What visibility-graph curvature measures in Forbush decreases: a calibration on the two largest events of solar cycle 25
Abstract
Discrete curvatures of visibility graphs are increasingly used as descriptors of geophysical time series, but their response to a transient has rarely been calibrated against the simplest properties of that transient. We carry out this calibration for the nodal Forman--Ricci curvature ℱ of natural visibility graphs applied to neutron-monitor records of the Gannon storm (2024 May 10--11) and the 2025 June 1 Forbush decrease (FD), the two largest FDs of solar cycle 25, using 30-min NMDB data from six NM64 stations (Rc ≃ 0--$7$~GV), i.e.\ twelve station--event series. Curvature collapses at FD onset in every series (Cliff's δ= 0.63--$1.0$), but a 6-h running standard deviation separates onset from quiet time more strongly (mean δ= 0.96 vs $0.89$; mean block-permutation displacement z = −27 vs −14). Injecting synthetic decreases into the real pre-event records of each station shows that the curvature extreme follows |ℱmin| ∝ (A/σ)0.50 (R2 = 0.88), where A is the FD amplitude and σ the station's quiet-time noise, and is independent of the duration of the main phase (exponent $0.006$ over 3--36~h). With A, σ and the main-phase duration of each series as the only inputs, the calibration predicts the twelve observed extremes with standardized residuals of mean −0.26 and standard deviation $0.94$, and the observed extremes correlate with A/σ at Spearman ρ= 0.95. Within the precision allowed by these data, nodal Forman--Ricci curvature of the whole-series visibility graph carries no information about these FDs beyond their amplitude relative to station noise; in particular, it does not distinguish the single-step Gannon decrease from the two-step June 2025 decrease.
Related
- Comparison of observed and theoretically calculated amplitudes of Forbush effects for events associated with the arrival of a shock wave
- IViS: Interferometric Visibility-domain inversion Software. A GPU-accelerated Python framework for joint deconvolution with ASKAP
- Denoising Interferometric Observations Using Visibility-Informed Neural Networks
- Options for Compression of radio interferometry data: lossy compression of visibilities and lossless compression of uv-visibility grids for the MHONGOOSE survey
- Aurora Hunter: A Two-Stage Framework for Probabilistic Visibility Forecasting
BibTeX
@misc{sierraporta2026what,
title = {{What visibility-graph curvature measures in Forbush decreases: a calibration on the two largest events of solar cycle 25}},
author = {D. Sierra-Porta},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2607.13236},
eprint = {2607.13236},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2607.13236},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - What visibility-graph curvature measures in Forbush decreases: a calibration on the two largest events of solar cycle 25
AU - D. Sierra-Porta
PY - 2026
DA - 2026/10/23
PB - arXiv
DO - 10.48550/arxiv.2607.13236
UR - https://arxiv.org/abs/2607.13236
AB - Discrete curvatures of visibility graphs are increasingly used as descriptors of geophysical time series, but their response to a transient has rarely been calibrated against the simplest properties of that transient. We carry out this calibration for the nodal Forman--Ricci curvature ℱ of natural visibility graphs applied to neutron-monitor records of the Gannon storm (2024 May 10--11) and the 2025 June 1 Forbush decrease (FD), the two largest FDs of solar cycle 25, using 30-min NMDB data from six NM64 stations (R_c ≃ 0--$7$~GV), i.e.\ twelve station--event series. Curvature collapses at FD onset in every series (Cliff's δ= 0.63--$1.0$), but a 6-h running standard deviation separates onset from quiet time more strongly (mean δ= 0.96 vs $0.89$; mean block-permutation displacement z = −27 vs −14). Injecting synthetic decreases into the real pre-event records of each station shows that the curvature extreme follows |ℱ_min| ∝ (A/σ)^0.50 (R^2 = 0.88), where A is the FD amplitude and σ the station's quiet-time noise, and is independent of the duration of the main phase (exponent $0.006$ over 3--36~h). With A, σ and the main-phase duration of each series as the only inputs, the calibration predicts the twelve observed extremes with standardized residuals of mean −0.26 and standard deviation $0.94$, and the observed extremes correlate with A/σ at Spearman ρ= 0.95. Within the precision allowed by these data, nodal Forman--Ricci curvature of the whole-series visibility graph carries no information about these FDs beyond their amplitude relative to station noise; in particular, it does not distinguish the single-step Gannon decrease from the two-step June 2025 decrease.
ER -