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SummaryWe simulate an instantaneous time mirror (ITM), i.e., a rapid short duration change in elastic material properties, using numerical experiments in time-varying isotropic elastic media. Our implementation in the seismic wave propagation software SeisSol is based on high-order discontinuous Galerkin discretization with ADER time stepping. We develop an eigenvector-based analytical solution for time interfaces for general linear hyperbolic wave systems and apply it to analyze the energy balance at time boundaries and ITMs. The energy increases for all intermittent medium changes for all impedance scaling factors. Our numerical implementation is validated against these analytical solutions and achieves high-order convergence. Its accuracy is further corroborated by estimates of reflection and transmission coefficients and observed frequency shifts across time boundaries, and by acoustic wave speed estimates obtained from focal spots associated with ITM-generated converging P waves that are consistent with theoretical predictions and ground truth values, respectively. We use the ITM implementation to simulate the partitioning of seismic body waves excited by a point source in a spatially homogeneous elastic full space. The response to an intermittent short change in the elastic parameters yields a diverging and converging P and S wavefield. A systematic scaling of the elastic parameters is then used to steer independent ITM reflections of either P or S waves. Numerical ITM solutions as developed here can be used to synthesize converging wavefields in seismic imaging applications, and more generally to analyze the behavior and manipulation of seismic wavefields in space-time varying media.

For decades, researchers thought that an October 1843 earthquake on the small Greek island of Chalke caused a powerful tsunami and led to the deaths of as many as 600 people. But a new analysis of primary accounts of the event by Ioanna Triantafyllou at Hellenic Mediterranean University suggests the truth was much less dramatic and destructive.

Greenland, which has been prominently in the news in recent days, hosts a vast ice sheet. If it melts, it will become one of the largest contributors to global sea-level rise. Under a high-emissions scenario, the Greenland Ice Sheet is expected to largely disappear over time, with far-reaching consequences. This is the conclusion of a new study by Chloë Paice and colleagues, published in The Cryosphere. The Greenland Ice Sheet contains enough ice to raise global sea levels by approximately 7.4 meters and has been losing mass at an accelerating rate since the 1990s. Roughly half of this loss is due to surface melt, while the other half results from ice calving where the ice sheet meets the ocean.

Organic matter carried in rivers to the Russian part of the Arctic Ocean may be creating more clouds and keeping the region cooler, a new study has found.

Editors’ Highlights are summaries of recent papers by AGU’s journal editors. Source: Journal of Geophysical Research: Biogeosciences

Ocean acidification is known to have major impacts on marine habitats under projected climate change. How vulnerable marine organisms in these habitats are to acidification largely depends on the variability of environmental conditions, such as pH, they experience naturally.

Burdett et al. [2025] provide precious time-series evidence that, unlike the open ocean, coastal ecosystems experience high natural environmental variability. For about two thirds of the year, the monitored coastal coralline algae reef was exposed to pH levels as low as those expected for the year 2100 under IPCC projections. The pH levels varied considerably throughout the day and between seasons, associated with biological activity, tidal cycling, and water temperature. Long‐term exposure to such low pH conditions and high variability may help coralline algal communities to adapt to future acidification, providing a level of optimism for the survival of this globally distributed biodiverse habitat.

Citation: Burdett, H. L., Mao, J., Foster, G. L., & Kamenos, N. A. (2025). Persistence of extreme low pH in a coralline algae habitat. Journal of Geophysical Research: Biogeosciences, 130, e2025JG009062. https://doi.org/10.1029/2025JG009062

—Xiaojuan Feng, Associate Editor, JGR: Biogeosciences

Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Publication date: 15 January 2026

Source: Advances in Space Research, Volume 77, Issue 2

Author(s): Jingkai Meng, Chunhua Han, Jiale An, Zhongcai Gao, Yurong Li, Yongjun Li

Publication date: 15 January 2026

Source: Advances in Space Research, Volume 77, Issue 2

Author(s): Huayi Zhang, Na Wei, Jun Xu, Long Yang, Yikai Feng, Dongxu Zhou, Yongduo Lu

Publication date: 15 January 2026

Source: Advances in Space Research, Volume 77, Issue 2

Author(s): Ricky Anak Kemarau, Oliver Valentine Eboy, Zaini Sakawi, Stanley Anak Suab

Publication date: 15 January 2026

Source: Advances in Space Research, Volume 77, Issue 2

Author(s): Xiaohui Chen, Alireza Arabameri, M. Santosh, Hasan Raja Naqvi, Mohd Ramiz

Publication date: 15 January 2026

Source: Advances in Space Research, Volume 77, Issue 2

Author(s): Junye Zhu, Yutong Liu, Kefan Xu, Yangshu Lin, Keqi Wang, Zhiming Lin, Qiwen Jin, Chao Yang, Lijie Wang, Chenghang Zheng, Yongxin Zhang, Xuecheng Wu

Our planet is unique for its ability to sustain abundant life. From studies of the rock record, scientists believe life had already emerged on Earth at least 3.5 billion years ago and probably much earlier.

A new global study shows that increasing soil salinity is systematically reshaping the storage and distribution of soil inorganic carbon (SIC), a key but often-overlooked part of terrestrial ecosystems. The findings, published in the Proceedings of the National Academy of Sciences on January 20, provide the first comprehensive global assessment of how soil salinization influences inorganic carbon storage and highlight its implications for the global carbon cycle.

Beneath Antarctica's Ross Ice Shelf lies one of the least measured oceans on Earth—a vast, dark cavity roughly twice the volume of the North Sea.

