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SummaryMonitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations, or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types, and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements:(i) A likelihood function that describes the distribution of detection and travel time data from the sensor network,(ii) A prior distribution that describes a priori belief about seismic events,(iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data,(iv) An algorithm to compute EIG about seismic events over a dataset of hypothetical prior events,(v) An optimizer that finds a sensor network which maximizes EIG.Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number, and locations influence uncertainty; and how prior models and constraints influence sensor placement.

Abstract

Partial ambiguity resolution (PAR) has been widely adopted in real-time kinematic (RTK) and precise point positioning with augmentation from continuously operating reference station (PPP-RTK). However, current PAR methods, either in the position domain or the ambiguity domain, suffer from high false alarm and miss detection, particularly in challenging environments with poor satellite geometry and observations contaminated by non-line-of-sight (NLOS) effects, gross errors, biases, and high observation noise. To address these issues, a PAR method based on machine learning is proposed to significantly improve the correct fix rate and positioning accuracy of PAR in challenging environments. This method combines two support vector machine (SVM) classifiers to effectively identify and exclude ambiguities those are contaminated by bias sources from PAR without relying on satellite geometry. The proposed method is validated with three vehicle-based field tests covering open sky, suburban, and dense urban environments, and the results show significant improvements in terms of correct fix rate and positioning accuracy over the traditional PAR method that only utilizes ambiguity covariances. The fix rates achieved with the proposed method are 93.9%, 81.9%, and 93.1% with the three respective field tests, with no wrong fixes, compared to 72.8%, 20.9%, and 16.0% correct fix rates using the traditional method. The positioning error root mean square (RMS) is 0.020 m, 0.035 m, and 0.056 m in the east, north, and up directions for the first field test, 0.027 m, 0.080 m, and 0.126 m for the second field test, and 0.035 m, 0.042 m, and 0.071 m for the third field test. In contrast, only decimeter- to meter-level accuracy was obtainable with these datasets using the traditional method due to the high wrong fix rate. The proposed method provides a correct and fast time-to-first-fix (TTFF) of 3–5 s, even in challenging environments. Overall, the proposed method offers significant improvements in positioning accuracy and ambiguity fix rate with high reliability, making it a promising solution for PAR in challenging environments.

A new study finds that climate change may have a range of contrasting effects on coastal forests, both slowing and enabling growth in areas where sea levels are rising and storms are more common.

On the basis of current carbon emissions rates and climate policies, average global temperatures are projected to increase to 2.9°C above preindustrial averages by the end of the century. Such an increase would severely strain global agriculture, making large tracts of current production areas unsuitable for crops and livestock. At the same time, the Food and Agriculture Organization of the United Nations estimates that food production needs to increase by 70% to keep pace with population growth.

In a recently published paper, NASA scientists use nearly 20 years of observations to show that the global water cycle is shifting in unprecedented ways. The majority of those shifts are driven by activities such as agriculture and could have impacts on ecosystems and water management, especially in certain regions.

Research co-led by the University of Maryland reveals that drought and increased temperatures in a CO2-rich climate can dramatically alter how grasslands use and move water.

Increasingly common since 1980, persistent multi-year droughts will continue to advance with the warming climate, warns a study from the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), with Professor Francesca Pellicciotti from the Institute of Science and Technology Austria (ISTA) participating.

Approximately 66 million years ago, the Chicxulub asteroid, estimated to be 10–15 kilometers in diameter, struck the Yucatán Peninsula (in current-day Mexico), creating a 200-kilometer-wide impact crater. This impact triggered a chain reaction of destructive events, including a rapid climate change that eventually led to the extinction of the non-avian dinosaurs and, in total, about 75% of species on Earth.

Dichlorodiphenyltrichloroethane (DDT) soil pollution is still a major problem in many parts of the world. Researchers at Chalmers University of Technology, Sweden, have developed a new method to manage ecological risks from the toxin by binding it with biochar. When they mixed biochar into contaminated soil at a former tree nursery, DDT uptake by earthworms in the soil was halved. This method may enable the growing of certain crops on land that is currently considered unusable due to environmental risks.

Permafrost thaw poses multiple risks to local Arctic communities, their livelihoods, infrastructure and environment. A transdisciplinary study led by Umeå University and others has identified key risks across four Arctic regions. This allows communities to adapt and make informed decisions.

The synchronization of data from two natural climate archives—a speleothem from the Herbstlabyrinth Cave in Hesse (Germany) and ice cores from Greenland—offers new insights into the chronology of abrupt climate changes in Central Europe.

As climate change drives increasingly severe hurricanes, U.S. coastal communities are bearing the brunt of mounting losses. With regulations failing to curb the damage, homeowners have become the front line of defense—but their efforts often fall short, a recent study reveals.

