New research reveals the surprising ways atmospheric winds influence ocean eddies, shaping the ocean's weather patterns in more complex ways than previously believed.
Constructed wetlands do a good job in their early years of capturing carbon in the environment that contributes to climate change—but that ability does diminish with time as the wetlands mature, a new study suggests.
The Earth's atmosphere has strengthened its ability to remove air pollutants, including the potent climate-warming gas methane, according to research published in Nature Communications.
The Kenyan rift system is prone to deformation due to various geological processes and human activities, such as overexploitation of groundwater and exploitation of geothermal energy. Crustal deformation monit...
A relatively small amount of groundwater trickling through Alaska's tundra is releasing huge quantities of carbon into the ocean, where it can contribute to climate change, according to new research out of The University of Texas at Austin.
An international study has investigated the causes and impacts of the devastating flood disaster in the Himalayas in October 2023, which destroyed large areas along and surrounding the Teesta River in Sikkim, India.
While a single plant is capable of fixing inorganic carbon dioxide (CO2) from the air, the entire ecosystem surrounding the plant, including water, other organisms and soil conditions, influences how efficiently the ecosystem exchanges CO2.
Geospatial modeling methods have become an important tool for environmental monitoring, which is used to manage environmental risks and monitor natural disaster threats. The modeling results are an important source of information for forecasting and understanding the consequences of various scenarios of socio-economic development and climate change.
Studies of sediment cores from the sea floor and the coastal regions surrounding the Aegean Sea show that humans contaminated the environment with lead early on in antiquity.
An international team of Earth and environmental scientists has found evidence that the Ronne Ice Shelf in the West Antarctic did not melt during the last interglacial event, suggesting it could survive modern climate change. In their study published in the journal Nature, the team analyzed ice core samples taken from a site near the shelf's edge. The editors at Nature have also published a Research Briefing summarizing the work.
Author(s): Jiaolong Zeng, Aihua Deng, Cheng Gao, Yong Hou, and Jianmin Yuan
Understanding the ionization balance of extremely dense plasmas still remains a scientific challenge for both theory and experiment, which is very important in many research fields such as the equation of state, radiative opacity, and thermal and electrical conductivities. In a most recent experimen…
[Phys. Rev. E 111, 015211] Published Thu Jan 30, 2025
Author(s): Cheng Gao, Yongjun Li, Yong Hou, Fengtao Jin, Jiaolong Zeng, and Jianmin Yuan
In hot dense plasmas, orbital delocalization and relocalization considerably influence the ionization balance, equation of state and radiative properties of matter. A self-consistent plasma screening potential is applied in atomic structure calculations for solid-density Mg plasmas, generated by an …
[Phys. Rev. E 111, 015212] Published Thu Jan 30, 2025
Abstract
Integrated Water Vapor (IWV) is crucial in environmental research, offering insights into atmospheric dynamics. Direct IWV measurement is challenging, necessitating alternative estimation technologies. Existing methods including Global Navigation Satellite System (GNSS), radiosondes, water vapor radiometers (WVR), satellite remote sensing, and numerical weather models (NWM), have specific limitations. GNSS and WVR provide high precision and temporal resolution (e.g., 5 min) but are limited to specific locations. Radiosondes, while accurate, have sparse spatial distribution and low temporal resolution (e.g., twice daily). Satellite remote sensing offers broad spatial resolution but lower temporal resolution (hours to days) and reduced accuracy under cloudy conditions and due to satellite tracks. NWMs provide global hourly products but their accuracy depends on meteorological data and model precision.
This study introduces a regional IWV predictive model using Machine Learning to address these challenges. Utilizing IWV data from GNSS stations, the study develops a predictive model based on least squares support vector machine, which autonomously determines optimal parameters to enhance performance. The model enables accurate IWV estimation at any location within a region, using inputs such as latitude, longitude, altitude, and temperature, achieving an average root mean square error of 0.95 mm. The model’s performance varies across seasons and terrains, showing adaptability to diverse conditions. The model’s reliability is validated by comparing its predictions with the conventional ERA5 IWV method, showing a 61% improvement rate. This refined IWV estimation model is applied for regional climate analysis, demonstrating its practical utility in environmental research, specifically for the Upper Rhine Graben Region.
Nature Geoscience, Published online: 30 January 2025; doi:10.1038/s41561-024-01628-6
Waves breaking on sandy beaches globally contribute a similar amount of dissolved silicon to oceans as that from rivers, according to a global analysis informed by experiments performed on a simulated quartz sand beach.
SummarySeismic tomography is a principal method for studying mantle structure, but imaging of Earth’s wavespeed anomalies is conditioned by seismic wave sampling. Global models use misfit criteria that may strive for balance between portions of the data set but can leave important regional domains underserved. We evaluate two full-waveform global tomography wavespeed models, GLAD-M25 and SEMUCB-WM1, in the mantle below the Pacific Ocean. The region of the South Pacific Superswell contains multiple hotspots which may be fed by plumes anchored in the Large Low Shear-Velocity Province at the base of the mantle. The uneven distribution of seismic receivers worldwide leaves several candidate plumes beneath various hotspots poorly resolved. We assess the regional quality of GLAD-M25 relative to its global performance using a partition of the seismic waveform data used in its construction. We evaluate synthetic waveforms computed using the spectral-element method to determine how well they fit the data according to a variety of criteria measured across multiple seismic phases and frequency bands. The distributions of travel-time anomalies that remain in GLAD-M25 are wider for trans-Pacific paths than globally, suggesting comparatively insufficiently resolved seismic velocity structure in the region of interest. Hence, Pacific-centered regional inversions, based on (augmented) subsets of the global data set have the potential to enhance the resolution of velocity structure. We compare GLAD-M25 and SEMUCB-WM1 by cross-validation with a new, independent, data set. Our results reveal that short- and long-wavelength structure is captured differently by the two models. Our findings lead us to recommend focusing future model iteration on and around the Pacific Superswell and adding data that sample new corridors, especially using ocean sensors, to better constrain seismic velocity structure in this area of significant geodynamic complexity.
