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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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 |
work_keys_str_mv |
AT ertalaat spatialandtemporalvariationoftotalelectroncontentasrevealedbyprincipalcomponentanalysis AT ertalaat spatialandtemporalvariationoftotalelectroncontentasrevealedbyprincipalcomponentanalysis AT xzhu spatialandtemporalvariationoftotalelectroncontentasrevealedbyprincipalcomponentanalysis |
_version_ |
1725588103724269568 |