Investigation of phase and power fluctuation events using Rytov method and the forward propagation model

Ionospheric density irregularities cause fluctuations in transionospheric satellite signals, known as “scintillation”. While scintillation degrades the performance of navigation satellites, such as the Global Positioning System (GPS), it also serves as a diagnostic tool for studying the underlying plasma processes. In this study, we characterize high-latitude ionospheric structuring and its impact on radio signals using a 3D propagation model, the “Satellite-beacon Ionospheric-scintillation Global Model of the upper Atmosphere” (SIGMA), in conjunction with GPS observations and an analytical model. Establishing a modeling framework for defining the irregularity parameters, including spatial extent, spectral index, axial ratios, density fluctuations, layer height, drift velocity, and thickness, is essential for providing insights into scintillation modeling. We use the Rytov method, a well-known analytical 2D model for estimating irregularity parameters from observed log-power and phase spectra, which is particularly useful in the absence of auxiliary observations. Observations from GPS array receivers in Poker Flat, Alaska, are used to examine the simultaneous occurrence of phase and power fluctuations. These occurrences are rare, as only a few such events were detected in observations from 2014 to 2019. These reveal both large-scale, refractive fluctuations and smaller-scale, diffractive features embedded within them, highlighting the multiscale nature of plasma structuring. Initializing SIGMA with Rytov-derived parameters shows a good agreement between the simulated and observed power spectral densities, with goodness-of-fit metric <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>χ</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>′</mml:mo> </mml:mrow> </mml:msup> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> close to 1. This is observed with power fluctuations, particularly when shorter temporal segments are used for the inversion. A spectral break within the diffractive regime suggests the presence of multiscale structuring. Overall, our findings support the concept that turbulent energy cascading from large-scale structures, likely driven by gradient-drift and/or Kelvin–Helmholtz instabilities, plays a crucial role in generating scintillation-inducing irregularities.

Authors

Institutions

Publication Details

Journal
Frontiers in Astronomy and Space Sciences
Published
2025-11-05
DOI
https://doi.org/10.3389/fspas.2025.1653357
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigation of phase and power fluctuation events using Rytov method and the forward propagation model

M. D. Zettergren, Seebany Datta‐Barua, G. S. Bust, K. Deshpande et al.
Frontiers in Astronomy and Space Sciences
Ionosphere and magnetosphere dynamics
article

Investigation of phase and power fluctuation events using Rytov method and the forward propagation model

M. D. Zettergren, Seebany Datta‐Barua, G. S. Bust, K. Deshpande, Pralay Raj Vaggu
article en

Abstract

Ionospheric density irregularities cause fluctuations in transionospheric satellite signals, known as “scintillation”. While scintillation degrades the performance of navigation satellites, such as the Global Positioning System (GPS), it also serves as a diagnostic tool for studying the underlying plasma processes. In this study, we characterize high-latitude ionospheric structuring and its impact on radio signals using a 3D propagation model, the “Satellite-beacon Ionospheric-scintillation Global Model of the upper Atmosphere” (SIGMA), in conjunction with GPS observations and an analytical model. Establishing a modeling framework for defining the irregularity parameters, including spatial extent, spectral index, axial ratios, density fluctuations, layer height, drift velocity, and thickness, is essential for providing insights into scintillation modeling. We use the Rytov method, a well-known analytical 2D model for estimating irregularity parameters from observed log-power and phase spectra, which is particularly useful in the absence of auxiliary observations. Observations from GPS array receivers in Poker Flat, Alaska, are used to examine the simultaneous occurrence of phase and power fluctuations. These occurrences are rare, as only a few such events were detected in observations from 2014 to 2019. These reveal both large-scale, refractive fluctuations and smaller-scale, diffractive features embedded within them, highlighting the multiscale nature of plasma structuring. Initializing SIGMA with Rytov-derived parameters shows a good agreement between the simulated and observed power spectral densities, with goodness-of-fit metric <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>χ</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>′</mml:mo> </mml:mrow> </mml:msup> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> close to 1. This is observed with power fluctuations, particularly when shorter temporal segments are used for the inversion. A spectral break within the diffractive regime suggests the presence of multiscale structuring. Overall, our findings support the concept that turbulent energy cascading from large-scale structures, likely driven by gradient-drift and/or Kelvin–Helmholtz instabilities, plays a crucial role in generating scintillation-inducing irregularities.

Frontiers in Astronomy and Space SciencesVol. 12
Illinois Institute of Technology (US), Johns Hopkins University Applied Physics Laboratory (US), Embry–Riddle Aeronautical University (US)
National Science Foundation, National Aeronautics and Space Administration, Nuclear Safety and Security Commission, Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
Openalex Percentile: Top 77%
Ionosphere and magnetosphere dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.