Search for: All records

Data-driven approaches to identify geophysical signals have proven beneficial in high dimensional environments where model-driven methods fall short. GNSS offers a source of unsaturated ground motion observations that are the data currency of ground motion forecasting and rapid seismic hazard assessment and alerting. However, these GNSS-sourced signals are superposed onto hardware-, location- and time-dependent noise signatures influenced by the Earth’s atmosphere, low-cost or spaceborne oscillators, and complex radio frequency environments. Eschewing heuristic or physics based models for a data-driven approach in this context is a step forward in autonomous signal discrimination. However, the performance of a data-driven approach depends upon substantial representative samples with accurate classifications, and more complex algorithm architectures for deeper scientific insights compound this need. The existing catalogs of high-rate (≥1Hz) GNSS ground motions are relatively limited. In this work, we model and evaluate the probabilistic noise of GNSS velocity measurements over a hemispheric network. We generate stochastic noise time series to augment transferred low-noise strong motion signals from within 70 kilometers of strong events (≥ MW 5.0) from an existing inertial catalog. We leverage known signal and noise information to assess feature extraction strategies and quantify augmentation benefits. We find a classifier model trained on this expanded pseudo-synthetic catalog improves generalization compared to a model trained solely on a real-GNSS velocity catalog, and offers a framework for future enhanced data driven approaches.

 

Abstract The Antarctic and Arctic regions are Earth's open windows to outer space. They provide unique opportunities for investigating the troposphere–thermosphere–ionosphere–plasmasphere system at high latitudes, which is not as well understood as the mid- and low-latitude regions mainly due to the paucity of experimental observations. In addition, different neutral and ionised atmospheric layers at high latitudes are much more variable compared to lower latitudes, and their variability is due to mechanisms not yet fully understood. Fortunately, in this new millennium the observing infrastructure in Antarctica and the Arctic has been growing, thus providing scientists with new opportunities to advance our knowledge on the polar atmosphere and geospace. This review shows that it is of paramount importance to perform integrated, multi-disciplinary research, making use of long-term multi-instrument observations combined with ad hoc measurement campaigns to improve our capability of investigating atmospheric dynamics in the polar regions from the troposphere up to the plasmasphere, as well as the coupling between atmospheric layers. Starting from the state of the art of understanding the polar atmosphere, our survey outlines the roadmap for enhancing scientific investigation of its physical mechanisms and dynamics through the full exploitation of the available infrastructures for radio-based environmental monitoring. 

This article presents the results of a week of observations around the 2 July 2019, total Chilean eclipse. The eclipse occurred between 19:22 and 21:46 UTC, with complete sun disc obscuration at 20:38–20:40 UTC (16:38–16:40 LT) over the Andes Lidar Observatory (ALO) at (30.3°S, 70.7°W). Observations were carried out using ALO instrumentation with the goal to observe possible eclipse‐induced effects on the mesosphere and lower thermosphere region (MLT; 75–105 km altitude). To complement our data set, we have also utilized TIMED/SABER temperatures and ionosonde electron density measurements taken at the University of La Serena's Juan Soldado Observatory. Observed events include an unusual fast, bow‐shaped gravity wave structure in airglow images, mesosphere temperature mapper brightness as well as in lidar temperature with 150 km horizontal wavelength 24 min observed period, and vertical wavelength of 25 km. Also, a strong zonal wind shear above 100 km in meteor radar scans as well as the occurrence of a sporadic E layer around 100 km from ionosonde measurements. Finally, variations in temperature and density and the presence of a descending sporadic sodium layer near 98 km were seen in lidar data. We discuss the effects of the eclipse in the MLT, which can shed light on a sparse set of measurements during this type of event. Our results point out several effects of eclipse‐associated changes in the atmosphere below and above but not directly within the MLT.

 

Data from a network of high‐frequency (HF) beacons deployed in Peru are used to estimate the regional ionospheric electron density in a volume. Pseudorange, accumulated carrier phase, and signal power measurements for each of the 36 ray paths provided by the network at a 1 min cadence are incorporated in the estimates. Additional data from the Jicamarca incoherent scatter radar, the Jicamarca sounder, and GPS receivers can also be incorporated. The electron density model is estimated as the solution to a global optimization problem that uses ray tracing in the forward model. The electron density is parametrized in terms of B‐splines in the horizontal direction and generalized Chapman functions or related functions in the vertical. Variational sensitivity analysis has been added to the method to allow for the utilization of the signal power observable which gives additional information about the morphology of the bottomside F region as well as absorption including absorption in the D and E regions. The goal of the effort is to provide contextual information for improving numerical forecasts of plasma interchange instabilities in the postsunset F region ionosphere associated with equatorial spread F (ESF). Data from two ESF campaigns are presented. In one experiment, the HF data revealed the presence of a large‐scale bottomside deformation that seems to have led to instability under otherwise inauspicious conditions. In another experiment, gradual variations in HF signal power were found to be related to the varying shape of the bottomside F layer.