of climate action. Pacific leaders view sea level rise as an existential threat.
A team of researchers from Monash University has made a discovery that could reshape our understanding of greenhouse gas emissions from coastal ecosystems. Published in Nature Geoscience, the study reveals sandy coastlines, which make up half the world's continental margins, are a previously overlooked source of methane.
Global climate change is making temperatures hotter, particularly in densely populated cities, which can adversely affect the health of residents. While mitigation efforts are urgent, it is hard for urban planners to identify exactly where to target as accurate, long-term climate records created over fine spatial scales have been unavailable.
The Operational Land Imager on Landsat 9 captured this image of Buccaneer Archipelago on June 11, 2025.
SummaryDistributed Acoustic Sensing (DAS) is a recent technology that turns optical fibers into multi-sensor arrays. In the marine environment, it offers new possibilities for measuring seismic and environmental signals. While DAS can be applied to existing fiber optic cables used for communications, a major limitation of such efforts is that the position of the cable is not always known with sufficient accuracy. In particular, for submarine telecommunication cables, the positioning accuracy decreases with increasing depth. This problem affects the accuracy of earthquake locations and source parameters based on DAS signals. This limitation calls for methods to retrieve the cable’s position and orientation. Here, we propose a method for relocating a linear section of cable “or multiple connected segments” using incidental acoustic sources, particularly boats moving in the vicinity of the cable. The method is based on Target Motion Analysis (TMA) for sources in uniform rectilinear motion. We consider Bearing-Only TMA (BO-TMA) and the Bearing and Frequency TMA (BF-TMA), which respectively use changes in back azimuth (called bearing in navigation) and changes in both back azimuth and Doppler frequency shift as the source moves. We adapt these methods to the 3D case to account for the difference in depth between the fiber and the sources. Both cases lead to a non-linear inverse problem, which we solve by the Levenberg-Marquardt method. On synthetic data, we test both TMA techniques on single and multiple source trajectories and evaluate their accuracy as a function of source trajectory and velocity. We then test the BO-TMA on real DAS recordings of acoustic signals produced by passing ships near a 42 km-long fiber optic cable off the coast of Toulon, southeastern France. In this study case, the position and characteristics of the acoustic source are known. While the Doppler frequency shift at low frequency (30 Hz) is difficult to measure with sufficient accuracy (<0.1○), we demonstrate that effective cable location can be achieved by BO-TMA using multiple ship passages with a variety of trajectories. Once the linear sections of the cable have been relocated, the stage is set to reconstruct the entire cable configuration. More generally, the three-dimensional TMA on linear antennas developed here can be used to locate either the sources or the antenna situated at different depths.
The climate benefits of planting trees may have been greatly overestimated, but swift action could ensure reforestation meets its potential to curb dangerous emissions, new research has found.
Glaciers across High Mountain Asia are losing more than 22 gigatons of ice per year—the equivalent to nearly 9 million Olympic swimming pools, according to research from the University of Utah and Virginia Tech. The impact of a warming climate on glacial loss is undisputed—this new study provides the first evidence that seasonal shifts in rainfall and snowfall patterns, particularly of the South Asian monsoons, are also exacerbating glacier melting across the region.
Picture this: You're stuck in traffic on a summer afternoon, checking the weather app on your phone as dark storm clouds roll in. You might think about power outages or possible flooding, but you probably don't think about how every lightning bolt that flashes across the sky also emits a gas, nitrogen oxide (NO), that is also emitted in the exhaust from your car's engine.
SummaryWe present a full-wave inversion algorithm (FWI) to accurately delineate the subsalt body using seismic borehole data. This ill-posed inverse problem is constrained by introducing geological a priori information through the parameterization of the salt boundary using a level set function. The implicit level set function is spanned by a set of B-spline basis functions for their ability to represent a wide range of shapes. Furthermore, the proposed FWI algorithm combines a meshed discretization with the implicit representation of shapes throughout the inversion process. A weak deformation of the mesh is applied at each iteration of the inversion to maintain the explicit discretization of the shapes when the level set boundary is updated. This method is very accurate when it comes to modelling the scattered wavefields and computing the Fréchet derivatives at interfaces. Three numerical examples using synthetic borehole seismic data illustrate the ability of the method to accurately retrieve the size, location and shape of the salt body when the density and seismic velocities are known.
