Each 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 P Dyn and effective convection electric field E y in the solar wind observed in situ upstream of Earth, the ring current index D ST , 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.Plain Language Summary Earth's near-space plasma environment is highly dynamic, with its own space weather. Space weather impacts include electrical power loss, aviation disruption, interrupted communications, and disturbance to satellite systems. The drivers of space weather, the sun and solar wind, and the response seen at Earth have now been almost continually monitored by ground-and space-based observations over the last five solar cycles (more than 50 years). Each of the last five solar maxima has a different duration and peak activity level and as a consequence the climate of Earth's space weather is also different at each solar maximum. We find that some aspects of the space weather climate are in fact reproducible; they can be inferred from that of previous solar maxima. This may help understand the behavior of future solar maxima.
We use 20 years of Wind solar wind observations to investigate the solar cycle variation of the solar wind driving of the magnetosphere. For the first time, we use generalized quantile‐quantile plots to compare the statistical distribution of four commonly used solar wind coupling parameters, Poynting flux, B2, the ε parameter, and vB, between the maxima and minima of solar cycles 23 and 24. We find the distribution is multicomponent and has the same functional form at all solar cycle phases; the change in distribution is captured by a simple transformation of variables for each component. The ε parameter is less sensitive than its constituent variables to changes in the distribution of extreme values between successive solar maxima. The quiet minimum of cycle 23 manifests only in lower extreme values, while cycle 24 was less active across the full distribution range.
Solar wind variability spans a wide range of amplitudes and timescales, from turbulent fluctuations to the 11 year solar cycle. We apply the data quantile‐quantile (DQQ) method to NASA/Wind observations spanning solar cycles 23 and 24, to study how the uniqueness of each cycle maximum and minimum manifests in the changing statistical distribution of plasma parameters in fast and slow solar wind. The DQQ method allows us to discriminate between two distinct components of the distribution: the core region simply tracks the solar cycle in its moments but shows little sensitivity to solar wind state or the specific activity of each cycle. This would be consistent with an underlying in situ process such as turbulence driving the evolution of fluctuations up to an outer scale. In contrast, the tail component of the distribution is sensitive both to the differences between the maxima and minima of cycles 23 and 24, and the fast or slow state of the solar wind. The tail component varies over the solar cycle in such a way as to maintain a constant functional form, with only its moments varying with solar activity. Finally, after isolating the core region of the distribution, we test its lognormality over the solar cycle in each solar wind state and find the lognormal provides a more robust description of the statistics in slow wind than fast; however, in both states the goodness of fit is significantly reduced at solar maximum.
Time series of solar wind variables are bursty in nature. Bursts, or excursions, in the time series of solar wind parameters are associated with various transient structures in the solar wind plasma and are often the drivers of increased space weather activity in Earth's magnetosphere. We define bursts by setting a threshold value of the time series and identifying how often, and for how long, it is exceeded. This allows us to study how the statistical distributions and scaling properties of burst parameters vary over solar cycles 23 and 24. We find that the distributions of burst duration and integrated burst size vary over the solar cycle and between the equivalent phases of consecutive cycles. However, there exists a single power law scaling relation between burst size and duration, with a joint area‐duration scaling exponent α that is independent of the solar cycle. This provides a solar cycle invariant constraint between possible sizes and durations of solar wind bursts that can occur.
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