The solar activity displays variability and periodic behaviours over a wide range of timescales, with the presence of a most prominent cycle with a mean length of 11 years. Such variability is transported within the heliosphere by solar wind, radiation and other processes, affecting the properties of the interplanetary medium. The presence of solar activity-related periodicities is well visible in different solar wind and geomagnetic indices, although with time lags with respect to the solar one, leading to hysteresis cycles. Here, we investigate the time lag behaviour between a physical proxy of the solar activity, the Ca II K index, and two solar wind parameters (speed and dynamic pressure), studying how their pairwise relative lags vary over almost five solar cycles. We find that the lag between Ca II K index and solar wind speed is not constant over the whole time interval investigated, with values ranging from 6 years to 1 year (average 3.2 years). A similar behaviour is found also for the solar wind dynamic pressure. Then, by using a Lomb-Scargle periodogram analysis we obtain a 10.21-year mean periodicity for the speed and 10.30-year for the dynamic pressure. We speculate that the different periodicities of the solar wind parameters with respect to the solar 11-year cycle may be related to the overall observed temporal evolution of the time lags. Finally, by accounting for them, we obtain empirical relations that link the amplitude of the Ca II K index to the two solar wind parameters.
We study the photospheric magnetic field of ~2000 active regions in solar cycle 23 to search for parameters indicative of energy build-up and subsequent release as a solar flare. We extract three sets of parameters: snapshots in space and time- total flux, magnetic gradients, and neutral lines; evolution in time- flux evolution; structures at multiple size scales- wavelet analysis. This combines pattern recognition and classification techniques via a relevance vector machine to determine whether a region will flare. We consider classification performance using all 38 extracted features and sev…
We study the relationship between solar wind helium to hydrogen abundance ratio ($A_\mathrm{He}$), solar wind speed ($v_\mathrm{SW}$), and sunspot number (SSN) over solar cycles 23 and 24. This is the first full 22-year Hale cycle measured with the Wind spacecraft covering a full cycle of the solar dynamo with two polarity reversals. While previous studies have established a strong correlation between $A_\mathrm{He}$ and SSN, we show that the phase delay between $A_\mathrm{He}$ and SSN is a monotonic increasing function of $v_\mathrm{SW}$. Correcting for this lag, $A_\mathrm{He}$ returns to th…
In the declining phase of the solar cycle, when the new-polarity fields of the solar poles are strengthened by the transport of same-signed magnetic flux from lower latitudes, the polar coronal holes expand and form non-axisymmetric extensions toward the solar equator. These extensions enhance the occurrence of high-speed solar wind streams (HSS) and related co-rotating interaction regions in the low-latitude heliosphere, and cause moderate, recurrent geomagnetic activity in the near-Earth space. Here, using a novel definition of geomagnetic activity at high (polar cap) latitudes and the longe…
By comparing a magneto-frictional model of the low coronal magnetic field to a potential-field source-surface model, we investigate the possible impact of non-potential magnetic structure on empirical solar-wind models. These empirical models (such as Wang-Sheeley-Arge) estimate the distribution of solar-wind speed solely from the magnetic-field structure in the low corona. Our models are computed in a domain between the solar surface and 2.5 solar radii, and are extended to 0.1 AU using a Schatten current-sheet model. The non-potential field has a more complex magnetic skeleton and quasi-sepa…
Solar wind charge exchange (SWCX) is the primary contamination to soft X-ray emission lines from the Milky Way (MW) hot gas. We report a solar-cycle ($\approx 10$ yr) temporal variation of observed \ion{O}{7} and \ion{O}{8} emission line measurements in the {\it XMM-Newton} archive, which is tightly correlated with the solar cycle traced by the sunspot number (SSN). This temporal variation is expected to be associated with the heliospheric SWCX. Another observed correlation is that higher solar wind (SW) fluxes lead to higher O VII or O VIII fluxes, which is due to the magnetospheric SWCX. We …
Galactic cosmic rays (GCRs), the highly energetic particles that may raise critical health issues for astronauts in space, are modulated by solar activity with their intensity lagging behind the sunspot number (SSN) variation by about one year. Previously, this lag has been attributed to a combined effect of outward convecting solar wind and inward propagating GCRs. However, the lag's amplitude and its solar-cycle dependence are still not fully understood (Ross & Chaplin, 2019). By investigating the solar surface magnetic field, we find that the source of heliospheric magnetic field -- the ope…
The Earth's magnetosphere extension is controlled by the solar activity level via solar wind properties. Understanding such a relation in the Solar System is important for predicting also the condition of exoplanetary magnetospheres near Sun-like stars. We use measurements of a chromospheric proxy, the Ca II K index, and solar wind OMNI parameters to connect the solar activity variations, on the decennial time scales, to the solar wind properties. The data span over the time interval 1965-2021, which almost entirely covers the last 5 solar cycles. Using both cross-correlation and mutual inform…
Tracking nonlinear solar-wind dynamics over three solar cycles using Wind observations
Instituto de Física del Noroeste Argentino, CONICET（阿根廷西北物理研究所，阿根廷国家科学研究委员会）；Universidad Nacional de Tucumán（图库曼国立大学）；Departamento de Física, Facultad de Ciencias Exactas y Tecnología, Universidad Nacional de Tucumán（图库曼国立大学理学院技术系物理系）
This article implements a Convolutional Neural Network (CNN)-based deep learning model for solar-wind prediction. Images from the Atmospheric Imaging Assembly (AIA) at 193Ȧ wavelength are used for training. Solar-wind speed is taken from the Advanced Composition Explorer (ACE) located at the Lagrangian L1 point. The proposed CNN architecture is designed from scratch for training with four years' data. The solar-wind has been ballistically traced back to the Sun assuming a constant speed during propagation, to obtain the corresponding coronal intensity data from AIA images. This forecasting sch…
The Sun and Sun-like stars lose angular momentum to their magnetised stellar winds. This braking torque is coupled to the stellar magnetic field, such that changes in the strength and/or geometry of the field modifies the efficiency of this process. Since the space-age, we have been able to directly measure solar wind properties using in-situ spacecraft. Furthermore, indirect proxies such as sunspot number, geomagnetic indices, and cosmogenic radionuclides, constrain the variation of solar wind properties on centennial, and millennial timescales. We use near-Earth measurements of the solar win…
When traveling in the heliosphere, Galactic cosmic rays (GCRs) are subjected to the solar modulation effect, a quasiperiodical change of their intensity caused by the 11-year cycle of solar activity. Here we investigate the association of solar activity and cosmic radiation over five solar cycles, from 1965 to 2020, using a collection of multichannel data from neutron monitors, space missions, and solar observatories. In particular, we focus on the time lag between the monthly sunspot number and the GCR flux variations. We show that the modulation lag is subjected to a 22-year periodical varia…
