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Volume 25, issue 1 | Copyright

Special issue: Nonlinear Waves and Chaos

Nonlin. Processes Geophys., 25, 67-76, 2018
https://doi.org/10.5194/npg-25-67-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 31 Jan 2018

Research article | 31 Jan 2018

A correlation study regarding the AE index and ACE solar wind data for Alfvénic intervals using wavelet decomposition and reconstruction

Fernando L. Guarnieri1, Bruce T. Tsurutani2, Luis E. A. Vieira1, Rajkumar Hajra3, Ezequiel Echer1, Anthony J. Mannucci2, and Walter D. Gonzalez1 Fernando L. Guarnieri et al.
  • 1Instituto Nacional de Pesquisas Espaciais – INPE, São José dos Campos, SP, Brazil
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 3Laboratoire de Physique et Chimie de l'Environement et de l'Espace, CNRS, Orléans, France

Abstract. The purpose of this study is to present a wavelet interactive filtering and reconstruction technique and apply this to the solar wind magnetic field components detected at the L1 Lagrange point  ∼ 0.01AU upstream of the Earth. These filtered interplanetary magnetic field (IMF) data are fed into a model to calculate a time series which we call AE. This model was adjusted assuming that magnetic reconnection associated with southward-directed IMF Bz is the main mechanism transferring energy into the magnetosphere. The calculated AE was compared to the observed AE (auroral electrojet) index using cross-correlation analysis. The results show correlations as high as 0.90. Empirical removal of the high-frequency, short-wavelength Alfvénic component in the IMF by wavelet decomposition is shown to dramatically improve the correlation between AE and the observed AE index. It is envisioned that this AE can be used as the main input for a model to forecast relativistic electrons in the Earth's outer radiation belts, which are delayed by  ∼ 1 to 2 days from intense AE events.

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In this work we developed a method to obtain a time series named as AE* which is well correlated with the geomagnetic AE index. In this process, wavelet filtering is applied to interplanetary solar wind data from spacecrafts around the L1 libration point. This geomagnetic indicator AE* can be obtained well before the AE index release in its final form, and it can be used to feed models for geomagnetic effects, such as the relativistic electrons, giving forecasts ~ 1 to 2 days in advance.
In this work we developed a method to obtain a time series named as AE* which is well correlated...
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