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In late November, a very interesting open access paper (Darrow and Jacobs 2025) was published on the journal Landslides. This piece of work sought to understand the patterns of landslides in Alaska over a century through the creation of a database compiled from “a combination of 24 digital newspapers and online media sources, including historic digitised Alaskan newspapers”. Such a study is an epic amount of work, but yields fantastic data. This study is no exception.

What is of particular interest here is that Alaska suffers from a range of landslide hazards, and suffers significant losses from them, and it is an environment in which climate change is clearly occurring, with warming at a rate that is higher than the global average. Previous studies have shown that this is having a measurable impact on landslides in the mountains of Alaska.

In total, Darrow and Jacobs (2025) have identified 281 landslides since 1883 in Alaska, with the occurrence showing a strong seasonal pattern associated primarily with seasonal patterns of rainfall. The headline from the paper is summarised in this graphic from the paper:-

The recorded incidence of landslides in Alaska by decade, from Darrow and Jacobs (2025).

The data shows a dramatic increase in landslides in recent decades, and in particular in the last two decades or so. Of course, care is needed to ensure that this is not an artefact of the reporting of landslides, but Darrow and Jacobs (2025) explored this issue in detail, concluding that the signal is real. Fortunately, the number of fatalities caused by landslides in Alaska is small, and there is no significant trend in terms of fatal landslides.

So what lies behind this change? Darrow and Jacobs (2025) show that the increase in occurrence of landslides in Alaska is associated with a marked increase in in average annual air temperature that ranges between 1.2 C and 3.4 C, and an associated increase in precipitation that ranges from 3% to 27%, over the 50 years.

Of course, warming is not going to stop in Alaska in the next few decades, so the likely direction of travel in terms of landslides there is clear. There is recognition in Alaska that greater attention will be needed on landslides.

But more widely, this is further quantitative evidence that the climate is having a big impact on landslide hazard. It is remarkable how the evidence just keeps accumulating.

Reference

Darrow, M.M. and Jacobs, A. 2025. Read all about it! A review of more than a century of Alaskan landslides as recorded in periodicals. Landslides. https://doi.org/10.1007/s10346-025-02663-z.

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.

Ancient African bedrock reveals the violent beginnings of life on our blue planet

Phys.org: Earth science - Fri, 01/02/2026 - 14:56

You have probably seen the images of the surface of Mars, beamed back by NASA's rovers. What if there were a time machine capable of roaming Earth during its remote geological past, perhaps even going right back to its beginnings, beaming back pictures of similar quality?

Marine Heat Waves Can Exacerbate Heat and Humidity over Land

EOS - Fri, 01/02/2026 - 14:52

Source: AGU Advances

In 2023, Earth experienced its warmest year since 1850, with heat waves stretching across oceans and land alike. East Asia, for example, experienced scorching temperatures and high humidity throughout the summer months. Humid-heat extremes like those seen that year can trigger heat-related illnesses and mortality at higher-than-average rates.

As on land, the ocean around East Asia also experienced unprecedented warming in 2023. Sea surface temperatures (SST) in the Kuroshio-Oyashio Extension region reached record highs, persisting through much of the year. Researchers know that marine heat waves can influence land heat waves, but the details of these connections remain unclear.

Okajima et al. modeled regional land-sea interactions to better understand the effects of the unprecedented 2023 marine heat wave on conditions on land in East Asia. The team focused on the peak hot and humid months of July, August, and September, using hourly data on atmospheric conditions, including temperature, humidity, wind velocity, and atmospheric pressure, as well as SST data from satellites and in situ sensors.

The modeling suggested that the 2023 marine heat wave greatly exacerbated the East Asian heat wave, particularly in Japan, by affecting atmospheric circulation and altering the usual radiative effects of clouds and water vapor. The team said the influence of the marine heat wave explains roughly 20% to 50% of the increase in the intensity and duration of hot and humid conditions observed on land in East Asia in summer 2023.

The scientists note that this research provides valuable insights that could help improve long-range weather predictions. Such predictions may help communities prepare for health risks, particularly in Asia, which the World Meteorological Organization reported earlier this year is warming twice as fast as the global average. (AGU Advances, https://doi.org/10.1029/2025AV001673, 2025)

—Sarah Derouin (@sarahderouin.com), Science Writer

Citation: Derouin, S. (2025), Marine heat waves can exacerbate heat and humidity over land, Eos, 107, https://doi.org/10.1029/2026EO260009. Published on 2 January 2026. Text © 2026. AGU. 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.

Subsurface structure across the Tacoma Basin, Washington State, using trans-dimensional Bayesian inversion of fundamental mode spatial autocorrelation data

