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| Titel |
Anomalous nighttime electron temperatures over Millstone Hill: a statistical study |
| VerfasserIn |
V. V. Lobzin, A. V. Pavlov |
| 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 ; 22, no. 2 ; Nr. 22, no. 2 (2004-01-01), S.431-439 |
| Datensatznummer |
250014773
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| Publikation (Nr.) |
 copernicus.org/angeo-22-431-2004.pdf |
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| Zusammenfassung |
A statistical study of anomalous nighttime electron temperature enhancements, NETEs, observed on 336
nights during Millstone Hill radar measurements on 730 nights from 1976 to 2001 is carried out. NETEs are most frequent
in winter and in autumn. The NETE occurrence has a maximum probability in February and a minimum probability
in July. The asymmetry between spring and autumn NETE occurrences is found for NETEs, which are observed during
geomagnetially quiet time periods. The calculated value of the NETE occurrence probability is decreased with the solar
activity index F10.7 increase. The increase in a 3-h geomagnetic index Kp or the decrease in a 1-h geomagnetic
index Dst leads to the increase in the NETE occurrence probability. This tendency is more pronounced for current values of Kp or Dst
rather than for delayed ones and becomes more weak with the delay increase. The NETEs are most likely to begin between
19:00 and 20:00 UT. The studied NETEs are characterized by the most typical duration from 1 to 3h with the
percentage peak between 1 and 2h. The electron temperature increases are predominately between 100K and 300K.
We did not find any relationship between the amplitude and duration of the NETEs studied. It is shown that there is a
tendency for the NETE amplitude to increase if the value of Kp or ∣Dst∣ increases. To determine whether there exists a
difference between NETEs observed during different solar cycles, we chose the data subsets corresponding to 21 and
22solar cycles and performed the statistical studies for each subset. It was found that, within the errors, the corresponding
dependencies are the same for the cycles considered and for the entire data set.
Key words. Ionosphere (plasma temperature and density;
ionospheric disturbances; modeling and forecasting) |
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