SummaryFractures in reservoirs are potential conduits for fluid flow. Therefore, it is crucial to know to what extent fluid flowing through a fracture could be lost by seepage to its porous background. For this reason, the hydraulic contact between the porous background and the fracture should be characterized, ideally based on seismic reflections. The representation of a fracture as a thin porous layer can provide insight into this seepage from a dynamic poroelasticity perspective. This is possible because the seismic waves reflected from a fracture are partially converted into the slow P-wave, which is the fluid motion relative to the solid-frame, and are sensitive to hydraulic contact being sealed or leak. It is well known that the P-wave reflectivity of fractures exhibits a marked difference between sealed and leaky cases for small angles of incidence (below twenty degrees) because of the variation in conversion scattering to slow P-wave. Drawing from a recent finding that a vertically polarized shear wave (SV-wave) can also generate a robust slow P-wave, we analyze the SV-wave reflectivity at fractures that can be hydraulically connected or disconnected from the surrounding porous medium, with the aim of advancing fracture characterization. We find that the reflectivity of the SV-wave is sensitive to fluid seepage, particularly at larger incident angles (above thirty degrees) where the amplitude is diminished substantially. Therefore, SV-wave reflectivity can also be used to identify leaky fractures, complementing the information provided by P-wave reflectivity.
SummaryEarthquake early warning systems are designed to provide critical seconds of warning before strong ground shaking, facilitating emergency mitigation efforts. Existing methods, such as neural networks and ground motion prediction equation-based approaches, rely on manually defined parameters and physics-based computations, which introduce human bias and hinder the efficiency of real-time applications. Furthermore, current studies primarily focus on scalar metrics such as peak ground acceleration and peak ground velocity to evaluate earthquake impacts. These metrics are limited to measuring ground shaking intensity and fail to capture the spectral characteristics of ground motion. Therefore, a ground-motion and structural-oriented deep learning-based model is proposed to predict uniform hazard spectral acceleration values across 111 periods ranging from 0.01 to 20 seconds. The framework is initially trained and evaluated on 17,500 ground-motion records from the crustal Next Generation Attenuation West 2 project. Spectral acceleration values are predicted by two subsets: deep learning-based uniform hazard spectral acceleration models 1 and 2. These models effectively utilize feature information from the initial seconds of seismic waveforms, eliminating the need for empirically defined parameters. Two deep learning-based models are developed for two datasets representing two distinct broad geographical regions. Both models utilize a similar deep-learning architecture but vary in input settings and hyperparameters to account for regional seismic characteristics. To assess the model's goodness-of-fit between observed and predicted values, as well as its generalization ability, we rigorously compare the two models with the latest data from the U.S. Geological Survey Earthquake Hazard Toolbox and the Japanese Strong-Motion Earthquake Network, respectively. An explainable artificial intelligence technique has been applied to better understand the framework and analyze how individual input features influence the outputs of the trained models. Integrating cutting-edge deep learning technologies into ground motion and engineering seismology reveals the significant potential of the model in enhancing real-time early warning systems. This integration also provides valuable support to various end-users involved in seismic monitoring, facilitating well-informed decisions in both real-time and near-real-time scenarios.
The Philippines, like other tropical countries, is known more for its balmy climate than for hailstorms. But a new Philippine study—the first of its kind—has found that the country's hottest days are, in fact, more likely to produce hail. The paper is published in the Asia-Pacific Journal of Atmospheric Sciences.
Carbon dioxide levels in the atmosphere vary naturally between ice ages and interglacial periods. A new study by researchers at the University of Gothenburg shows that an unexpectedly large proportion of carbon dioxide emissions after the ice age may have come from thawing permafrost.
Some 14,000 years ago, algal blooms in the Southern Ocean helped to massively reduce the global carbon dioxide content of the atmosphere—as has now been revealed by new analyses of ancient DNA published by a team from the Alfred Wegener Institute (AWI) in the journal Nature Geoscience. In the ocean around the Antarctic continent, these algal blooms had a significant impact on global carbon dynamics. The current and expected future decline in sea ice in this region now poses a serious threat to these algae, which could incur global consequences.