Geophysical Journal International - Fri, 01/02/2026 - 00:00

SummarySpatial autocorrelation (SPAC), the azimuthal average of the normalized cross-correlation between equidistant station pairs deployed in a 2-D array, is widely used to image the subsurface structure. However, the rigorous estimate of subsurface structure and its uncertainties as a function of depth using SPAC data is challenging due to the nonlinear relation between the SPAC data and Earth structure as well as the trade-off between depth and velocity. Additionally, data noise is strongly correlated due to data processing (e.g., filtering, stacking from multiple time segments and azimuthal averaging). Most studies do not account for the correlated noise and fix the ratio of compressional-wave velocity (${V}_P$) to shear-wave velocity (${V}_s$) (i.e., ${V}_P$/${V}_s$ ratio) and the number of layers, both of which are typically unknown. To address these challenges, we develop a hierarchical trans-dimensional Bayesian inversion of fundamental mode of SPAC data that properly accounts for the correlated data noise, samples the ${V}_P$/${V}_s$ ratio, and relaxes the number of layers (i.e., model parameterization) to be unknown in the inversion. We further examine the limitation of using only fundamental modes in the inversion. Our synthetic experiments show that the inversion recovers an incorrect model unless we sample the correlated noise and ${V}_P$/${V}_s$ ratio in the inversion. The inversion is then applied to SPAC data acquired at 19 sites across the Tacoma basin in Washington State to characterize the ${V}_s$ and the time-averaged ${V}_s$ over 30-m depth ($V{s}_{30}$). Our results show that the $V{s}_{30}\ $varies from ∼200 m/s to 800 m/s. The $V{s}_{30}$ within the basin is higher in the middle and lower on the east and west sides. We find that these $V{s}_{30}$ values vary with geologic unit. The uncertainties for $V{s}_{30}$ are within 20 m/s in average except for the most eastern site TB28. Additionally, the uncertainties are greater for deeper depths beneath most of the sites as the sensitivity decreases as a function of depth. The ${V}_s$ structure as a function of depth is also complex beneath some sites, possibly because the SPAC curves are affected by higher order Rayleigh modes that are not considered in the inversion. To better constrain the deeper ${V}_s\ $structure, $V{s}_{30}$, and/or other average measures of ${V}_s$ over depth, additional constraints from complementary data, such as ellipticity or geologic data are needed. Moreover, our synthetic experiments show that higher order modes can have significant effect in the inversion results, particularly when there is a low-velocity layer.

Regional Geomagnetic Field Modeling Method Based on a Two-Stage Adaptive Weight Physics-Informed Neural Network

Geophysical Journal International - Fri, 01/02/2026 - 00:00

SummaryRegional geomagnetic field models are used to delineate intricate details of the Earth’s magnetic field and have significant application value in precision navigation and geomagnetic exploration. However, traditional modeling methods often encounter challenges when applied to sparse data, leading to issues like low model resolution and accuracy, as well as limited generalizability. The recently developed physics-informed neural networks (PINNs), a powerful modeling tool, presents a viable alternative for regional geomagnetic field modeling. This study employed the PINNs method to construct a geomagnetic field model for satellite altitudes over the Chinese region, based on the Swarm satellite dataset provided by the European Space Agency. An adaptive weight training method was used for the two-stage training process, involving an initial pre-training and subsequent fine-tuning of the model. Experimental verification shows that the proposed algorithm enhanced the model’s fidelity to physical laws, improved its resolution and prediction accuracy (reducing the root mean square errors for geomagnetic components to as low as 4 nT), and enhanced its generalizability, with the total field intensity F and the prediction accuracy of both the X- and Y-components demonstrating superiority over that of other traditional methods. Collectively, these advancements enable efficient regional geomagnetic field modeling while providing a foundation for more reliable and precise predictions.

GNSS carrier phase time and frequency comparison for gravity potential determination

Geophysical Journal International - Fri, 01/02/2026 - 00:00

SummaryDetermining the gravity potential is a fundamental task in geodesy and plays a critical role in various fields, including seismology, geodynamics and aerospace engineering. Grounded in the principles of general relativity, the high-precision determination of gravity potential using time and frequency signals has become a prominent research frontier in modern geodesy. This study employs multi-GNSS (Global Navigation Satellite System) carrier phase time and frequency comparison to determine the gravity potential. It develops a model for multi-GNSS Precise Point Positioning (PPP) time and frequency comparison, incorporating gravity potential estimation, and further investigates simulation methods for high-precision clock offsets and GNSS observations. Ten time and frequency links formed by eleven stations from the IGS (International GNSS Service) were analyzed using a simulation framework. The experiment incorporated simulated GNSS observations and eight types of clocks with varying performance levels to assess the capability of the multi-GNSS PPP time and frequency comparison model in determining gravity potential. The results demonstrate that the accuracy of gravity potential determination with multi-GNSS time frequency signal after coverage is approximately 0.1 m²/s². These findings affirm the feasibility and reliability of using GNSS time and frequency signals to determine gravity potential. Moreover, the convergence speed and accuracy of PPP solutions with ambiguity resolution show notable improvements over ambiguity float solutions, with accuracy enhanced by roughly 10 per cent. As atomic clock performance and GNSS satellite products continue to advance, GNSS-based time and frequency comparison holds great promise for achieving even higher precision in gravity potential measurements and contributing to the unification of the global vertical height datum.

DynCFS: A Program for Modeling Dynamic Coulomb Failure Stress Changes in Layered Elastic Media

Geophysical Journal International - Fri, 01/02/2026 - 00:00

SummaryCoulomb failure stress change (ΔCFS) quantifies the earthquake-induced difference of shear stress and frictional resistance on a receiver fault, with the latter being proportional to the effective normal stress change. ΔCFS has become a widely used measure for studying earthquake triggering, dynamic rupture processes and earthquake-induced secondary disasters. In simple layered or half-space elastic media, methods for computing static ΔCFS have been well established, with programs such as Coulomb3, PSGRN-PSCMP, and AutoCoulomb being widely used. In contrast, dynamic ΔCFS evaluation generally relies on numerical discretization schemes, such as finite-difference, finite-element, boundary-element and discontinuous Galerkin methods, which, while suitable for complex structures, are computationally expensive. To overcome these limitations, we develop DynCFS, a user-friendly, Green’s function based and therefore computationally efficient program for calculating both static and dynamic ΔCFS in layered elastic media. The tool enables rapid assessment of dynamic triggering effects, both between successive earthquakes and among multiple sub-events or faults during an earthquake.