Ecological warning lights have blinked on across the Arctic over the last 40 years, according to new research, and many of the fastest-changing areas are clustered in Siberia, the Canadian Northwest Territories, and Alaska.

The Little Ice Age was a period of significant cooling from the early 14th to mid-19th centuries, which saw mean temperatures across the northern hemisphere drop by up to 2°C and the advancement of glaciers.

Author(s): Augustin Blanchet, François Soubiran, Marc Torrent, and Jean Clérouin

We computed the equation of state of iron using extended first-principles molecular dynamics simulations, ranging from 7.874g/cm3 and 5500 K up to 47.2g/cm3 and 109K. We compared the principal Hugoniot curve with semiempirical models, average atom-based model predictions, and shock experiment result…

[Phys. Rev. E 111, 015206] Published Thu Jan 16, 2025

Nature Geoscience, Published online: 16 January 2025; doi:10.1038/s41561-025-01643-1

Author Correction: Recent uplift of Chomolungma enhanced by river drainage piracy

SummaryThe seismic wavefield is fully described by translation, rotation and strain. Until recently, the seismological community has not been able to measure rotation directly with portable sensors with satisfactory resolution. Portable blueSeis-3A (Exail) sensors allow measuring 3 components of rotational motions. Co-located with conventional seismometers, one can locally observe six degrees of freedom (6 DoF) of ground motion. To test the performance of the rotational sensors, an active source experiment was carried out in Fürstenfeldbruck, Germany, in November 2019. Five explosions with different yields and distances from our sensors, were fired. In a first stage, eight rotational sensors were deployed inside a bunker next to a seismometer. In a second stage, the rotational sensors were installed in two clusters of 4 sensors each. We compare the back azimuths derived using two different methods: (i) a method using horizontal rotational components and (ii) a standard polarization analysis using only 3C translational data. Back azimuths calculated using rotational data for 5 explosions have an average 10.2○ deviation from the theoretical back azimuths. Estimates using 3C translational data for the first stage of the experiment have a 1.8○ deviation from the theoretical back azimuth. For the second stage we found a 29.4○ deviation using the seismometer from stage 1. We conclude that within our distance range from 50 m to 1070 m, all rotational sensors provide reliably back azimuths of explosive sources when using only horizontal rotational components. For future applications of rotational sensors in other environments this is promising as back azimuths can be derived reliably.

SummaryA new global mascon solution using GRACE and GRACE Follow-On data is co-estimated with Satellite Laser Ranging (SLR) measurements to seven major geodetic satellites. This combined solution is compared with an otherwise similar GRACE-only solution to determine improvements in the estimate. We find similar performance between both solutions in the recovered mass change, but significant improvements in the associated errors in the combination solution. Errors in recovered basin mass change are 10-20% better for the combination solution across all basin sizes, with the greatest improvements in high latitude ice sheets. These results lead to our recommendation that all GRACE Level 3 mascon and spherical harmonic user-oriented gridded solutions should include SLR information during the solution inversion. As an ancillary contribution, we also provide validation of the choice of truncated spherical harmonics used in determining GRACE Technical Note 14, the current recommended mechanism for including SLR information with GRACE solutions in post-processing.

Abstract

Tidal interactions play a key role in the dynamics and evolution of icy worlds. The intense tectonic activity of Europa and the eruption activity on Enceladus are clear examples of the manifestation of tidal deformation and associated dissipation. While tidal heating has long been recognized as a major driver in the activity of these icy worlds, the mechanism controlling how tidal forces deform the different internal layers and produce heat by tidal friction still remains poorly constrained. As tidal forcing varies with orbital characteristics (distance to the central planet, eccentricity, obliquity), the contribution of tidal heating to the internal heat budget can strongly change over geological timescales. In some circumstances, the tidally-produced heat can result in internal melting and surface activity taking various forms. Even in the absence of significant heat production, tidal deformation can be used to probe the interior structure, the tidal response of icy moons being strongly sensitive to their hydrosphere structure. In the present paper, we review the methods to compute tidal deformation and dissipation in the different layers composing icy worlds. After summarizing the main principle of tidal deformation and the different rheological models used to model visco-elastic tidal response, we describe the dissipation processes expected in rock-dominated cores, subsurface oceans and icy shells and highlight the potential effects of tidal heating in terms of thermal evolution and activity. We finally anticipate how data collected by future missions to Jupiter’s and Saturn’s moons could be used to constrain their tidal response and the consequences for past and present activities.

McGill University researchers have discovered that changes in clouds are slightly mitigating global warming. While greenhouse gases continue to cause temperatures to rise, a reduction in low-cloud cover over land has brought about a modest reduction of the amount of heat being trapped close to ground level.