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At least 109 records · Page 6

Evolution of X-Ray Activity in <25 Myr Old Pre-main Sequence Stars

Measuring the evolution of X-ray emission from pre-main-sequence (PMS) stars gives insight into two issues: the response of magnetic dynamo processes to changes in the interior structure, and the effects of high-energy radiation on protoplanetary disks and primordial planetary atmospheres. We present a sample of 6003 stars with ages 7–25 Myr in 10 nearby open clusters from Chandra X-ray and Gaia-EDR3 surveys. Combined with previous results in large samples of younger (≲5 Myr) stars in MYStIX and SFiNCs star-forming regions, mass-stratified activity-age relations are derived for the early phases of stellar evolution. X-ray luminosity (LX) is constant during the first few Myr, possibly due to the presence of extended X-ray coronas insensitive to temporal changes in stellar size. LX then decays during the 7–25 Myr period, more rapidly as stellar mass increases. This decay is interpreted as decreasing efficiency of the α2 dynamo as radiative cores grow and a solar-type αΩ dynamo emerges. For more massive 3.5–7 M⊙ fully radiative stars, the X-ray emission plummets—indicating the lack of an effective magnetic dynamo. The findings provide improved measurements of high-energy radiation effects on circumstellar material, first for the protoplanetary disk and then for the atmospheres of young planets. The observed X-ray luminosities can be so high that an inner Earth-mass rocky, unmagnetized planet around a solar-mass PMS star might lose its primary and secondary atmospheres within a few (several) million years. PMS X-ray emission may thus have a significant impact on the evolution of early-planetary atmospheres and the conditions promoting the rise of habitability.

Konstantin V Getman↗

Using Data Assimilation Methods for Prediction of Solar Activity

The variability of solar magnetic activity known as the 11-­‐year solar cycles has the longest history of observations. These solar cycles dramatically affect conditions in the heliosphere and the Earth’s space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-­‐term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model complemented by the equation of magnetic helicity conservation and long-­‐term sunspot data series. This approach has allowed us to reproduce the general properties of the solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Solar Activity↗

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗

Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty in the long-range predictions remains, requiring future monitoring, we do not expect the next cycle's + 2-sigma value will rise significantly above solar cycle #23's activity level.

Richon, K.↗

Why the observed spin evolution of older-than-solar-like stars might not require a dynamo mode change

ABSTRACT The spin evolution of main-sequence stars has long been of interest for basic stellar evolution, stellar ageing, stellar activity, and consequent influence on companion planets. Observations of older-than-solar late-type main-sequence stars have been interpreted to imply that a change from a dipole-dominated magnetic field to one with more prominent higher multipoles might be necessary to account for the data. The spin-down models that lead to this inference are essentially tuned to the Sun. Here, we take a different approach that considers individual stars as fixed points rather than just the Sun. We use a time-dependent theoretical model to solve for the spin evolution of low-mass main-sequence stars that includes a Parker-type wind and a time-evolving magnetic field coupled to the spin. Because the wind is exponentially sensitive to the stellar mass over radius and the coronal base temperature, the use of each observed star as a separate fixed point is more appropriate and, in turn, produces a set of solution curves that produces a solution envelope rather than a simple line. This envelope of solution curves, unlike a single line fit, is consistent with the data and does not unambiguously require a modal transition in the magnetic field to explain it.

Astronomy & Astrophysics↗

Electrodynamics of solar wind-magnetosphere-ionosphere interactions

The paper presents a coherent picture of fundamental physical processes in three basic elements of the solar-wind/magnetosphere/ionosphere coupling system: (1) the field-aligned potential structure which leads to the formation of auroral arcs, (2) the magnetosphere-ionosphere coupling which leads to the onset of magnetospheric substorms, and (3) the solar-wind/magnetosphere dynamo which supplies the power driving various magnetospheric processes. Process (1) is forced into existence by the loss-cone constriction effect when the upward field-aligned current density exceeds the loss-cone thermal flux limit. Substorm onset occurs when the ionosphere responds fully to the enhanced magnetospheric convection driven by the solar wind. Energy is transferred from the solar wind to the magnetosphere by a dynamo process, primarily on open field lines.

