HR: 08:45h
AN: GP41A-04 INVITED    [Abstracts]
TI: Resampling the 0-5 Ma Geomagnetic Field Recorded by Lavas
AU: * Constable, C G
EM: cconstable@ucsd.edu
AF: Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093-0225, United States
AU: Johnson, C L
EM: cjohnson@eos.ubc.ca
AF: Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093-0225, United States
AU: Johnson, C L
EM: cjohnson@eos.ubc.ca
AF: Department of Earth and Ocean Sciences, University of British Columbia, 6339 Stores Road, Vancouver, BC V6T 1Z4, Canada
AB: Paleomagnetic models of both the time-averaged field and paleosecular variation rely on directions and absolute intensities recorded by igneous rocks. Such modeling implicitly supposes that in a statistical sense the available data provide representative sampling for the time span under consideration. In practice, the vagaries of eruptive processes leave large spatial gaps, and at any specific location often lead to multiple samples that are closely spaced in time followed by a long hiatus. The resulting data set is rarely consistent with the assumption of random uniform sampling of a specific time interval. Such problems have led to extensive discussions of the significance of inclination anomalies and low paleosecular variation in Hawaii, where there are numerous directional data that are known to be densely clustered in some parts of the 0-5~Ma time interval and sparse elsewhere. Various ad hoc methods have been proposed for dealing with the temporal sampling problem. Most are intended to remove the influence of serial correlation in directional data with known stratigraphic ordering and to acquire independent estimates of the field. These methods have included sparse temporal sampling, or averaging of successive directions that are not significantly different from one another. We investigate alternative strategies that use all available directions and age information and ascribe a probability density function (pdf) to the probable ages associated with paleomagnetic directions. The data are then resampled in time to produce an essentially uniform distribution and assess the influence on VGP dispersion, inclination anomaly, and other paleomagnetic statistics of interest. In its crudest form the temporal pdf for a specific datum might be uniform over the Brunhes polarity interval for example, while for well-dated flows one might use a gaussian with rather tight constraints on its variance based on the standard error in the age. Upper and lower bounds on the age can also be readily accommodated. This provides a realistic mechanism for capitalizing on substantial recent efforts in radiometric dating of lava flows and for improving estimates of field variability on million year time scales.
DE: 1522 Paleomagnetic secular variation
DE: 1545 Spatial variations: all harmonics and anomalies
DE: 1560 Time variations: secular and longer
SC: Geomagnetism and Paleomagnetism [GP]
MN: 2007 Fall Meeting