Automated identification of current sheets -- a new tool to study turbulence and intermittency in the solar wind
Olga Khabarova, Timothy Sagitov, Roman Kislov, and Gang Li

TL;DR
This paper introduces a new automated method for identifying current sheets in the solar wind, combining plasma and magnetic field data, enabling comprehensive statistical analysis of their properties and relation to solar wind conditions.
Contribution
The authors develop a three-parameter empirical automated method for current sheet detection that improves upon existing techniques by incorporating plasma parameters alongside magnetic field data.
Findings
CS rate correlates with solar wind temperature T.
Maxima of CS rate are linked to interaction regions and ejections.
The method allows multiyear statistical analysis of current sheets at 1 AU.
Abstract
We propose a new method of the automated identification of current sheets (CSs) that represents a formalization of the visual inspection approach employed in case studies. CSs are often identified by eye via the analysis of characteristic changes in the interplanetary magnetic field (IMF) and plasma parameters. Known visual and semi-automated empirical methods of CS identification are exact but do not allow a comprehensive statistical analysis of CS properties. Existing automated methods partially solve this problem. Meanwhile, these methods suggest an analysis of variations of the IMF and its direction only. In our three-parameter empirical method, we employ both the solar wind plasma and IMF parameters to identify CSs of various types. Derivatives of the IMF strength, the plasma beta and the ratio of the Alfv'en speed VA to the solar wind speed V taken with the one-second cadence are…
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