SummaryWe present a new 3D crustal P-wave velocity (VP) model for the greater Alpine region (GAR). We use and merge three different high-quality datasets for local earthquake tomography covering 24 years, starting from January 1st, 1996, up to December 31st, 2019. We processed and repicked the waveforms from the events reported by the European-Mediterranean Seismological Centre with M > 3.0 inside the greater Alpine region for the period between May 2007 and December 2015 using a recently developed automated arrival time-picking procedure (ADAPT framework). This allows bridging the data gap between previously published (pre-2007) datasets and the recently published AlpArray research seismicity catalogue and thus provides a high-quality, highly consistent set of P-wave arrival times covering 24 years. With this data set we derived a new minimum 1D VP model and associated station delays covering the entire GAR. Subsequently, we performed a series of local-earthquake-tomography (LET) inversions obtaining a 3D VP model with a horizontal node spacing of 20×20 km and between 7 to 15 km variable vertical spacing in the well-resolved area of investigation, thus improving the spatial and uniformly high-resolution coverage compared to previous LET studies in the area. For well-known major crustal structures, such as, e.g. the geophysical Ivrea body, deep foreland basins and main orogenic crustal roots, our tomographic results correlate well with features documented by various previous seismic studies in the region. This correlation increases our confidence in the model's accuracy throughout the well-resolved area. Additionally, our model reveals previously poorly known, or unknown crustal features and it documents details in the Moho topography throughout the region. Eventually, we present a LET-Moho map (VP isoline of 7.25 km/s) for the GAR with spatially nearly uniform resolution and document its comparison with previously published Moho maps. The new regional 3D VP crustal model also correlates well with a previously published VS crustal model obtained by ambient noise tomography. These comparisons document the new LET results of combined 3D VP crustal velocities and Moho topography being intrinsically consistent and reliable within the region of high resolution. Hence, in addition to further improving our understanding of crustal structure geometries in the GAR, our results also provide pivotal information for a future reference seismic 3D crustal model of the region.
SummaryNumerical simulations of infinite Prandtl number convection in Cartesian domains have shown that a combination of internal and basal heating allows for behaviour not observed in either end-member cases of pure basal or pure internal heating. In particular, these mixed heating systems exhibit a decrease in the upper boundary layer velocity as internal heating increases. This leads to an inverse relationship between surface heat flow and boundary layer velocity. The inverse relationship has been attributed to boundary layer interactions, leading to deviations from classic boundary layer theory. Herein, we extend that work by presenting results from numerical experiments for mixed-heated convection in an isoviscous fluid in a fully 3D spherical domain. We show that an increase in internal heating causes a decrease in surface velocity, consistent with previous Cartesian results. We confirm that boundary layer interactions decrease with increased internal heating, which correlates with decreasing surface velocities. A scaling theory, previously applied to Cartesian geometry, is modified for spherical geometries and tested against the results of the numerical solutions. The modified scalings lead to good fits for temperature and heat flux trends. The scalings predict that velocities can decrease with increased internal heating from low to moderate internal heating rates and become constant at higher heating rates, consistent with numerical results. The quantitative match between velocity scalings and numerical results is not as good as observed for heat flow and temperature trends. We attribute this to surface velocities being more strongly affected by observed changes in convective wavelengths and planform transitions from sheet-like to plume-like downwellings as the rate of internal heating and/or basal heating increases.
SummarySeismic tomography is used to image subsurface structures at various scales, accomplished by solving a nonlinear and nonunique inverse problem. It is therefore important to quantify velocity model uncertainties for accurate earthquake locations and geological interpretations. Monte Carlo sampling techniques are usually used for this purpose, but those methods are computationally intensive, especially for large datasets or high-dimensional parameter spaces. In comparison, Bayesian variational inference provides a more efficient alternative by delivering probabilistic solutions through optimization. The method has been proven to be efficient in 2D tomographic problems. In this study, we apply variational inference to solve 3D double-difference (DD) seismic tomographic system using both absolute and differential travel time data. Synthetic tests demonstrate that the new method can produce more accurate velocity models than the original DD tomography method by avoiding regularization constraints, and at the same time provides more reliable uncertainty estimates. Compared to traditional checkerboard resolution tests, the resulting uncertainty estimates provide a better measure for the reliability of the solution. We further apply the new method to data recorded by a local dense seismic array around the San Andreas Fault Observatory at Depth (SAFOD) site along the San Andreas Fault (SAF) at Parkfield. Similar to previous studies, the obtained velocity models show significant velocity contrasts across the fault. More importantly, the new method produces velocity uncertainties of less than 0.34 km/s for ${{\rm{V}}}_p$ and 0.23 km/s for ${{\rm{V}}}_s$. We therefore conclude that variational inference provides an effective tool for solving 3D seismic tomographic problems and quantifying model uncertainties.
The precise position and geometry of a fault and the recognition of contemporary active strands are pivotal elements for formulating regulations for earthquake fault zones and fault setbacks. The western front...
An international research team led by the University of Göttingen has investigated the influence of the forces exerted by the Zagros Mountains in the Kurdistan region of Iraq on how much the surface of the Earth has bent over the last 20 million years. Their research has revealed that in the present day, deep below the Earth's surface, the Neotethys oceanic plate—the ocean floor that used to be between the Arabian and Eurasian continents—is breaking off horizontally, with a tear progressively lengthening from southeast Turkey to northwest Iran.
