Abstract:Both coronal holes and active regions are source regions of the solar wind. The distribution of these coronal structures across both space and time is well known, but it is unclear how much each source contributes to the solar wind. In this study we use photospheric magnetic field maps observed over the past four solar cycles to estimate what fraction of magnetic open solar flux is rooted in active regions, a proxy for the fraction of all solar wind originating in active regions. We find that the fractional co… Show more
“…The input magnetogram is preprocessed by a projection on spherical harmonics and a selection of a maximum frequency for the reconstruction (noted as ℓ max and fixed to 15 in this case), which is equivalent to a smoothing of the map to remove the small intense structures. These structures are indeed numerically more challenging, while their contribution to the overall structure of the wind at 0.1 au is not clear: for the velocities, they can have a strong impact on the distribution between slow and fast wind (but this is not very relevant for a polytropic wind); for the magnetic field, the dipolar mode is going to become more and more dominant farther away from the star, thus reducing the impact of small-scale magnetic structures (Samara et al 2021;Stansby et al 2021).…”
Section: The General Case: Data-driven Coronal Modelsmentioning
We present a novel global 3D coronal MHD model called COCONUT, polytropic in its first stage and based on a time-implicit backward Euler scheme. Our model boosts run-time performance in comparison with contemporary MHD-solvers based on explicit schemes, which is particularly important when later employed in an operational setting for space-weather forecasting. It is data-driven in the sense that we use synoptic maps as inner boundary inputs for our potential-field initialization as well as an inner boundary condition in the further MHD time evolution. The coronal model is developed as part of the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) and will replace the currently employed, more simplistic, empirical Wang–Sheeley–Arge (WSA) model. At 21.5 R
⊙ where the solar wind is already supersonic, it is coupled to EUHFORIA’s heliospheric model. We validate and benchmark our coronal simulation results with the explicit-scheme Wind-Predict model and find good agreement for idealized limit cases as well as real magnetograms, while obtaining a computational time reduction of up to a factor 3 for simple idealized cases, and up to 35 for realistic configurations, and we demonstrate that the time gained increases with the spatial resolution of the input synoptic map. We also use observations to constrain the model and show that it recovers relevant features such as the position and shape of the streamers (by comparison with eclipse white-light images), the coronal holes (by comparison with EUV images), and the current sheet (by comparison with WSA model at 0.1 au).
“…The input magnetogram is preprocessed by a projection on spherical harmonics and a selection of a maximum frequency for the reconstruction (noted as ℓ max and fixed to 15 in this case), which is equivalent to a smoothing of the map to remove the small intense structures. These structures are indeed numerically more challenging, while their contribution to the overall structure of the wind at 0.1 au is not clear: for the velocities, they can have a strong impact on the distribution between slow and fast wind (but this is not very relevant for a polytropic wind); for the magnetic field, the dipolar mode is going to become more and more dominant farther away from the star, thus reducing the impact of small-scale magnetic structures (Samara et al 2021;Stansby et al 2021).…”
Section: The General Case: Data-driven Coronal Modelsmentioning
We present a novel global 3D coronal MHD model called COCONUT, polytropic in its first stage and based on a time-implicit backward Euler scheme. Our model boosts run-time performance in comparison with contemporary MHD-solvers based on explicit schemes, which is particularly important when later employed in an operational setting for space-weather forecasting. It is data-driven in the sense that we use synoptic maps as inner boundary inputs for our potential-field initialization as well as an inner boundary condition in the further MHD time evolution. The coronal model is developed as part of the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) and will replace the currently employed, more simplistic, empirical Wang–Sheeley–Arge (WSA) model. At 21.5 R
⊙ where the solar wind is already supersonic, it is coupled to EUHFORIA’s heliospheric model. We validate and benchmark our coronal simulation results with the explicit-scheme Wind-Predict model and find good agreement for idealized limit cases as well as real magnetograms, while obtaining a computational time reduction of up to a factor 3 for simple idealized cases, and up to 35 for realistic configurations, and we demonstrate that the time gained increases with the spatial resolution of the input synoptic map. We also use observations to constrain the model and show that it recovers relevant features such as the position and shape of the streamers (by comparison with eclipse white-light images), the coronal holes (by comparison with EUV images), and the current sheet (by comparison with WSA model at 0.1 au).
