Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2609.37486

An autonomous approach to model daytime behavior of sub-ionospheric VLF signals over short and medium propagation paths in India

Sayak Chakraborty·Tamal Basak·Sourav Palit·Sandip K. Chakrabarti
View original source ↗Read source document ↗Export metadata ↓

Abstract

We present an autonomous model to simulate the daytime variation of sub-ionospheric Very Low Frequency (VLF) signal amplitude, beginning with the computation of the D-region electron density by numerically solving the electron continuity equation (ECE). From the resulting altitude-dependent electron density profile (Ne), we extract Wait's ionospheric parameters (h' and beta) using a log-linear fitting method. The study focuses on two VLF propagation paths (one short and one medium in length) in India, originating from the VTX (18.2 kHz) transmitter. The model employs the Long Wave Propagation Capability (LWPC) framework to reproduce the daytime VLF signal amplitude profile. It accurately captures the daytime variations observed at the Bengaluru (BAN) station, where the ground-wave component is dominant, as well as at Khukurdaha, WB (KHK). A quantitative comparison between the simulated (Asim) and observed (Aobs) amplitudes shows good agreement, supporting the physical consistency and potential predictive capability of the proposed approach.

Explore related subjects

physics.space-phastro-ph.EPastro-ph.SR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sayak Chakraborty, Tamal Basak, Sourav Palit, Sandip K. Chakrabarti. 2026-09-27. An autonomous approach to model daytime behavior of sub-ionospheric VLF signals over short and medium propagation paths in India. https://doi.org/10.1007/s10509-026-04541-z

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

P2D - A Two-Dimensional Multi-Spacecraft Solar Wind Persistence Model

The background solar wind is a key component in space weather forecasting, as it contains geoeffective high-speed streams and provides the medium through which coronal mass ejections propagate and evolve in interplanetary space. Due to the solar rotation and the slow evolution of large-scale solar wind structures, solar wind properties exhibit an autocorrelation with a period of roughly 27 days, particularly at solar minimum. We made use of this property to develop a solar wind persistence model with input from multiple spacecraft (Solar Orbiter, Parker Solar Probe, STEREO-A, STEREO-B and the OMNI database). The model ballistically propagates in-situ data from the position of their measurement radially away from the Sun, as well as longitudinally with the solar rotation rate, producing 2D maps of solar wind parameters. These can be extracted at any point in the heliosphere for a solar wind reconstruction. From Earth's perspective, the reconstruction performs with an MAE of 65.41 km/s and 3.51/cm^3 for speed and density, respectively. During high-speed streams, the peak hit rate is 50% and 48% for speed and density. It performs best during times when there are spacecraft located between Earth and Lagrange point L5. During these times, the mean absolute error of the predicted solar wind speed decreases by roughly 35% in comparison to the benchmark 27-day persistence model. Therefore, future L5 missions like Vigil are expected to provide a robust basis for reliable persistence forecasts.

physics.space-ph↗
arXiv2026

Spectral Properties of Solar Wind Charge Exchange from Earth's Magnetospheric Boundaries: MHD and Test Particle Simulations

The Solar Wind Charge Exchange (SWCX) mechanism, where X-rays can be generated through interactions between heavy, highly charged solar wind ions and neutral atoms, offers an opportunity to observe the large-scale transfers of energy and momentum through the Sun-Earth system. In this study, we simulate SWCX signatures from Earth's outer boundaries using Gorgon global magnetohydrodynamic (MHD) simulations combined with kinetic particle-based simulations which we call the X-ray Imaging of the Magnetosphere (XIM) framework. The XIM-predicted emissivities agree with the predictions of the MHD model, producing enhanced emissions from the magnetosheath and cusp regions, but several differences are apparent. Compared with MHD, XIM shows enhanced structuring in the magnetosheath and notable enhanced emissions along the magnetopause associated with betatron acceleration. The results also evidence species-specific spatial variations, which are shown to vary compared to anticipated relative abundances in the solar wind and ion-specific properties. These simulations provide new insights into the underlying dynamics of SWCX at the Earth's outer boundaries, which can be used to understand what might be observed using X-ray observatories in space, such as the recently launched SMILE mission.

physics.space-ph↗
arXiv2026

Temporal Correlation between Ionospheric Storm-Enhanced Density Plume and Plasmaspheric Plume Occurrence

We present a statistical evidence of a temporal correlation between ionospheric storm-enhanced density (SED) and plasmaspheric plumes during magnetic storms. We identified SED plumes in 75 storms between 2010-2024 with sufficient total electron content (TEC) coverage. We also identified plasmaspheric plumes during these storms using a plasmapause asymmetry (PPA) index derived from the machine-learning-based DEN3D model. We found that all SED plumes coincided with plasmaspheric plumes. The start and end times of both phenomena exhibit near-zero lag within a half-hour delay, confirming their synchronized evolution. For the first time, superposed epoch analyses reveal that plume onsets align with solar wind driving and geomagnetic activity, including peaks in the electric field, coupling function, auroral electrojet indices, and the asymmetric ring current index, all of which facilitate plume formation. This work provides timely new insights into magnetosphere-ionosphere coupling processes and demonstrates the utility of machine-learning-based diagnostics for space physics/weather.

physics.space-ph↗