Global solar wind variations over the last four centuries.
TL;DR: The first quantitative estimate of global solar wind variations over the last 400 years is produced using nearly 30 years of output from a data-constrained magnetohydrodynamic model of the solar corona to calibrate heliospheric reconstructions based solely on sunspot observations.
Abstract: The most recent “grand minimum” of solar activity, the Maunder minimum (MM, 1650–1710), is of great interest both for understanding the solar dynamo and providing insight into possible future heliospheric conditions. Here, we use nearly 30 years of output from a data-constrained magnetohydrodynamic model of the solar corona to calibrate heliospheric reconstructions based solely on sunspot observations. Using these empirical relations, we produce the first quantitative estimate of global solar wind variations over the last 400 years. Relative to the modern era, the MM shows a factor 2 reduction in near-Earth heliospheric magnetic field strength and solar wind speed, and up to a factor 4 increase in solar wind Mach number. Thus solar wind energy input into the Earth’s magnetosphere was reduced, resulting in a more Jupiter-like system, in agreement with the dearth of auroral reports from the time. The global heliosphere was both smaller and more symmetric under MM conditions, which has implications for the interpretation of cosmogenic radionuclide data and resulting total solar irradiance estimates during grand minima.
Citations
More filters
TL;DR: Observations and theory of magnetism in the Sun and other stars are reviewed, with a partial focus on the “Solar-stellar connection”: ways in which studies of other stars have influenced the authors' understanding of theSun and vice versa.
Abstract: The Sun and other stars are magnetic: magnetism pervades their interiors and affects their evolution in a variety of ways In the Sun, both the fields themselves and their influence on other phenomena can be uncovered in exquisite detail, but these observations sample only a moment in a single star's life By turning to observations of other stars, and to theory and simulation, we may infer other aspects of the magnetism-eg, its dependence on stellar age, mass, or rotation rate-that would be invisible from close study of the Sun alone Here, we review observations and theory of magnetism in the Sun and other stars, with a partial focus on the "Solar-stellar connection": ie, ways in which studies of other stars have influenced our understanding of the Sun and vice versa We briefly review techniques by which magnetic fields can be measured (or their presence otherwise inferred) in stars, and then highlight some key observational findings uncovered by such measurements, focusing (in many cases) on those that offer particularly direct constraints on theories of how the fields are built and maintained We turn then to a discussion of how the fields arise in different objects: first, we summarize some essential elements of convection and dynamo theory, including a very brief discussion of mean-field theory and related concepts Next we turn to simulations of convection and magnetism in stellar interiors, highlighting both some peculiarities of field generation in different types of stars and some unifying physical processes that likely influence dynamo action in general We conclude with a brief summary of what we have learned, and a sampling of issues that remain uncertain or unsolved
257 citations
Cites background from "Global solar wind variations over t..."
...Note that attempts to reconstruct the solar wind conditions over the past four centuries have also been pursued by Owens et al. (2017)....
[...]
TL;DR: In this article, a simplified solar-wind model is proposed to estimate CME arrival time in approximately 0.01 seconds on a modest desktop computer and thus enables significantly larger ensembles.
Abstract: Near-Earth solar-wind conditions, including disturbances generated by coronal mass ejections (CMEs), are routinely forecast using three-dimensional, numerical magnetohydrodynamic (MHD) models of the heliosphere. The resulting forecast errors are largely the result of uncertainty in the near-Sun boundary conditions, rather than heliospheric model physics or numerics. Thus ensembles of heliospheric model runs with perturbed initial conditions are used to estimate forecast uncertainty. MHD heliospheric models are relatively cheap in computational terms, requiring tens of minutes to an hour to simulate CME propagation from the Sun to Earth. Thus such ensembles can be run operationally. However, ensemble size is typically limited to $10^{1}$ to $10^{2}$ members, which may be inadequate to sample the relevant high-dimensional parameter space. Here, we describe a simplified solar-wind model that can estimate CME arrival time in approximately 0.01 seconds on a modest desktop computer and thus enables significantly larger ensembles. It is a one-dimensional, incompressible, hydrodynamic model, which has previously been used for the steady-state solar wind, but it is here used in time-dependent form. This approach is shown to adequately emulate the MHD solutions to the same boundary conditions for both steady-state solar wind and CME-like disturbances. We suggest it could serve as a “surrogate” model for the full three-dimensional MHD models. For example, ensembles of $10^{5}$ to $10^{6}$ members can be used to identify regions of parameter space for more detailed investigation by the MHD models. Similarly, the simplicity of the model means it can be rewritten as an adjoint model, enabling variational data assimilation with MHD models without the need to alter their code. The model code is available as an Open Source download in the Python language.
