Spatial and temporal variation of total electron content as revealed by principal component analysis

Eleven years of global total electron content (TEC) data derived from the assimilated thermosphere–ionosphere electrodynamics general circulation model are analyzed using empirical orthogonal function (EOF) decomposition and the corresponding principal component analysis (PCA) technique. For the...

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Main Authors: E. R. Talaat, X. Zhu
Format: Article
Language:English
Published: Copernicus Publications 2016-11-01
Series:Annales Geophysicae
Online Access:https://www.ann-geophys.net/34/1109/2016/angeo-34-1109-2016.pdf
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spelling doaj-74a72fd019b840d9ae81b7c51616210d2020-11-24T23:16:15ZengCopernicus PublicationsAnnales Geophysicae0992-76891432-05762016-11-01341109111710.5194/angeo-34-1109-2016Spatial and temporal variation of total electron content as revealed by principal component analysisE. R. Talaat0E. R. Talaat1X. Zhu2The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723, USAnow at: Heliophysics Division, NASA Headquarters, Washington, D.C. 20546, USAThe Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723, USAEleven years of global total electron content (TEC) data derived from the assimilated thermosphere–ionosphere electrodynamics general circulation model are analyzed using empirical orthogonal function (EOF) decomposition and the corresponding principal component analysis (PCA) technique. For the daily averaged TEC field, the first EOF explains more than 89 % and the first four EOFs explain more than 98 % of the total variance of the TEC field, indicating an effective data compression and clear separation of different physical processes. The effectiveness of the PCA technique for TEC is nearly insensitive to the horizontal resolution and the length of the data records. When the PCA is applied to global TEC including local-time variations, the rich spatial and temporal variations of field can be represented by the first three EOFs that explain 88 % of the total variance. The spectral analysis of the time series of the EOF coefficients reveals how different mechanisms such as solar flux variation, change in the orbital declination, nonlinear mode coupling and geomagnetic activity are separated and expressed in different EOFs. This work demonstrates the usefulness of using the PCA technique to assimilate and monitor the global TEC field.https://www.ann-geophys.net/34/1109/2016/angeo-34-1109-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author E. R. Talaat
E. R. Talaat
X. Zhu
spellingShingle E. R. Talaat
E. R. Talaat
X. Zhu
Spatial and temporal variation of total electron content as revealed by principal component analysis
Annales Geophysicae
author_facet E. R. Talaat
E. R. Talaat
X. Zhu
author_sort E. R. Talaat
title Spatial and temporal variation of total electron content as revealed by principal component analysis
title_short Spatial and temporal variation of total electron content as revealed by principal component analysis
title_full Spatial and temporal variation of total electron content as revealed by principal component analysis
title_fullStr Spatial and temporal variation of total electron content as revealed by principal component analysis
title_full_unstemmed Spatial and temporal variation of total electron content as revealed by principal component analysis
title_sort spatial and temporal variation of total electron content as revealed by principal component analysis
publisher Copernicus Publications
series Annales Geophysicae
issn 0992-7689
1432-0576
publishDate 2016-11-01
description Eleven years of global total electron content (TEC) data derived from the assimilated thermosphere–ionosphere electrodynamics general circulation model are analyzed using empirical orthogonal function (EOF) decomposition and the corresponding principal component analysis (PCA) technique. For the daily averaged TEC field, the first EOF explains more than 89 % and the first four EOFs explain more than 98 % of the total variance of the TEC field, indicating an effective data compression and clear separation of different physical processes. The effectiveness of the PCA technique for TEC is nearly insensitive to the horizontal resolution and the length of the data records. When the PCA is applied to global TEC including local-time variations, the rich spatial and temporal variations of field can be represented by the first three EOFs that explain 88 % of the total variance. The spectral analysis of the time series of the EOF coefficients reveals how different mechanisms such as solar flux variation, change in the orbital declination, nonlinear mode coupling and geomagnetic activity are separated and expressed in different EOFs. This work demonstrates the usefulness of using the PCA technique to assimilate and monitor the global TEC field.
url https://www.ann-geophys.net/34/1109/2016/angeo-34-1109-2016.pdf
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