Analysis of the Thelliers' method of paleointensity determination 2: Applicability to high and low magnetic fields.

Tanaka, Hidefumi; Kono, Michikata

doi:10.5636/jgg.36.285

Cited by 30 publications

(18 citation statements)

References 17 publications

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“…Their data also indicate that when F Lab is < F Anc paleointensity estimates tend to be less accurate and Arai plots more scattered. Tanaka and Kono [1984] also investigated the effects of varying the strength of F Lab . The results of Tanaka and Kono [1984] indicate that the scatter of the Arai plot is lowest when F Lab is within a factor of ∼2 of F Anc .…”

Section: Discussionmentioning

confidence: 99%

“… Tanaka and Kono [1984] also investigated the effects of varying the strength of F Lab . The results of Tanaka and Kono [1984] indicate that the scatter of the Arai plot is lowest when F Lab is within a factor of ∼2 of F Anc . It should be noted that the paleointensity data of Tanaka and Kono [1984] used the variance analysis of Kono and Tanaka [1984] and, as noted above, this may yield inaccurate results.…”

Section: Discussionmentioning

confidence: 99%

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Towards the robust selection of Thellier‐type paleointensity data: The influence of experimental noise

Paterson¹,

Biggin²,

Yamamoto³

et al. 2012

Geochem Geophys Geosyst

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[1] The process of data selection in paleointensity studies is an essential step to ensure data fidelity. There is, however, no consensus as to the best approach to consistently select data with most studies using arbitrarily defined thresholds for selection. We present a new numerical model that simulates the variability of paleointensity data from hypothetical ideal samples acquiring a thermoremanent magnetization (TRM) by incorporating experimental noise, which has been constrained using over 75,000 data measurements. Using Monte Carlo analyses, we investigate the behavior of simulated data and characterize the distributions of parameters typically used to select paleointensity data. We use the 95th percentiles of the distributions to define thresholds for the maximum likely parameter values that can result from experimental noise. These represent values below which we cannot distinguish non-ideal behavior from noise. We find that a number of parameters are highly sensitive to noise and laboratory field strength (e.g., partial TRM, pTRM, check CDRAT and pTRM tail check dt*); this sensitivity may diminish their ability to identify non-ideal behavior. The fractional ( f ) dependence of some parameters and the proportion of inaccurate results provide justification for f ≥ 0.35 when selecting data from both Thellier-Thellier and Coe protocol experiments. The manifestation of noise in the original Thellier method, however, is different to that of methods that use zero-field heating steps. This suggests that the data selection procedure for the Thellier method should be different, but it also suggests that, contrary to previous analyses, the accuracy and scatter of results from this method are more sensitive to noise than methods that use zero-field heating steps. The general approach taken here is shown to be a powerful means of understanding the behavior of selection parameters and has the potential to be extended to models incorporating non-ideal behavior resulting from alteration and multidomain grains.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Towards the robust selection of Thellier‐type paleointensity data: The influence of experimental noise

Paterson¹,

Biggin²,

Yamamoto³

et al. 2012

Geochem Geophys Geosyst

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“…The problem treated in this paper is only mathematical; we assume that we know the temperature interval in which all the assumptions are satisfied and try to estimate the slope of linear relation and its uncertainty. The non-ideal behaviors of real samples and related problems were reported by many authors, and we also address to some problems in this category (e.g., range of magnetic field where the method is applicable) in an accompanying paper (TANAKA and KoNo, 1984).…”

Section: J+(t)=y(t)+x(t)mentioning

confidence: 99%

Analysis of the Thelliers' method of paleointensity determination 1: Estimation of statistical errors.

Kono

Tanaka

1984

J. geomagn. geoelec

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In obtaining paleointensity estimates of the geomagnetic field and their uncertainties, least squares fitting is performed on the data to obtain the slope of the linear NRM-TRM relation. Since both the X and Y coordinates (the TRM and NRM components) contain errors, variances of both coordinates should be used in the calculation of the slope (i.e., paleointensity). We propose a method to calculate variances based on experimental errors. Numerical analysis indicates that errors vary with temperature, and that data near the Curie point contain large statistical errors, even when samples show an ideal behavior. Contrary to the usual belief, heating in nonmagnetic space does not reduce overall errors; the original method of double heating with the field direction reversed gives more well balanced errors and therefore better performance. Further, we suggest the use of WILLIAMSON's (1968) method instead of YORK'S (1966) original argorithm in the calculation of the slope of the NRM-TRM linear relation, because the former method reflects the error level in individual data points while the latter does not. The standard error obtained by the present method is a good measure of the overall reliability of paleointensity data.

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“…The sets of the curves show that the relationship between pTRM and F L is linear (Fig. 4) as expected for small applied fields (Nagata, 1943;Tanaka and Kono, 1984). It is clear that there is a decrease in pTRM intensity from θ = 0 • to 90…”

Section: Results Of Ptrm Acquisition Experimentsmentioning

confidence: 67%

Effect of magnetic anisotropy on the experimentally determined palaeointensity of the geomagnetic field

et al. 2014

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Rock magnetic properties of the Nile mud are reported. They indicate that the carrier of magnetization in the Nile mud is predominantly magnetite. Fourty air-dried ceramic samples made of Nile mud were manufactured to ceramics by stepwise heating to 700• C at various field intensities between 0.03 mT and 0.09 mT and with various angles θ between the laboratory field (F L ) direction and the ceramics. The partial (pTRM) and the total thermoremanent magnetization (TRM) increase linearly as the magnetic field (F L ) increases. The rate of increase of the pTRM with both F L and temperature T depends on θ , so that it decreases by 25% as θ increases from 0• to 90• . In extreme cases, the effect of the magnetic anisotropy results in overestimating the determined palaeointensity by 33% and underestimating it by 25% from the correct value. The direction of TRM is the same as that of the ambient magnetic field independent of the anisotropy. Applying the laboratory field in the direction of the stable natural remanent magnetization during a Thellier-type experiment results in accurate determination of the palaeointensity.

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Analysis of the Thelliers' method of paleointensity determination 2: Applicability to high and low magnetic fields.

Cited by 30 publications

References 17 publications

Towards the robust selection of Thellier‐type paleointensity data: The influence of experimental noise

Towards the robust selection of Thellier‐type paleointensity data: The influence of experimental noise

Analysis of the Thelliers' method of paleointensity determination 1: Estimation of statistical errors.

Effect of magnetic anisotropy on the experimentally determined palaeointensity of the geomagnetic field

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