53 citations
Cites methods from "Global solar wind variations over t..."
...We now expand this same analysis to the whole 40+ year period for which steady-state HelioMAS solutions are available (i.e. the data set used by Owens, Lockwood, and Riley, 2017)....
[...]
TL;DR: In this paper, the effect of missing data is investigated by introducing synthetic gaps into near-continuous data and the best method for dealing with them when deriving the coupling function, is formally defined using P_{\alpha}, and it is shown that gaps in data recorded before 1995 have introduced considerable errors into coupling functions.
Abstract: Different terrestrial space weather indicators (such as geomagnetic indices, transpolar voltage, and ring current particle content) depend on different “coupling functions” (combinations of near-Earth solar wind parameters) and previous studies also reported a dependence on the averaging timescale, {\tau} We study the relationships of the am and SME geomagnetic indices to the power input into the magnetosphere P_{\alpha}, estimated using the optimum coupling exponent {\alpha} for a range of {\tau} between 1 min and 1 year The effect of missing data is investigated by introducing synthetic gaps into near-continuous data and the best method for dealing with them when deriving the coupling function, is formally defined Using P_{\alpha}, we show that gaps in data recorded before 1995 have introduced considerable errors into coupling functions From the near-continuous solar wind data for 1996-2016, we find {\alpha} = 044 plus/minus 002 and no significant evidence that {\alpha} depends on {\tau}, yielding P_{\alpha} = B^088 Vsw^190 (mswNsw)^023 sin4({\theta}/2), where B is the Interplanetary Magnetic Field (IMF), Nsw the solar wind number density, msw its mean ion mass, Vsw its velocity and {\theta} is the IMF clock angle in the Geocentric Solar Magnetospheric reference frame Values of P_{\alpha} that are accurate to within plus/minus 5% for 1996-2016 have an availability of 838% and the correlation between P_{\alpha} and am for these data is shown to be 0990 (between 0972 and 0997 at the 2{\sigma} uncertainty level), 0897 plus/minus 0004, and 0790 plus/minus 003, for {\tau} of 1 year, 1 day and 3 hours, respectively, and that between P_{alpha} and SME at {\tau} of 1 min is 07046 plus/minus 00004
42 citations
Cites background from "Global solar wind variations over t..."
...…have estimated the annual mean power input into the magnetosphere for all years back to 1612 from the reconstructed solar wind and interplanetary field parameters derived by Owens et al. (2017), and from this Lockwood et al. (2018a) have derived the annual means of Ap and AE back to this date....
[...]
TL;DR: In this paper, the role of human activity in recent global warming was calculated by fitting the residuals to the UN IPCC's recommended anthropogenic forcings time series, and the contribution from direct solar forcing for all 16 estimates of TSI was evaluated using simple linear least squares fitting.
Abstract: To evaluate the role of Total Solar Irradiance (TSI) on Northern Hemisphere (NH) surface air temperature trends it is important to have reliable estimates of both quantities. 16 different TSI estimates were compiled from the literature. 1/2 of these estimates are low variability and 1/2 are high variability. 5 largely-independent methods for estimating NH temperature trends were evaluated using: 1) only rural weather stations; 2) all available stations whether urban or rural (the standard approach); 3) only sea surface temperatures; 4) tree-ring temperature proxies; 5) glacier length temperature proxies. The standard estimates using urban as well as rural stations were anomalous as they implied a much greater warming in recent decades than the other estimates. This suggests urbanization bias might still be a problem in current global temperature datasets despite the conclusions of some earlier studies. Still, all 5 estimates confirm it is currently warmer than the late 19th century, i.e., there has been some global warming since 1850. For the 5 estimates of NH temperatures, the contribution from direct solar forcing for all 16 estimates of TSI was evaluated using simple linear least-squares fitting. The role of human activity in recent warming was then calculated by fitting the residuals to the UN IPCC's recommended anthropogenic forcings time series. For all 5 NH temperature series, different TSI estimates implied everything from recent global warming being mostly human-caused to it being mostly natural. It seems previous studies (including the most recent IPCC reports) that had prematurely concluded the former failed to adequately consider all the relevant estimates of TSI and/or to satisfactorily address the uncertainties still associated with NH temperature trend estimates. Several recommendations are provided on how future research could more satisfactorily resolve these issues.
32 citations
References
More filters
[...]