“…In each of these configurations, energy is channelled from the convection into the low-corona. Coronal holes are the dominant source of the solar wind in the Heliosphere (Cranmer et al 2017;Stansby et al 2021), typically producing the fast solar wind (McComas et al 2008;Ebert et al 2009;Macneil et al 2020a;Wang 2020). The magnetic field configuration of a coronal hole is relatively simple, compared with the quiet sun and active regions, given that the field is principally open to the solar wind (Lowder et al 2017;Hofmeister et al 2019).…”
Context. Current models of the solar wind must approximate (or ignore) the small-scale dynamics within the solar atmosphere, however these are likely important in shaping the emerging wave-turbulence spectrum and ultimately heating/accelerating the coronal plasma.Aims. This study strives to make connections between small-scale vortex motions at the base of the solar wind and the resulting heating/acceleration of coronal plasma. Methods. The Bifrost code produces realistic simulations of the solar atmosphere that facilitate the analysis of spatial and temporal scales which are currently at, or beyond, the limit of modern solar telescopes. For this study, the Bifrost simulation is configured to represent the solar atmosphere in a coronal hole region, from which the fast solar wind emerges. The simulation extends from the upper-convection zone (2.5 Mm below the photosphere) to the low-corona (14.5 Mm above the photosphere), with a horizontal extent of 24 Mm x 24 Mm. The network of magnetic funnels in the computational domain influence the movement of plasma, and the propagation of magnetohydrodynamic waves, into the low-corona.Results. The twisting of the coronal magnetic field by photospheric flows, efficiently injects energy into the low-corona. Poynting fluxes of up to 2 − 4 kWm −2 are commonly observed inside twisted magnetic structures with diameters in the low-corona of 1-5 Mm. Torsional Alfvén waves are favourably transmitted along these structures, and will subsequently escape into the solar wind. However, reflections of these waves from the upper boundary condition make it difficult to unambiguously quantify the emerging Alfvén wave-energy flux. Conclusions. This study represents a first step in quantifying the conditions at the base of the solar wind using Bifrost simulations. It is shown that the coronal magnetic field is readily braided and twisted by photospheric flows. Temperature and density contrasts form between regions with active stirring motions and those without. Stronger whirlpool-like flows in the convection, concurrent with magnetic concentrations, launch torsional Alfvén waves up through the magnetic funnel network, which are expected to enhance the turbulent generation of magnetic switchbacks in the solar wind.
“…The input magnetogram is pre-processed by a projection on spherical harmonics and a selection of a maximum frequency for the reconstruction (noted as max and fixed to 15 in this case), which is equivalent to a smoothing of the map to remove the small intense structures. These structures are indeed numerically more challenging, while their contribution to the overall structure of the wind at 0.1 AU is not clear: for the velocities, they can have a strong impact on the distribution between slow and fast wind (but this is not very relevant for a polytropic wind); for the magnetic field, the dipolar mode is going to become more and more dominant further away from the star, thus reducing the impact of small scale magnetic structures (Samara, E. et al 2021;Stansby et al 2021).…”
Section: The General Case: Data-driven Coronal Modelsmentioning
We present a novel global 3-D coronal MHD model called COCONUT, polytropic in its first stage and based on a time-implicit backward Euler scheme. Our model boosts run-time performance in comparison with contemporary MHD-solvers based on explicit schemes, which is particularly important when later employed in an operational setting for space weather forecasting. It is data-driven in the sense that we use synoptic maps as inner boundary input for our potential field initialization as well as an inner boundary condition in the further MHD time evolution. The coronal model is developed as part of the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) and will replace the currently employed, more simplistic, empirical Wang-Sheeley-Arge (WSA) model. At 21.5 R where the solar wind is already supersonic, it is coupled to EUHFORIA's heliospheric model. We validate and benchmark our coronal simulation results with the explicit-scheme Wind-Predict model and find good agreement for idealized limit cases as well as real magnetograms, while obtaining a computational time reduction of up to a factor 3 for simple idealized cases, and up to 35 for realistic configurations, and we demonstrate that the time gained increases with the spatial resolution of the input synoptic map. We also use observations to constrain the model and show that it recovers relevant features such as the position and shape of the streamers (by comparison with eclipse white-light images), the coronal holes (by comparison with EUV images) and the current sheet (by comparison with WSA model at 0.1 AU).
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