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| Titel |
Statistical analysis on spatial correlation of ionospheric day-to-day variability by using GPS and Incoherent Scatter Radar observations |
| VerfasserIn |
X. Yue, W. Wan, L. Liu, T. Mao |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 25, no. 8 ; Nr. 25, no. 8 (2007-08-29), S.1815-1825 |
| Datensatznummer |
250015898
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| Publikation (Nr.) |
 copernicus.org/angeo-25-1815-2007.pdf |
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| Zusammenfassung |
| In this paper, the spatial correlations of ionospheric day-to-day
variability are investigated by statistical analysis on GPS and Incoherent
Scatter Radar observations. The meridional correlations show significant
(>0.8) correlations in the latitudinal blocks of about 6 degrees size on
average. Relative larger correlations of TEC's day-to-day variabilities can
be found between magnetic conjugate points, which may be due to the
geomagnetic conjugacy of several factors for the ionospheric day-to-day
variability. The correlation coefficients between geomagnetic conjugate
points have an obvious decrease around the sunrise and sunset time at the upper
latitude (60°) and their values are bigger between the winter and summer
hemisphere than between the spring and autumn hemisphere. The time delay of
sunrise (sunset) between magnetic conjugate points with a high dip latitude is
a probable reason. Obvious latitude and local time variations of meridional
correlation distance, latitude variations of zonal correlation distance, and
altitude and local time variations of vertical correlation distance are
detected. Furthermore, there are evident seasonal variations of meridional
correlation distance at higher latitudes in the Northern Hemisphere and local
time variations of zonal correlation distance at higher latitudes in the
Southern Hemisphere. These variations can generally be interpreted by the
variations of controlling factors, which may have different spatial scales.
The influences of the occurrence of ionospheric storms could not be ignored.
Further modeling and data analysis are needed to address this problem. We
suggest that our results are useful in the specific modeling/forecasting of
ionospheric variability and the constructing of a background covariance matrix
in ionospheric data assimilation. |
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