TL;DR: In the years around a sunspot maximum there is seldom a day when a number of spots cannot be seen, and often hundreds are present.
Abstract: zero. In contrast, in the years around a sunspot maximum there is seldom a day when a number of spots cannot be seen, and often hundreds are present. Past counts of sunspot number are readily available from the year 1700 (3), [m and workers in solar and terrestrial studies often use the record as though it were of of uniform quality. In fact, it is not. Thus it is advisable, from time to time, to
1,853 citations
TL;DR: In this paper, the authors analyzed hourly averaged interplanetary magnetic field (IMF) and plasma data from the Advanced Composition Explorer (ACE) and Wind spacecraft, generated from 1 to 4 min resolution data time-shifted to Earth.
Abstract: [1] Hourly averaged interplanetary magnetic field (IMF) and plasma data from the Advanced Composition Explorer (ACE) and Wind spacecraft, generated from 1 to 4 min resolution data time-shifted to Earth have been analyzed for systematic and random differences. ACE moments-based proton densities are larger than Wind/Solar Wind Experiment (SWE) fits-based densities by up to 18%, depending on solar wind speed. ACE temperatures are less than Wind/SWE temperatures by up to ∼25%. ACE densities and temperatures were normalized to equivalent Wind values in National Space Science Data Center's creation of the OMNI 2 data set that contains 1963–2004 solar wind field and plasma data and other data. For times of ACE-Wind transverse separations <60 RE, random differences between Wind values and normalized ACE values are ∼0.2 nT for ∣B∣, ∼0.45 nT for IMF Cartesian components, ∼5 km/s for flow speed, and ∼15 and ∼30% for proton densities and temperatures. These differences grow as a function of transverse separation more rapidly for IMF parameters than for plasma parameters. Autocorrelation analyses show that spatial scales become progressively shorter for the parameter sequence: flow speed, IMF magnitude, plasma density and temperature, IMF X and Y components, and IMF Z component. IMF variations have shorter scales at solar quiet times than at solar active times, while plasma variations show no equivalent solar cycle dependence.
1,062 citations
TL;DR: In this paper, several different mathematical methods are described which use the observed line-of-sight component of the photospheric magnetic field to determine the magnetic field of the solar corona in the current-free approximation.
Abstract: Several different mathematical methods are described which use the observed line-of-sight component of the photospheric magnetic field to determine the magnetic field of the solar corona in the current-free (or potential-field) approximation. Discussed are (1) a monopole method, (2) a Legendre polynomial expansion assuming knowledge of the radial photospheric magnetic field, (3) a Legendre polynomial expansion obtained from the line-of-sight photospheric field by a least-meansquare technique, (4) solar wind simulation by zero-potential surfaces in the corona, (5) corrections for the missing flux due to magnetograph saturation. We conclude (1) that the field obtained from the monopole method is not consistent with the given magnetic data because of non-local effects produced by monopoles on a curved surface, (2) that the field given by a Legendre polynomial (which is fitted to the measured line-of-sight magnetic field) is a rigorous and self-consistent solution with respect to the available data, (3) that it is necessary to correct for the saturation of the magnetograph (at about 80 G) because fields exceeding 80 G provide significant flux to the coronal field, and (4) that a zero-potential surface at 2.5 solar radii can simulate the effect of the solar wind on the coronal magnetic field.
1,018 citations
TL;DR: A reconstruction of the sunspot number covering the past 11,400 years is reported, based on dendrochronologically dated radiocarbon concentrations, and it is pointed out that solar variability is unlikely to have been the dominant cause of the strong warming during the past three decades.
Abstract: Direct observations of sunspot numbers are available for the past four centuries1,2, but longer time series are required, for example, for the identification of a possible solar influence on climate and for testing models of the solar dynamo. Here we report a reconstruction of the sunspot number covering the past 11,400 years, based on dendrochronologically dated radiocarbon concentrations. We combine physics-based models for each of the processes connecting the radiocarbon concentration with sunspot number. According to our reconstruction, the level of solar activity during the past 70 years is exceptional, and the previous period of equally high activity occurred more than 8,000 years ago. We find that during the past 11,400 years the Sun spent only of the order of 10% of the time at a similarly high level of magnetic activity and almost all of the earlier high-activity periods were shorter than the present episode. Although the rarity of the current episode of high average sunspot numbers may indicate that the Sun has contributed to the unusual climate change during the twentieth century, we point out that solar variability is unlikely to have been the dominant cause of the strong warming during the past three decades3.
883 citations