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A southern African secular variation model derived from satellite data - A southern African secular variation model derived from CHAMP satellite observations recorded between 2001 and 2005

English, German · Paperback / Softback

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Time variations of the geomagnetic field can be classified into two main categories of internal and external origin with respect to the surface of the Earth. It has been found that the variations that take place on longer time scales are commonly known as secular variation and are of internal origin. The authors study the time variations of the geomagnetic field on longer time scales over southern Africa region applying two regional geomagnetic field modelling techniques, namely, Polynomial Surface Modelling and Spherical Cap Harmonic Analysis to CHAMP satellite observations recorded between 2001 and 2005. They evaluate the performance of the developed model using two global models IGRF-10 and CHAOS with the help of ground-based data.The results identify the occurrence of rapid secular variation fluctuations in all components of the magnetic field vector in 2003 and 2004. These small scale features of the time variations of the geomagnetic field are not detectable by the global models. This book invites also those readers who are interested in operating geomagnetic instruments for data collection and in geomagnetic data processing.

About the author










Emmanuel Nahayo, MSc: Physics at University of KwaZulu-Natal. He is doing a PhD part time in Geophysics in the School of Geosciences at University of the Witwatersrand in South Africa. Scientific Data Analyst at South African National Space Agency (SANSA) Space Science, Hermanus, South Africa.

Product details

Authors Michael Alport, Piete Kotzé, Pieter Kotzé, Emmanue Nahayo, Emmanuel Nahayo
Publisher LAP Lambert Academic Publishing
 
Languages English, German
Product format Paperback / Softback
Released 31.05.2016
 
EAN 9783659698637
ISBN 978-3-659-69863-7
No. of pages 208
Subject Natural sciences, medicine, IT, technology > Geosciences

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