Physics Mining of the CLUSTER Data Using a New Automated Technique: New List of Flux Transfer Events

Details Physics Mining of the CLUSTER Data Using a New Automated Technique: New List of Flux Transfer Events Physics Mining of the CLUSTER Data Using a New Automated Technique: New List of Flux Transfer Events

Dec 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008agufmsm23a1687s&link_type=abstract

American Geophysical Union, Fall Meeting 2008, abstract #SM23A-1687

Other

2723 Magnetic Reconnection (7526, 7835), 7526 Magnetic Reconnection (2723, 7835), 7835 Magnetic Reconnection (2723, 7526)

Scientific paper

A new data mining technique called MineTool-TS is used to develop a model for automated detection of flux transfer events (FTEs) at Earth's magnetopause in the Cluster spacecraft time series data. The model classifies a given time series into one of three categories of non-FTE, magnetosheath FTE, or magnetospheric FTE. One important feature of MineTool-TS is the ability to explore the importance of each variable or combination of variables as indicators of FTEs. FTEs have traditionally been identified based on their magnetic field signatures, but here we find that some plasma variables like the perpendicular temperature can be equally strong indicators of FTEs. For example, the perpendicular ion temperature yields a model accuracy of 96%. We also find that models using GSM coordinates yield comparable accuracy to those using boundary normal coordinates. This is useful since there are regions where magnetopause models are not accurate. Another surprising result is the finding that the algorithm can distinguish between magnetosheath and magnetospheric FTEs solely based on the magnetic field data, something that experts may not do so straightforwardly based on short time series intervals. The most accurate models use combination of plasma and magnetic field variables and achieve a very high accuracy of prediction of 97%. A list of FTEs, which contains both the expert labels and the automated detection results from Cluster data during years 2001 - 2003, can be obtained from the authors.

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