Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

Abstract A systems science approach based on canonical correlation analysis (CCA) is applied as a new, behavioral way to validate global geospace models. The biggest novelty of the technique is that it validates models at a system level, whereby a side‐by‐side comparison is performed of CCA applied to a 30‐day observational and the corresponding simulation data sets comprising quiet, moderate and active times. The simulation used the Multiscale Atmosphere‐Geospace Environment (MAGE) model. It is shown that (a) CCA must be combined with sensitivity analysis to be effective, (b) the MAGE model generally reproduces the observed behavior (more so for quieter time intervals), quantified by the intercorrelations between different variables and (c) the technique identifies the SuperMAG SML index as a quantity for which refinements of the model are needed.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-10-07
DOI
https://doi.org/10.1029/2025gl115589
Citations
1
Primary Topic
Geomagnetism and Paleomagnetism Studies
Type
article
Field-Weighted Citation Impact
0.81

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Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

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Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

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article en
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Abstract

Abstract A systems science approach based on canonical correlation analysis (CCA) is applied as a new, behavioral way to validate global geospace models. The biggest novelty of the technique is that it validates models at a system level, whereby a side‐by‐side comparison is performed of CCA applied to a 30‐day observational and the corresponding simulation data sets comprising quiet, moderate and active times. The simulation used the Multiscale Atmosphere‐Geospace Environment (MAGE) model. It is shown that (a) CCA must be combined with sensitivity analysis to be effective, (b) the MAGE model generally reproduces the observed behavior (more so for quieter time intervals), quantified by the intercorrelations between different variables and (c) the technique identifies the SuperMAG SML index as a quantity for which refinements of the model are needed.

Geophysical Research LettersVol. 52(19)
NSF National Center for Atmospheric Research (US), NSF NCAR High Altitude Observatory (US), Space Science Institute (US), Los Alamos National Laboratory (US), University of New Hampshire (US), Johns Hopkins University Applied Physics Laboratory (US), University College London (GB)
National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Johns Hopkins University, Nuclear Safety and Security Commission, National Nuclear Security Administration, Laboratory Directed Research and Development, Los Alamos National Laboratory
Openalex Percentile: Top 23%
Geomagnetism and Paleomagnetism Studies
0.81
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