Gap Filling of Solar Wind Data by Singular Spectrum Analysis

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

The solar wind is the primary driver for space weather phenomena at the Earth. Unfortunately, the observations of the solar wind are plagued by gaps in the data. Modeling of the dynamics of the magnetosphere and ionosphere generally require time-continuous information about the solar wind density, velocity and interplanetary magnetic field (IMF). This project will utilize singular spectrum analysis (SSA) techniques to fill in the gaps in the solar wind data by using data from a variety of ground-based observations where continuous data are available. The SSA analysis will be applied to the historical solar wind data from 1963 to the present. The resulting dataset will be used for studies of the radiaton belts. The dataset will also be made available to the research community through the Virtual Radiation Belt Observatory (ViRBO). The continuous solar wind and IMF data that will be produced will be useful in a variety of research projects concerning space weather and the work therefore will have societal benefits. The project also has educational benefits through the participation of a graduate student.