Computer Science
Scientific paper
May 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010adspr..45.1129k&link_type=abstract
Advances in Space Research, Volume 45, Issue 9, p. 1129-1144.
Computer Science
Scientific paper
This paper presents an analysis of a set of time series that represent foF2 disturbances during storm conditions, using clustering tools. The time series under study have been drawn from ionospheric observations obtained from eight European middle latitude ionosondes during a significant number of storm-time intervals and they are divided into eight groups according to the latitude (middle to low and middle to high) and the local time of the observation point at storm onset (afternoon, evening, morning, prenoon). The time series in each group have been analyzed using clustering-based methods. Specifically, each time series has been represented using two different ways of representation: the first is the raw representation while the second is through the parameters of the autoregressive (AR) model that best represents it. For each representation a hierarchy of clusterings is produced via the complete link algorithm. The two produced hierarchies are combined to a single one and the final clustering results are extracted from the produced hierarchy. The obtained results are in close agreement with the theoretical formulations concerning ionospheric storm effects at middle latitudes. In addition, they may be proved useful in the development of more accurate ionospheric forecasting methods.
Belehaki Anna
Koutroumbas K.
Tsagouri Ioanna
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