With the rapid advancement of artificial intelligence, deep-learning-based inversion frameworks are increasingly being adopted to tackle the challenges associated with surface-wave dispersion curve (DC) inversion. Compared with classical model-driven methods, the deep-learning-based inversion is known for its higher efficiency and independence from the initial model. Existing researches, however, have

Multigrid (MG) methods solve large linear equations on fine grids by projecting them onto progressively coarser grids, on which the problem can be solved more cheaply. They have become among the most effective and prospective solvers for large linear systems. However, due to the abundant null solution space and the inclusion of the air layer, traditional MG methods struggle to converge in three-dimensional

To investigate physical links between the Earth atmosphere and ionosphere, we present data of the medium-scale atmospheric gravity waves (AGWs, periods 25–100 min) observed at auroral latitudes. The AGWs at 80–100 km altitude were inferred from the wind data of the Nordic meteor radar Cluster with spatial/height/time resolution 90 km/5 km/10 min respectively. At the same time, medium-scale traveling

The Active Plasma and E-field Sounders (APES) mission concept aims to resolve orders-of-magnitude errors in modeling transionospheric radio propagation through the midlatitude trough, and to determine which physical mechanism(s) are responsible for generating plasma irregularities there. APES will observe ionospheric electron density profiles and signals from ground transmitters along its orbital track

Many components of the Earth system feature self-reinforcing feedback processes that can potentially scale up a small initial change to a fundamental state change of the underlying system in a sometimes abrupt or irreversible manner beyond a critical threshold. Such tipping points can be found across a wide range of spatial and temporal scales and are expressed in very different observable variables

A 6-year cycle has long been recognized to influence the Earth’s rotation, the internal magnetic field and motions in the fluid Earth’s core. Recent observations have revealed that a 6-year cycle also affects the angular momentum of the atmosphere and several climatic parameters, including global mean sea level rise, precipitation, land hydrology, Arctic surface temperature, ocean heat content and

The risk of earthquakes and their effects on both nature and infrastructure in seismically active regions of India require adaptable and scalable earthquake early warning (EEW) systems. Developing a robust EEW system is crucial to mitigate earthquake risks in the region, but it is a challenging task. Various institutes have attempted to develop EEW systems using different methods. Still, there is no

Physics-informed neural networks (PINNs) provide a flexible and effective alternative for estimating seismic wavefield solutions due to their typical mesh-free and unsupervised features. However, their accuracy and training cost restrict their applicability. To address these issues, we propose a novel initialization for PINNs based on meta-learning to enhance their performance. In our framework, we

In this paper, we review the theoretical studies of the electromagnetic and other non-seismic phenomena accompanying earthquakes. This field of geophysical research is at the interception of several sciences: electrodynamics, solid-state physics, fracture mechanics, seismology, acoustic-gravity waves, magnetohydrodynamics, ionospheric plasma, etc. In order to make physics of these phenomena as transparent

Previous surveys using the remote sensing (RS) method revealed significant structures in the area of the Western Carpathians. It has not yet been possible to verify and explain the results of these surveys, even though all the phenomena are regional in nature and show many morphological features that clearly indicate recent activity and deformations, including current earthquake foci. The aim of the

Gravity forward modeling provides important high-resolution information for the development of global gravity models, and can also be applied in many studies, e.g., topographic/isostatic effects computation and Bouguer anomaly maps compilation. In this paper, we present efficient spectral forward modeling approaches in the spheroidal harmonic domain, based on a single layer with constant density or

Seismic and electromagnetic (EM) imaging are essential tools for characterizing velocity and conductivity. However, the separate inversion of seismic and EM data is challenging due to the noisy measurements, inadequate data collection, and reliance on prior information, consequently resulting in uncertainty and ambiguity of the solutions. Moreover, the two methods are different in sensitivity and spatial

This review article provides a synthesis and perspective on how weather and climate extreme events can play a role in influencing tipping elements and triggering tipping points in the Earth System. An example of a potential critical global tipping point, induced by climate extremes in an increasingly warmer climate, is Amazon rainforest dieback that could be driven by regional increases in droughts

We revisit the derivation of the linear relationships connecting the variations of the Earth’s length-of-day (more specifically its mass term ΔLODmass), polar oblateness (ΔJ2), and total moment of inertia (ΔT) caused by geophysical mass transports. The three integral quantities are expressed as inner products of the perturbation, either in the form of density change in the Eulerian description or deformation