La Niña—a climate phenomenon characterized by unusually cool sea surface temperatures in the central and eastern tropical Pacific Ocean—can persist for multiple years, exerting significant climate impacts worldwide. In recent decades, such prolonged La Niña events have grown more frequent. However, the mechanisms that sustain these multiyear cooling episodes have remained unclear.

A 66 million-year-old mystery behind how our planet transformed from a tropical greenhouse to the ice-capped world of today has been unraveled by scientists. Their new study has revealed that Earth's massive drop in temperature after the dinosaurs went extinct could have been caused by a large decrease in calcium levels in the ocean.

Eight people have been killed or are missing in two landslides triggered by heavy rainfall in New Zealand

Substantial parts of New Zeealand have been suffering extreme rainfall – yet again – causing floods and landslides. The most serious event to date occurred at a camp site at Mount Maunganui on the Bay of Plenty in the North Island. Here, a landslide devastated a campsite close to the coast. Unfortunately, January is the main summer holiday period in New Zealand.

Stuff has a video of the landslide as it occurred. Meanwhile, The Guardian has a Youtube video with imagery of the aftermath:-

This still shows the basic components of the failure:-

The aftermath of the 22 January 2026 landslide at Mount Maunganui. Still from a video posted to Youtube.

The location is reported to be the Mount Maunganui Beachside Holiday Park. This makes the location [-37.63234, 176.17507]. This is Google Earth image of the site:-

Google Earth image of the site of the 22 January 2026 landslide at Mount Maunganui.

The image suggests a complex geology, with maybe a hint of previous landslides (this is very speculative). The geology of this area is primarily volcanic rocks, which may indicate a high landslide susceptibility. The images of the aftermath appear to suggest deeply weathered soils, and note the amount of water flowing through the debris.

News reports indicate that at least six people are missing, some of whom are children., The authorities are continuing to describe the operation at the site as a rescue.

Meanwhile, two other people were killed by an early morning landslide at Welcome Bay Road in Papamoa, also on the Bay of Plenty. This appears to have occurred at about [-37.7231, 176.20896]. One News has an image of the aftermath of the event that appears to show multiple shallow landslides on the same hillside.

Return to The Landslide Blog homepage Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

The asteroid that struck the Earth 66 million years ago devastated life across the planet, wiping out the dinosaurs and other organisms in a hail of fire and catastrophic climate change. But new research shows that it also set the stage for life to rebound astonishingly quickly.

Global average temperature increases could pass the 1.5 degrees Celsius threshold outlined in the Paris Agreement by the end of the decade, according to the EU's Copernicus Climate Change Service, putting the world at greater risk of never-seen-before extreme weather events.

SummaryAccurate characterization of the magnitude-frequency distribution of seismicity, and its associated uncertainties, is essential for seismic hazard assessment. This distribution is commonly described by the Gutenberg–Richter (GR) relation, parameterized by the b-value, which has been identified as a potential proxy for investigating many spatiotemporally varying Earth phenomena. Estimating the spatiotemporal variability of b-values often requires windowing, forcing a trade-off between resolution and statistical reliability. New probabilistic methods circumvent this by inferring both the number and locations of change points directly from earthquake catalogs. Nevertheless, accurately determining the b-value remains difficult because the GR relation only holds over a limited range of magnitudes. This research develops a general statistical model to address several methodological challenges in estimating the magnitude-frequency distribution of observed seismicity, including variations in space or time. The approach simultaneously solves for the b-value and magnitude-range limits. This avoids potential bias due to inaccurate manual truncation of earthquake catalogs. The model considers the entire observed catalog and parameterizes the decay of the distribution at both low and high magnitudes. Consequently, robust uncertainties in estimated b-values reflect uncertainty in the range of magnitudes over which the GR relation is observed to be valid. Importantly, spatiotemporal variations in the parameters that define the magnitude range are considered to be independent from the b-value, as we assume the physical factors that influence the GR relation are independent of the factors that limit the observed earthquake catalog. We demonstrate this methodology through application to simulated and observed earthquake catalogs. In particular, the value of our approach is highlighted through application to observed records of induced seismicity associated with fluid-injection operations in western Canada. Our results demonstrate accurate b-value estimates and associated uncertainties. Furthermore, the additional parameters that define the magnitude range serve as proxies for other factors including seismic network performance, recording duration, potential geometric limitations on earthquake size, and potential injection characteristics (in induced seismicity cases). Our approach also allows for the investigation of how these other factors may vary in space/time. Results from this work contribute to rigorous propagation of accurate b-value estimates, including uncertainties, into subsequent analyses such as seismic hazard models and regulatory protocols that are applied to industrial activity.

SummarySeismic emissions from wind turbines (WTs) depend on the rotation of the WT blades and the wind direction-dependent movement of the WT. Mechanical coupling between the WT foundation and the subsurface generates complex seismic wavefields, making it challenging to manually separate the contributions of different signal sources, thus complicating data labelling. We address this challenge by applying unsupervised machine learning techniques that do not require labelled data. Our analysis focuses on seismic WT emissions recorded near Wind Farm Tegelberg in the eastern Swabian Alb, Southwest Germany. Specifically, we extract time-averaged wavelet features by temporal averaging the wavelet transformation of the continuous three-component seismic data and subsequently apply the clustering algorithm Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). The resulting clusters not only capture the variations in the WT rotation rate but also reveal a clear dependency on wind direction, associated with the radiation pattern of different surface waves. Our results demonstrate the potential of HDBSCAN to uncover meaningful, source-related patterns in continuous seismic records.