Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): Zengyi Lyu, Zhe Dong
Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): Jingxian Zhu, Haodong Yang, Jianying Wang
Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): Zhifan Yan, Jinyun Guo, Maosheng Zhou, Jingwen Zong
Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): Haili Lin, Hao Liu, Dongsheng Zhao, Kefei Zhang, Suqin Wu, Craig M. Hancock
Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): Bharati Kakad, Chougule Prathmesh, Amar Kakad
Publication date: 1 November 2026
Source: Advances in Space Research, Volume 78, Issue 9
Author(s): R. Satheeskumar, K. Uma, Talatoti Ratna Kumar, CH V Satyanarayana
In the deep sea, it never stops snowing. The type of snow that falls in the ocean, known as marine snow, is very different from the flaky geometric wonders that fall on land. Marine snow describes tiny clumps of organic and inorganic detritus—think mucus, poop, silt, dead plankton, etc.—that rain from the shallows into the deep.
New research led by Vrije Universiteit Brussel (VUB) and published in the journal Earth System Dynamics shows a clear warming signal across the Congo Basin since the 1960s, using historical weather records from the Democratic Republic of the Congo (DRC). These records come from the paper archives of the Institut National pour l'Etude et la Recherche Agronomiques (INERA) in Yangambi, DRC, and the State Archives of Belgium.
Researchers at the Mubadala Arabian Center for Climate and Environmental Sciences (ACCESS) at NYU Abu Dhabi have developed a new algorithm that can forecast Arctic sea ice extent up to nine months in advance, offering a new way to anticipate changes in the Arctic that can affect the global climate system. The research is published in the journal Scientific Reports.
Nearly 300,000 people may live in areas at risk of flooding in the Nepalese, Indian and Chinese areas of the Himalayas. The results, from a study published in Scientific Reports, also indicate that the total area covered by buildings within potential flood zones increased by approximately 45% between 2016 and 2023.
Mountains preserve evidence of ancient oceans, moving continents and tectonic processes that have shaped Earth over millions of years. Later deformation, erosion and burial, however, can obscure important parts of this geological record. An international research team led by Istanbul Technical University (ITU) has identified evidence of a previously unrecognized Late Cretaceous continental magmatic arc in northwestern Iran.
SummaryMost geologic materials exhibit a low-frequency dispersion of the complex conductivity that can be used to investigate their petrophysical characteristics. This frequency-dependent behavior is caused by polarization processes on the microscale, which can be described and investigated by suitable mechanistic models. However, most existing models only consider the polarization of single particles and can only be upscaled using simplistic models. In particular, the effect of particle-particle interaction on the microscale is often neglected. We present numerical models of systems of two particles and of clusters of particles to investigate the effect of interaction between adjacent particles on the modeled complex-conductivity spectra. Due to numerical reasons, most of the simulations are done in 2d. We observe that the peak caused by the polarization of the individual particles is increased or decreased, depending on the orientation of the particles relative to the external electric field. For small distances between the particles, we also observe a membrane-like polarization of the particle-particle interspace when the particles are not aligned with the electric field. For clusters of particles, the membrane-like behavior manifests itself by several minor peaks related to the different length scales of these interspaces. An additional polarization process is present for finite particle clusters, that is related to the polarization of the cluster as a whole, which becomes the main polarization process when the distance between the particles is decreased to zero, i. e., neighboring particles are in direct contact to each other. In that case, the length scale of the individual particles only acts as surface roughness. Our modeling results clearly show that we must expect particle-particle interaction to significantly increase the complexity of the low-frequency polarization response. Therefore, interaction effects need to be taken into account by considering the detailed microscale structure of the pore space for the interpretation of complex-conductivity spectra of geological materials.
Polar oceans may play an important role in storing carbon and supporting biodiversity, but current science and policy frameworks are not yet ready to fully recognize their potential.
Episodic lava fountaining is a rare volcanic behavior in which repeated, hours-long bursts of molten lava and gas are spewed from volcanic vents, with quiet pauses lasting days to weeks between episodes. These lava fountains have been observed in active volcanoes in places like Hawaii, Iceland and Italy, but researchers still do not fully understand what starts, sustains or stops these individual fountain episodes.
Parts of Earth's climate system can change abruptly once warming pushes them beyond critical thresholds. The Greenland and Antarctic ice sheets, the Amazon rainforest, coral reefs and major ocean currents are all among the systems containing potential climate tipping points.
When the COVID-19 pandemic brought human activity to a standstill around the world in the first half of 2020, wildfire incidents also declined by more than 12%. A new study published in Cell Reports Sustainability reveals the complex role humans play in shaping global fire patterns, both as a source of fire and in helping keep fires in check.
Nitrogen is one of life's building blocks, but it's only helpful in the right amounts. Too much nitrogen in water, for example, can lead to poor water quality and the gradual death of aquatic organisms. Microbes remove nitrogen from water by converting it to a gas that escapes into the atmosphere. But scientists have difficulty determining how much nitrogen is removed this way.
Author(s): Lifang Dong, Cheng Li, Xiaoxiu Qi, Yunan He, Yaohua Li, and Yuyang Pan
Effectively controlling the spatial distribution of filaments and improving their physical properties are crucial for advancing the applications of dielectric barrier discharge. In this work, we report a dielectric barrier discharge device to simultaneously regulate filament distribution and improve…
[Phys. Rev. E 114, 045204] Published Fri Oct 09, 2026
A new academic paper by Paul Hanson and Matthew Joeckel of the Conservation and Survey Division in the University of Nebraska–Lincoln's School of Natural Resources contains a brief phrase—"new linework"—that looks innocuous but carries enormous meaning.
SummaryGeophysical data observed in the Earth, planetary, and lunar sciences are spatially limited to sampling plans designed to span a feature of interest whose resolution and regularity in discretization are bound by site, observational, and instrumental constraints. Common wisdom tells us that the more observations we make, the less variable our estimates of statistical properties of measured physical quantities will be. However, given the limited spatial extent and possibly irregular sampling of any dataset, how confident can we be in our estimates of the parameters of statistical processes underlying such fields? We study how sampling geometry contributes to uncertainty in modeling spatial geophysical observations as sampled random fields characterized by stationary, isotropic, parametric covariance functions. We incorporate the signature of discrete spatial sampling patterns into an asymptotically unbiased spectral maximum-likelihood estimation method along with analytical uncertainty calculation. We illustrate the broad applicability of our modeling through synthetic and real data examples with sampling patterns that include irregularly bounded contiguous regions of interest, structured sweeps of instrumental measurements, and missing observations dispersed across the domain of a field, which spur behaviors in the estimator. We find through asymptotic studies that allocating samples following a growing-domain strategy rather than a densifying, infill scheme best reduces estimator bias and (co)variance, whether the field has been sampled regularly or not. As our modeling assumptions, too, shape how (well) an observed random field can be characterized, we study the effect of covariance parameters assumed a priori. We demonstrate the desirable behavior of the general Matérn class and show how to interrogate goodness-of-fit criteria to detect departures from the null hypothesis of Gaussianity, stationarity, and isotropy.
