The figure shows bias of the magnitude error distributions for the Tsyganenko- 2004 (TS04) model by comparing the residual error for TS04 against a validation set. The color scale denotes the number of observation points at that location in comparison space. The X-axis shows the logarithm of the observed magnetic field magnitude. Positive values on the Y-axis imply model over-prediction of the magnetic field magnitude, while negative values imply model under-prediction of the magnetic field magnitude. Here, most of the comparisons (bright colors) show small model-observations differences at locations where the observed field values is ~100 nT, which is typical of geosynchronous orbit magnetic field values. Credit: Brito and Morley, 2017, Figure 5d
Source: Space Weather

Improving models of the geomagnetic field is important to radiation belt studies, determining when satellites are on the same magnetic field line, and mapping from the ionosphere to the magnetotail or vice versa, to name just a few applications. Brito and Morley [2017] present a method for comparing the accuracy of several versions of the Tsyganenko empirical magnetic field models and for optimizing the empirical magnetic field model using in situ magnetic field measurements. The study was carried out for intervals of varied geomagnetic activity selected by the Geospace Environment Modeling Challenge for the Quantitative Assessment of Radiation Belt Modeling Focus Group. The authors describe a method for improving the results of various Tsyganenko magnetic field models, especially with respect to outliers, using a new cost function, various metrics and Nelder-Mead optimization.

Importantly, this model evaluation was based on points in the magnetosphere that were not used for fitting. Thus, the results provide an independent validation of the method. The model, known as TS04, produced the best results after optimization, generating a smaller error in 57.3% of the points in the tested data set when compared to the standard (unoptimized) inputs. The results of this study include a set of optimized parameters that can be used to evaluate the models studied in this paper. These optimized parameters are included as supplementary material so that the broader scientific community can use the optimized magnetic field models immediately, and without any additional code development, using any standard implementation of the magnetic field models tested in the study.

Citation: Brito T.V., and S.K. Morley [2017], Improving empirical magnetic field models by fitting to in situ data using an optimized parameter approach, Space Weather, 15,

—Delores J. Knipp, Editor-in-Chief, Space Weather

Text © 2017. The authors. CC BY-NC-ND 3.0
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