Kan, Joseph R.↗

Preface for frontiers of magnetic reconnection research in heliophysical, astrophysical, and laboratory plasmas

Magnetic reconnection—the topological rearrangement of magnetic field—underlies many explosive phenomena across a wide range of natural and laboratory plasmas.3 It plays a pivotal role in electron and ion heating, particle acceleration to high energies, energy transport, and self-organization. Reconnection can have a complex relationship with turbulence at both large and small scales, leading to various effects that are only beginning to be understood. In heliophysics, magnetic reconnection plays a key role in solar flares, coronal mass ejections, coronal heating, solar wind dissipation, the interaction of interplanetary plasma with magnetospheres, dynamics of planetary magnetospheres such as magnetic substorms, and the heliospheric boundary with the interstellar medium. Here, the magnetic reconnection is integral to the solar and planetary dynamo processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Solar Cycle Predictions Near Sunspot Minimum

Observations of solar magnetic activity and the dynamics of the solar convection zone have produced severe constraints on models of the Sun's magnetic dynamo. These constraints are so severe that, at present, we do not have numerical models that can accept the current conditions and then march forward in time to predict future activity. Given this state of solar dynamo theory we are forced to examine previous behavior to discover patterns and trends that afford us some measure of predictability. Here we examine the behavior of several indicators of solar activity near solar minimum that are well correlated with the amplitude of the following solar maximum to predict the level of solar activity over cycle 23. Sunspot numbers, areas, and positions are useful for characterizing solar cycle behavior due to the extent of the data (12 cycles or more). These data exhibit several patterns that relate future activity to past behavior. With the Odd-Even effect the odd numbered cycles have been larger than their even numbered predecessors for each of the last six cycle pairs. With the Amplitude-Period effect short period cycles have been followed by large amplitude cycles and long period cycles have been followed by small amplitude cycles for 10 of the last 13 cycles. With the Maximum-Minimum effect the sunspot number at minimum is directly correlated with the sunspot number at maximum for a given cycle. The geomagnetic indices aa and Ap are also related to solar activity by the connections between disturbances in the solar wind and variations in the Earth's magnetic field. Like the Maximum-Minimum effect for sunspots, the size of the aa and Ap indices at minimum are directly related to the amplitude of the following maximum. The number of geomagnetically disturbed days (days with Ap >= 25) over the course of a cycle is another indicator for the size of the next cycle. The aa and Ap indices can each be separated into a component in phase with the current sunspot cycle and an "extended cycle" component that is directly related to the following cycle. Individually each of these indicators provides some measure of predictive ability for the amplitudes of previous cycles. Taken in combination we find that the predictions are much more accurate. Our multi-variate analysis indicates that a maximum sunspot number of 160 +/- 20 should occur near the end of 1999 for cycle 23.

Hathaway, David H.↗

Lunar surface magnetometer experiment

The Apollo 16 lunar surface magnetometer (LSM) activation completed the network installation of magnetic observatories on the lunar surface and initiated simultaneous measurements of the global response of the moon to large-scale solar and terrestrial magnetic fields. Fossil remanent magnetic fields have been measured at nine locations on the lunar surface, including the Apollo 16 LSM site in the Descartes highlands area. This fossil record indicates the possible existence of an ancient lunar dynamo or a solar or terrestrial field much stronger than exists at present. The experimental technique and operation of the LSM are described and the results obtained are discussed.

Dyal, P.↗

Using dynamo theory to predict the sunspot number during solar cycle 21

On physical grounds it is suggested that the polar field strength of the sun near a solar minimum is closely related to the solar activity of the following cycle. Four methods of estimating the polar magnetic field strength of the sun near solar minimum are employed to provide an estimate of the yearly mean sunspot number of cycle 21 at solar maximum of 140 + or - 20. This estimate may be considered a first-order attempt to predict the cycle activity using one parameter of physical importance based upon dynamo theory.

Schatten, K. H.↗

Solar Activity Forecasting for use in Orbit Prediction

Orbital prediction for satellites in low Earth orbit (LEO) or low planetary orbit depends strongly on exospheric densities. Solar activity forecasting is important in orbital prediction, as the solar UV and EUV inflate the upper atmospheric layers of the Earth and planets, forming the exosphere in which satellites orbit. Geomagnetic effects also relate to solar activity. Because of the complex and ephemeral nature of solar activity, with different cycles varying in strength by more than 100%, many different forecasting techniques have been utilized. The methods range from purely numerical techniques (essentially curve fitting) to numerous oddball schemes, as well as a small subset, called 'Precursor techniques.' The situation can be puzzling, owing to the numerous methodologies involved, somewhat akin to the numerous ether theories near the turn of the last century. Nevertheless, the Precursor techniques alone have a physical basis, namely dynamo theory, which provides a physical explanation for why this subset seems to work. I discuss this solar cycle's predictions, as well as the Sun's observed activity. I also discuss the SODA (Solar Dynamo Amplitude) index, which provides the user with the ability to track the Sun's hidden, interior dynamo magnetic fields. As a result, one may then update solar activity predictions continuously, by monitoring the solar magnetic fields as they change throughout the solar cycle. This paper ends by providing a glimpse into what the next solar cycle (#24) portends.

