Mathematics – Logic
Scientific paper
Dec 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007agufm.p51c0670h&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #P51C-0670
Mathematics
Logic
1221 Lunar And Planetary Geodesy And Gravity (5417, 5450, 5714, 5744, 6019, 6250), 1517 Magnetic Anomalies: Modeling And Interpretation, 1541 Satellite Magnetics: Main Field, Crustal Field, External Field, 5410 Composition (1060, 3672), 5440 Magnetic Fields And Magnetism
Scientific paper
The global magnetic anomaly maps derived from the Lunar Prospector vector magnetometer data has revealed weak anomalies over the regions flooded by lunar mare basalts and strong anomalies over the regions diametrically opposite to some of the largest basin-forming impact craters. Conversely, the spectrometer data over the Lunar mare show a high concentration of FeO by weight, suggesting that iron could mostly be present in the form of ilmenites and other high Titanium oxide. Among the mare basins, Crisium and Marginis show anomaly strength > 4 nT at 30 km altitude while Serenitatis, Fecundiatis, Nectaris, Australe and Moscoviense show strength < 4 nT. Large mare basins Imbrium and Orientale show the weakest features < 1.5 nT. The anomalies are modelled in terms of vertically integrated magnetization model of the lunar crust. The lunar crustal thickness model, paleomagnetic measurements of the samples collected from Apollo Lunar mission and the known geological regions covering the lunar mare are combined together following a Geographic Information System based technique to compute a lunar crustal magnetization model (LCMM). Vector magnetic anomaly maps are predicted at an altitude of 30 km using LCMM and are compared with the corresponding observed magnetic anomaly map. The sources causing the magnetic anomalies, in particular the thickness of the underlying basalts are modified to match the observations. Some of the regions, for instance north of Mare Marginis, not occupied by the present known surface expression of the mare regions also show strong anomaly features whose causative sources need to be understood and modelled.
Hemant Kumar
Purucker Michael
Sabaka Terence
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