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Abstract

The utility of frequency- and space-limited spherical harmonic Slepian basis functions for magnetic anomaly modeling over restricted spherical patches of the Earth was investigated using combined near-surface scalar and CHAMP satellite vector observations from Australia and adjacent marine areas. In particular, Slepian spherical harmonic models up to degree 360 were studied for modeling anomaly features of 1° (~111 km) and longer over a 25°-radius cap centered on Australia. Relative to the roughly 130,000 coefficients required for global spherical harmonic modeling, less than 5% of this number of coefficients is sufficient for effective localized Slepian modeling. Slepian coefficients have maximum power over the spherical cap and may be exploited for estimating the magnetic anomaly vectors and gradients to all orders within the working precision of the observations. The Earth cap modeled by Slepian coefficients is also more efficient in accommodating local crustal constraints from drilling and other geological and geophysical studies for interpreting the associated magnetic anomaly data registered in spherical coordinates. In general, Slepian spherical harmonic modeling is well suited for combining spectrally diverse compilations of near-surface and satellite magnetic observations over any spatially restricted spherical cap of the Earth or other planetary body.[Figure not available: see fulltext.]

Details

Title
Utility of Slepian basis functions for modeling near-surface and satellite magnetic anomalies of the Australian lithosphere
Author
Kim, Hyung Rae 1 ; von Frese, Ralph R; B 2 

 Department of GeoEnvironmental Science, Kongju National University, Gongju, Chungnam, South Korea 
 School of Earth Sciences, The Ohio State University, Columbus, OH, USA 
Pages
1-13
Section
1. Geomagnetism
Publication year
2017
Publication date
Apr 2017
Publisher
Springer Nature B.V.
e-ISSN
18805981
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1957091971
Copyright
Earth, Planets and Space is a copyright of Springer, 2017.