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dc.contributor.advisor Gasiewski, Albin
dc.contributor.author Anghel, Adela
dc.date.accessioned 2019-04-16T10:58:20Z
dc.date.available 2019-04-16T10:58:20Z
dc.date.issued 2009
dc.identifier.uri http://repositorio.igp.gob.pe/handle/IGP/4472
dc.description.abstract "This thesis presents a series of studies investigating the Earth's thermosphere, ionosphere, and plasmasphere using continuous wavelet analysis techniques, multi-layer feedforward neural networks, and Kalman filters, along with extensive datasets of satellite and ground-based observations collected during the solar cycle 23. It is widely accepted that the overall ionospheric and thermospheric variability is primarily influenced by the solar activity, geomagnetic activity, and meteorological processes originating at lower atmospheric layers. While the solar activity influences mostly the long-term variability of the thermosphere-ionosphere system, the geomagnetic activity and meteorological processes tipically induce oscillations with periods ranging from several days to minutes and even seconds. Stemming from the need to understand and predict the behavior of the thermosphere-ionosphere system and its deviations from normal climatological patterns, during both quiet and disturbed geomagnetic conditions, recent modeling and experimental studies have shown an increased interest in the short-period (minutes-to-hours) and day-to-day variability, or weather aspects of the Earth's upper atmosphere and ionosphere. In this context, one of the main objectives of our current studies is to investigate the geomagnetically forced multi-day periodic variations in the thermosphere-ionosphere system, especially those associated with the recurrent geomagnetic activity at the declining and minimum phases of the solar cycle 23. For this purpose, several ionospheric, thermospheric, and solar wind parameters, along with different geomagnetic and solar activity indices are analyzed using a wide spectrum of wavelet-based analysis techniques. A large part of this thesis is also dedicated to presenting a variety of neural network-based models developed (1) for estimating the daytime equatorial zonal electric fields using magnetometer observations, (2) for quantifying the relationships between the interplanetary electric field and the daytime penetration electric fields at equatorial latitudes, and (3) for investigating the shielding effect of the ring current at different longitude sectors. In addition, we also examine the periodic variations in the magnetometer-inferred equatorial ionospheric electric fields using wavelet analysis, and relate these variations to periodic fluctuations in the dawn-to-dusk component of the interplanetary electric field, showing that the geomagnetic activity is an important source of periodic oscillations in the ionosphere. A significant part of this thesis is also dedicated to presenting a Kalman filter-based data assimilation algorithm developed for the near-real time estimation of both the ionospheric and plasmaspheric contributions to the GPS measurements of total electron content (TEC), by combining GPS-TEC observations with background information from an ionospheric model and from a plasmaspheric model. It is shown that the newly-developed algorithm represents a valuable remote sensing technique for investigating both the ionosphere and plasmasphere in near-real time". es_ES
dc.description.uri Tesis es_ES
dc.format application/pdf es_ES
dc.language.iso eng es_ES
dc.publisher University of Colorado es_ES
dc.rights info:eu-repo/semantics/restrictedAccess es_ES
dc.source Repositorio institucional - IGP es_ES
dc.subject Observaciones satelitales es_ES
dc.subject Actividad solar es_ES
dc.subject Ionósfera es_ES
dc.subject Campos eléctricos es_ES
dc.title Studies of the thermosphere,ionosphere and plasmasphere using wavelet analysis neural networks, and kalman filters es_ES
dc.type info:eu-repo/semantics/doctoralThesis es_ES
dc.subject.ocde Atmósfera es_ES
dc.subject.ocde Meteorología es_ES
dc.subject.ocde Tierra (planeta) es_ES
thesis.degree.grantor University of Colorado. Electrical and Computer Engineering. es_ES
thesis.degree.level Maestría es_ES
thesis.degree.discipline Electrical and Computer Engineering. es_ES
dc.description.peer-review Por pares es_ES

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