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This study examines the variation of different energies linked with the Sun and the Earth’s magnetosphere-ionosphere systems for solar cycles (SCs) 22–24 for which the gradual decrease in the solar activity is noticed. Firstly, we investigated the variation of solar magnetic energy density (SMED) for SCs 21–24 and its relation to the solar activity. We observed distinct double peak structures in SMED for the past four SCs, 21–24. This feature is consistent with noticeable asymmetry in their two peaks. For SCs 22–24 a significant decrease is observed in the integrated SMED of each SC. This reduction is 37% from SCs 22 to 23 and 51% from SCs 23 to 24, which indicates substantial weakening of Sun’s magnetic field for SC 24. Also, the magnetic, kinetic, and thermal energy densities at the Earth’s bow-shock nose are found to be considerably low for the SC 24. We examined the solar wind Alfven speed, magnetosonic Mach number, solar wind-magnetosphere energy coupling parameter (ε), and the Chapman-Ferraro magnetopause distance (LCF) for the SCs 22–24. The estimated maximum stand-off magnetopause distance is larger for SC 24 (LCF ≤ 10.6 RE) as compared to SC 23 (LCF ≤ 10.2 RE) and SC 22 (LCF ≤ 9.8 RE). The solar wind Alfven speeds during SCs 22 and 23 are in the same range and do not exceed ≈73 km/s whereas, it is below 57 km/s for SC 24. A lower bound of solar wind magnetosonic Mach number for SC 24 is larger (M ≥ 6.9) as compared to SC 22 (M ≥ 5.9) and SC 23 (M ≥ 6). We noticed weakening in the energy coupling parameter for SC 24, which resulted in substantial (15%–38%) decrease in average strength of high latitude ionospheric (AE), low latitude magnetospheric (Dst) and equatorial ionospheric (EEJ) current systems in comparison with SC 23. Subsequently, a reduction of ≈30% is manifested in the high latitude Joule heating for SC 24. Overall this study indicates the significant step down in various energies at Sun, Earth’s bow-shock, and near Earth environment for current SC 24, which will have important implication on our Earth’s atmosphere-ionosphere-magnetosphere system.

The prediction of an extended solar minimum is extremely important because of the severity of its impact on the near-earth space. Here, we present a new method for predicting the descent time of the forthcoming solar cycle (SC); the method is based on the estimation of the Shannon entropy. We use the daily and monthly smoothed international sunspot number. For each nth SC, we compute the parameter [Tpre]n by using information on the descent and ascent times of the n − 3th and nth SCs, respectively. We find that [Tpre] of nth SC and entropy can be effectively used to predict the descent time of the n + 2th SC. The correlation coefficient between [Td]n+2 − [Tpre]n and [E]n is found to be 0.95. Using these parameters the prediction model is developed. Solar magnetic field and F10.7 flux data are available for SCs 21–22 and 19–23, respectively, and they are also utilized to get estimates of the Shannon entropy. It is found that the Shannon entropy, a measure of randomness inherent in the SC, is reflected well in the various proxies of the solar activity (viz sunspot, magnetic field, F10.7 flux). The applicability and accuracy of the prediction model equation is verified by way of association of least entropy values with the Dalton minimum. The prediction model equation also provides possible criteria for the occurrence of unusually longer solar minima.

We present a non-stationary epidemic-type aftershock sequence (ETAS) model in which the usual assumption of stationary background rate is relaxed. Such a model could be used for modeling seismic sequences affected by aseismic transients such as fluid/magma intrusion, slow slip earthquakes (SSEs), etc. The non-stationary background rate is expressed as a linear combination of B-splines, and a method is proposed that allows for simultaneous estimation of background rate as well as other ETAS model parameters. We also present an extension to this non-stationary ETAS model where an adaptive roughness penalty function is used and consequently provides better estimates of rapidly varying background rate functions. The performance of the proposed methods is demonstrated on synthetic catalogs and an application to detect earthquake swarms (possibly associated with SSEs) in Hikurangi margin (North Island, New Zealand) is presented. [ABSTRACT FROM AUTHOR]