The cause and treatment of anisotropic errors in near-Earth geomagnetic data

Abstract The data available to constrain models of the geomagnetic field are dominated by measurements made at or near to the Earth's surface, typically treated as independent and uncorrelated. Here we examine the effect on field modelling of error anisotropy in these data, potentially leading to correlations between different field components measured at the same location. We consider three examples. First, we examine the effect of crustal magnetisation, in general the largest source of error in main field modelling. We demonstrate that under a stochastic treatment of the crustal field, the error resulting from this source is larger by a factor of approximately 2 in Z than in X and Y. and that correct modelling of this effect reduces the variances of the field model coefficients by greater than 10%. The anisotropy leads to error correlation between measurements of inclination and field intensity. Second, we consider the calculation of cartesian component vector data from measurements of field intensity and direction. When measurement error is the dominant source of uncertainty, the error estimates for the resulting vector data can be strongly correlated. Third, we examine the proposed deployment of a set of ocean-bottom magnetic observatories. One important difficulty with this project is the determination of accurate horizontal orientation. We demonstrate that with correct modelling, orientation information of limited accuracy is sufficient to allow determination of high-quality field models.

[1]  T. Sabaka,et al.  Uncertainty estimates in geomagnetic field modeling , 1989 .

[2]  Catherine Constable,et al.  The influence of correlated crustal signals in modelling the main geomagnetic field , 1997 .

[3]  Robert A. Langel,et al.  The Geomagnetic Field: 1970-1990 and the NASA Candidate Models for DGRF1985 and IGRF1990. , 1992 .

[4]  George E. Backus,et al.  Trimming and procrastination as inversion techniques , 1996 .

[5]  A. Jackson,et al.  Statistical Treatment of Crustal Magnetization , 1994 .

[6]  Philip B. Stark,et al.  Geomagnetic field models incorporating frozen‐flux constraints , 1993 .

[7]  R. Langel,et al.  Toward an Improved Distribution of Magnetic Observatories for Modeling of the Main Geomagnetic Field and Its Temporal Change. , 1995 .

[8]  Andrew Jackson,et al.  Accounting for crustal magnetization in models of the core magnetic field , 1990 .

[9]  J. Cain,et al.  Modelling the Earth's geomagnetic field to high degree and order , 1989 .

[10]  R. Parker A statistical theory of seamount magnetism , 1988 .

[11]  F. Lowes Mean‐square values on sphere of spherical harmonic vector fields , 1966 .

[12]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[13]  Jeremy Bloxham,et al.  Geomagnetic field analysis—III. Magnetic fields on the core—mantle boundary , 1985 .

[14]  Jeremy Bloxham,et al.  Alleviation of the Backus Effect in geomagnetic field modelling , 1995 .

[15]  Jeremy Bloxham,et al.  Geomagnetic secular variation , 1989, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.

[16]  Catherine Constable,et al.  Frozen-flux modelling for epochs 1915 and 1980 , 1997 .

[17]  G. V. Haines Modelling geomagnetic secular variation by main‐field differences , 1993 .

[18]  Robert A. Langel,et al.  THE NEAR-EARTH MAGNETIC FIELD FROM MAGNETOSPHERIC AND QUIET-DAY IONOSPHERIC SOURCES AND HOW IT IS MODELED , 1996 .

[19]  R. Parker Geophysical Inverse Theory , 1994 .

[20]  A. Jackson,et al.  Bounding the long wavelength crustal magnetic field , 1996 .

[21]  G. D. Mead,et al.  Some new methods in geomagnetic field modeling applied to the 1960-1980 epoch. , 1982 .

[22]  Robert A. Langel,et al.  A geomagnetic field spectrum , 1982 .

[23]  Jeremy Bloxham,et al.  Simultaneous stochastic inversion for geomagnetic main field and secular variation: 2. 1820–1980 , 1989 .

[24]  Jeremy Bloxham,et al.  Time‐dependent mapping of the magnetic field at the core‐mantle boundary , 1992 .

[25]  Jeremy Bloxham,et al.  The treatment of attitude errors in satellite geomagnetic data , 1996 .