Abstract
Local Intermittency Measure (LIM) is a development of wavelet analysis particularly suited to the diagnosis of isolated, intermittent events in time series. We construct LIM scalograms of Neutron Monitor (NM) data for an example each of a large GLE and a Forbush decrease. Both kinds of event show distinctive LIM signatures. In the case of the Forbush decrease the method also identifies a second, much smaller event that took place in the same time period. LIM may thus be a useful tool for automated or semi-automated detection of such events in NM data.
Highlights
The data provided by the global neutron monitor (NM) network offer a detailed look at many aspects of solar high-energy phenomena and solar-terrestrial interactions
We give more details of Local Intermittency Measure (LIM) formalism and what it says about a time series before applying it to Neutron Monitor (NM) data to show that it can be effective at identifying ground level enhancements (GLE) and Forbush decreases (FD)
The LIM2 signature of the GLE is seen in a scalogram calculated using data from the Terre Adelie NM
Summary
The data provided by the global neutron monitor (NM) network offer a detailed look at many aspects of solar high-energy phenomena and solar-terrestrial interactions. Semi-regular changes in count rates reflect known periodicities in solar phenomena: the solar rotation rate, the activity cycle. Fourier and wavelet decompositions of the NM count rate time series have been used to extract information about such quasi-periodic behaviour (e.g. Kudela et al 2010). Time series analysis methods focusing on quasi-periodic behaviour may not be the best tools for studying them. We suggest that Local Intermittency Measure (LIM) may be a useful tool for identifying and characterising such events in NM data. We give more details of LIM formalism and what it says about a time series before applying it to NM data to show that it can be effective at identifying GLEs and FDs. Section 4 offers some concluding comments
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