Abstract

AbstractEach solar maximum interval has a different duration and peak activity level, which is reflected in the behavior of key physical variables that characterize solar and solar wind driving and magnetospheric response. The variation in the statistical distributions of the F10.7 index of solar coronal radio emissions, the dynamic pressure PDyn and effective convection electric field Ey in the solar wind observed in situ upstream of Earth, the ring current index DST, and the high‐latitude auroral activity index AE are tracked across the last five solar maxima. For each physical variable we find that the distribution tail (the exceedences above a threshold) can be rescaled onto a single master distribution using the mean and variance specific to each solar maximum interval. We provide generalized Pareto distribution fits to the different master distributions for each of the variables. If the mean and variance of the large‐to‐extreme observations can be predicted for a given solar maximum, then their full distribution is known.

Highlights

  • The space plasma environment near the Earth is highly dynamic, with its own space weather

  • We have quantified the variation between the last five solar maxima of the statistical distributions, that is, survival or return time distributions, of large-to-extreme observations of key physical variables that characterize solar and solar wind driving of space weather and the magnetospheric response: the F10.7 index (Tapping, 2013) of solar coronal radio emissions, the dynamic pressure PDyn, and estimated convection electric field Ey in the solar wind observed in situ upstream of Earth, the enhancement of the ring current DST, and auroral activity at high latitudes, the AE index

  • These statistical distributions can be long tailed, and the tail of the distribution that corresponds to the most space weather-effective events changes in a different manner to the bulk of the distribution as we compare one solar maximum interval to another

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Summary

Introduction

The space plasma environment near the Earth is highly dynamic, with its own space weather. That threshold we find a distinct GPD master distribution for observations of each of the F10.7 index, the solar wind dynamical pressure, and effective electric field Ey and the DST and AE indices. These distributions can be long tailed but are not in the heavy-tailed class (Embrechts et al, 1997), so that a relatively small data sample is required to quantify the mean and variance compared to that needed to resolve the distribution long tail. An estimate of the mean and variance could be obtained over a relatively short time interval at the beginning of an interval of solar maximum activity, and this would provide a prediction of the likelihood of occurrence, and the return times, that could be expected for the more extreme values that may occur during that solar maximum interval

Rescaling and Curve Collapse of Distribution Long Tails
GPD Fits to the Distribution Tails
Survival Functions and Return Times
Findings
Discussion and Conclusions
Full Text
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