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Fossil algae show a lake once existed on Lesotho's Mafadi summit, but it vanished about 150 years ago

Phys.org: Earth science - Sat, 07/27/2024 - 10:10

Lesotho is a small, land-locked, mountainous country located in the middle of South Africa. Its Eastern Lesotho Highlands are often referred to as the region's "water tower" because they receive some of the highest rainfall amounts in southern Africa, providing water to South Africa and electricity to Lesotho through the Lesotho Highlands Water Project.

Improving multiple LEO combination for SLR-based geodetic parameters determination using variance component estimation

Journal of Geodesy - Sat, 07/27/2024 - 00:00

Abstract

The combination of satellite laser ranging (SLR) observations to various low earth orbit (LEO) satellites can enhance the accuracy and robustness of SLR-derived geodetic parameters, benefiting the realization of the International terrestrial reference frames. Observation stochastic models play a critical role in the integrated processing of SLR observations to multiple LEO satellites. The consideration of precision in heterogeneous SLR observations from various satellites is essential. In this study, we aim to improve the combination of multi-LEO SLR observations for geodetic parameters determination by optimizing the stochastic model using variance component estimation (VCE). We perform weekly estimates of the geodetic parameters, including station coordinates, Earth rotation parameters, and geocenter coordinates (GCC), using three years of SLR observations to seven LEO satellites at different orbits. The satellite-dependent, station-dependent, and satellite–station-dependent variance components are separately estimated through VCE processing to refine the stochastic models. Given the fact that the precision of SLR observations significantly differs in satellites and stations, the multiple LEO combination can be significantly improved with the implementation of VCE. Satellite–station-pair-dependent variance components are more suitable to the SLR VCE and the accuracy of station coordinates, pole coordinates, and length of day can be averagely improved by 8.4, 22.6, and 21.9%, respectively, compared to the equal-weight solution. Our result also indicates that the observation insufficiency for some stations may result in an unreliable VCE estimation, and eventually leads to an accuracy degradation for station coordinates. To overcome this deficiency, we adopt the variance components derived from the monthly solutions to build the stochastic model in the weekly solutions. The application of monthly weights can effectively mitigate the accuracy deterioration of station coordinates, improving the repeatability of the station coordinates by 15.9, 14.6, and 9.2% with respect to the equal-weight solution in E, N, and U components. The global geodetic parameters also benefit from this processing. The import of monthly weight decreases the outliers in the GCC series, especially in the X and Y components.

Correction: Observations and positioning quality of low-cost GNSS receivers: a review

GPS Solutions - Sat, 07/27/2024 - 00:00

Real-time cloud computing of GNSS measurements from smartphones and mobile devices for enhanced positioning and navigation

GPS Solutions - Sat, 07/27/2024 - 00:00

Abstract

In recent years, Global Navigation Satellite Systems (GNSSs) have become integral to our daily lives because of their precise positioning and navigation capabilities. Widespread use of smartphones equipped with GNSS receivers results in the generation of a huge amount of positioning data. Therefore, real-time cloud computing has emerged as a promising approach to effectively leverage this wealth of location information. In this study, we developed an Android app that captures raw GNSS data from smartphones, leverages cloud computing resources, calculates the position of the device, and returns the computed solution to the user. Integration of cloud-based processing not only conserves the device resources but also enables real-time position calculation, paving the way for enhanced location-based applications and services.

Gnssrefl: an open source software package in python for GNSS interferometric reflectometry applications

GPS Solutions - Sat, 07/27/2024 - 00:00

Abstract

An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.

A rapid analysis of aftershock processes after a moderate magnitude earthquake with ML-methods

Geophysical Journal International - Sat, 07/27/2024 - 00:00

SummaryModerate magnitude earthquakes and seismic sequences frequently develop on fault systems, but whether they are linked to future major ruptures is always ambiguous. In this study, we investigated a seismic sequence that has developed within a portion of the stretching region of the Apennines in Italy where moderate to large earthquakes are likely to occur. We captured a total of 2 039 aftershocks of the September 18, 2023, Mw4.9 earthquake occurred during the first week, by using ML-based algorithms. Aftershocks align on two 5-7 km long parallel faults, from a length that exceeds what is expected from the mainshock magnitude. The segments are ramping at about 6 km depth on closely spaced N100 striking 70 N dipping planes, at a distance of some kilometers from the mainshock hypocenter. Our results indicate that even moderate magnitude events trigger seismicity on a spread set of fault segments around the mainshock hypocenter, revealing processes of interaction within the crustal layer. The possibility that larger earthquakes develop during seismicity spread is favored by pore pressure diffusion, in relation with the closeness to criticality of fault segments. Based on the very rapid activation of seismicity on the entire system and a back-front signal from the hypocenter of the main event, we infer that fluid pressure, initially high within the crustal layer, rapidly dropped after the mainshock. Our study reinforces the importance of timely extracting information on fault geometry and seismicity distribution on faults. ML-based methods represent a viable tool for semi-real-time application, yielding constraints on short-time forecasts.

Low-Rank Approximation Reconstruction of Five-Dimensional Seismic Data

Surveys in Geophysics - Sat, 07/27/2024 - 00:00

Abstract

Low-rank approximation has emerged as a promising technique for recovering five-dimensional (5D) seismic data, yet the quest for higher accuracy and stronger rank robustness remains a critical pursuit. We introduce a low-rank approximation method by leveraging the complete graph tensor network (CGTN) decomposition and the learnable transform (LT), referred to as the LRA-LTCGTN method, to simultaneously denoise and reconstruct 5D seismic data. In the LRA-LTCGTN framework, the LT is employed to project the frequency tensor of the original 5D data onto a small-scale latent space. Subsequently, the CGTN decomposition is executed on this latent space. We adopt the proximal alternating minimization algorithm to optimize each variable. Both 5D synthetic data and field data examples indicate that the LRA-LTCGTN method exhibits notable advantages and superior efficiency compared to the damped rank-reduction (DRR), parallel matrix factorization (PMF), and LRA-CGTN methods. Moreover, a sensitivity analysis underscores the remarkably stronger robustness of the LRA-LTCGTN method in terms of rank without any optimization procedure with respect to rank, compared to the LRA-CGTN method.

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