Schatten, Kenneth↗

A Floor in the Sun's Photospheric Magnetic Field: Implications for an Independent Small-scale Dynamo

Clette recently showed that F 10.7 systematically approaches a quiet Sun daily value of 67 solar flux units (sfu) at solar minima as the number of spotless days on the Sun increases. Previously, a floor of ∼2.8 nT had been proposed for the solar wind (SW) magnetic field strength (B). F 10.7 , which closely tracks the Sun's unsigned photospheric magnetic flux, and SW B exhibit different relationships to their floors at 11 yr solar minima during the last ∼50 yr. While F 10.7 approaches 67 sfu at each minimum, the corresponding SW B is offset above ∼2.8 nT by an amount approximately proportional to the solar polar field strength—which varied by a factor of ∼2.5 during this interval. This difference is substantiated by ∼130 yr of reconstructed F 10.7 (via the range of the diurnal variation of the East-component (rY) of the geomagnetic field) and SW B (based on the interdiurnal variability geomagnetic activity index). For the last ∼60 yr, the contribution of the slow SW to SW B has exhibited a floor-like behavior at ∼2 nT, in contrast to the contributions of coronal mass ejections and high-speed streams that vary with the solar cycle. These observations, as well as recent SW studies based on Parker Solar Probe and Solar Dynamics Observatory data, suggest that (1) the Sun has a small-scale turbulent dynamo that is independent of the 11 yr sunspot cycle; and (2) the small-scale magnetic fields generated by this nonvarying turbulent dynamo maintain a constant open flux carried to the heliosphere by the Sun's floor-like slow SW.

Solar magnetic fields↗

The stretching of magnetic flux tubes in the convective overshoot region

The present study examines the fate of a magnetic flux tube initially lying at the bottom of the solar convective overshoot region. Stretching of the flux tube, e.g., by differential rotation, reduces its density, causing it to rise quasi-statically (a process referred to as vertical flux drift) until it reaches the top of the overshoot region and enters the buoyantly unstable convection region, from which a portion of it may ultimately protrude to form an active region on the surface. It is suggested that vertical flux drift and flux destabilization are inevitable consequences of field amplification, and it is surmised that these phenomena should be considered in self-consistent models of solar and stellar dynamos operating in the overshoot region.

Fisher, George H.↗

Clustering of Emerging Flux

Observations show that newly emerging flux tends to appear on the Solar surface at sites where there is flux already. This results in clustering of solar activity. Standard dynamo theories do not predict this effect.

Flux Cluster dynamo↗

Activity Cycles in Stars

Starspots and stellar activity can be detected in other stars using high precision photometric and spectrometric measurements. These observations have provided some surprises (starspots at the poles - sunspots are rarely seen poleward of 40 degrees) but more importantly they reveal behaviors that constrain our models of solar-stellar magnetic dynamos. The observations reveal variations in cycle characteristics that depend upon the stellar structure, convection zone dynamics, and rotation rate. In general, the more rapidly rotating stars are more active. However, for stars like the Sun, some are found to be inactive while nearly identical stars are found to be very active indicating that periods like the Sun's Maunder Minimum (an inactive period from 1645 to 1715) are characteristic of Sun-like stars.

Hathaway, David H.↗

The Solar Clock

The Sun is powered by a very stable source of fusion energy in its core that radiates that energy outward in a constant flow. Yet it has a cycle of magnetic dynamo activity whose strength and duration are variable. This variability, which affects the Earth's ‘space climate', points to temporal changes in the convective and diffusive transport of magnetic flux above the tachocline, where the flux is generated. The longest record we have of this variability is the time series of Sunspot Numbers (SSN). This record suggests that the interior of the Sun follows a clocklike magnetic flux production cycle with a length of close to 11.05 yr. The variations in sunspot cycle duration, as well as the sunspot number rise and fall times, their hemispheric asymmetries, and the maximum sunspot numbers of the individual cycles, are likely produced in the process of the magnetic flux transport. Helioseismology continues to shed more light on the convection zone variabilities, including the ‘torsional oscillations' that seem to have a special connection to the emerging strong magnetic fluxes that produce the sunspots. These new observations may eventually lead to an explanation for the surprisingly good correlation between the rate of sunspot appearance and the maximum sunspot number, and to a better understanding of the relationship between the solar dynamo and the sunspot number cycle. Better understanding of the polar regions awaits long-term monitoring with a polar solar mission. Better predictions of nearterm space weather could be obtained from a permanent L5 monitor.

C T Russell↗