Assessment of CESE-HLLD ambient solar wind model results using multipoint observation

Li, Huichao; Feng, Xueshang; Wei, Fengsi

doi:10.1051/swsc/2020048

Cited by 7 publications

(4 citation statements)

References 76 publications

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“…During the declining and minimum phase of solar cycle 23, both PFSS and MHD modeled results driven by GONGb synoptic maps gave satisfying results (e.g., Gressl et al., 2014; Feng et al., 2017; Jian et al., 2016, 2015; Li & Feng, 2018; Li, Feng, & Wei 2020; Li, Feng, Zuo, & Wei 2020; Wiengarten et al., 2014). However, as can be seen here, the GONGb maps do not perform well during the declining phase of solar cycle 24.…”

Section: Summary and Discussionmentioning

confidence: 92%

Comparison of Synoptic Maps and PFSS Solutions for The Declining Phase of Solar Cycle 24

Feng

Wei

2021

JGR Space Physics

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The distributions of the global photospheric magnetic fields are usually provided by synoptic maps. Conventional synoptic maps are constructed by remapping the full-disk magnetgrams into the heliographic Carrington coordinate system. Magnetograms taken throughout a Carrington Rotation (CR) are used to construct one single full-CR synoptic map, which represents the full-surface field during the 27.275-day period. To better approximate the photospheric magnetic field at a specific time, synoptic maps can be updated regularly by fresh observations. Such updated synoptic maps are constructed by simply merging new observation into the maps, or by employing a more sophisticated flux transport model (e.g., Worden & Harvey, 2000). The updated synoptic maps are more favorable for the operational space weather forecast, as the time-evolving nature of the photosphere is better reflected, and fresh observational information can constrain the model through synoptic map input (Cash et al., 2015). Photospheric synoptic maps serve as basic observational input for coronal and heliospheric models to specify their boundary conditions (Gombosi et al., 2018; Wiegelmann et al., 2017; Yeates et al., 2018). Modeled results obtained by using synoptic maps of different sources can differ substantially. For example, Riley et al. (2012) compared solar wind solutions of CR 2060 obtained by the WSA-ENLIL Magnetohydrodynamics (MHD) heliospheric model. The solutions are computed using synoptic maps from Wilcox Solar Observatory (WSO), Michelson Doppler Imager (MDI), Synoptic Optical Longterm Investigations of the Sun (SOLIS), and Global Oscillation Network Group (GONG). While a major high-speed stream is captured by WSO and GONG results, it is missed by MDI and SOLIS results. Hayashi et al. (2016) examined coronal magnetic field structures derived with the potential field source surface (PFSS) model at CR 2044, using synoptic maps from GONG, MDI, Helioseismic and Magnetic Imager (HMI) and Huairou Solar Observing Station (HSOS). The HSOS results compared best with the extreme-ultraviolet (EUV) images, and the HMI results achieved the best agreements with near-Earth in situ data. Despite such comparison efforts, there is no consensus on which kind of synoptic map better represents the distribution of the photospheric

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Section: Summary and Discussionmentioning

confidence: 92%

Comparison of Synoptic Maps and PFSS Solutions for The Declining Phase of Solar Cycle 24

Feng

Wei

2021

JGR Space Physics

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“…For a higher resolution of the rotational discontinuity, we adopt the magnetic tension flux T  proposed in Minoshima et al (2020), which is consistent with the HLLD solver. The HLLD Riemann fan includes six solution states U nL , * U nL , ** U nL , ** U nR , * U nR , and U nR , which are separated by two fast waves, two Alfvén waves, and an entropy wave, respectively (e.g., Miyoshi & Kusano 2005;Miyoshi et al 2010;Fuchs et al 2011b;Guo et al 2016;Li et al 2020).…”

Section: Multistate Low-dissipation Ausm For Decomposed Mhd Equationsmentioning

confidence: 99%

“…In recent decades, 3D physically based magnetohydrodynamic (MHD) simulations of the ambient solar wind with diversified physical temporal and spatial scales have become a critical tool for space weather research (e.g., Usmanov 1993;Mikić et al 1999;Usmanov & Goldstein 2003;Detman et al 2006;Hayashi et al 2006;Dryer 2007;Feng et al 2007;Nakamizo et al 2009;Feng et al 2010Feng et al , 2011bFeng et al , 2012aFeng et al , 2012bFeng et al , 2014aFeng et al , 2014bFeng et al , 2017Lugaz & Roussev 2011;Riley et al 2012;Tóth et al 2012;Zhou et al 2012;Wu & Dryer 2015;Zhou & Feng 2017;Gombosi et al 2018;Feng 2020c;Li et al 2020;Shen et al 2021;Yang et al 2021). Finitevolume methods (FVMs) based on approximate Riemann solvers are popular among these simulations.…”

Section: Introductionmentioning

confidence: 99%

Implicit Solar Coronal Magnetohydrodynamic (MHD) Modeling with a Low-dissipation Hybridized AUSM-HLL Riemann Solver

Wang

Xiang

Liu

et al. 2022

ApJ

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In this paper, we develop a 3D implicit single-fluid magnetohydrodynamic (MHD) model to simulate the steady-state solar corona with a wide range of Mach numbers and low plasma β. We employ a low-dissipation advection upstream splitting method (AUSM) to calculate the convective flux in the regions of low Mach numbers for a high resolution, and hybridize the AUSM with Harten-Lax-van Leer Riemann solver in the regions of high Mach numbers to improve the solver’s robustness. The inner boundary condition of no backflow is implemented by numerical flux. A reconstruction method based on the divergence-free radial basis function is adopted to enhance the divergence-free constraint of magnetic field. Also, an anisotropic thermal conduction term is considered; the positivity-preserving reconstruction method is used to prevent the presence of negative thermal pressure and plasma density, and the implicit lower-upper symmetric Gauss Seidel method is implemented for a better convergence rate. After establishing the implicit solar wind MHD model, we employ it to simulate steady-state solar coronal structures in Carrington rotations 2177 and 2212. The simulations demonstrate that the MHD model’s computational efficiency is desirable, and the modeled results are basically in agreement with the solar coronal observations and the mapped in situ measurements from the OMNI archive. Consequently, this implicit MHD model is promising to simulate a complex plasma environment with high-intensity magnetic field and wide-ranging Mach numbers.

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“…Owens et al (2017) and Henley & Pope (2017) discussed ensemble solar wind forecasts using a "cost-loss" analysis, and Owens (2018) proposed time window approaches to complement traditional point-to-point comparison metrics. Numerous studies have assessed the quality of ambient solar wind models by comparing their solutions to in situ measurements (see, for example, Owens et al, 2008;MacNeice, 2009b;Norquist & Meeks, 2010;Jian et al, 2011;Gressl et al, 2014;Jian et al, 2015Devos et al, 2014;Reiss et al, 2016;Reiss et al, 2019;Hinterreiter et al, 2019;Li et al, 2020;Riley & Ben-Nun, 2021, among others). Other observational tests focus on the Earth to Sun magnetic connectivity (MacNeice et al, 2011), interplanetary scintillation (Kim et al, 2014;Jackson et al, 2015;Gonzi et al, 2021), coronagraph images (Jones et al, 2017;Lamy et al, 2019), and more.…”

Section: Introductionmentioning

confidence: 99%

Unifying the Validation of Ambient Solar Wind Models

Reiss¹,

Muglach²,

Mullinix³

et al. 2022

Preprint

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Progress in space weather research and awareness needs community-wide strategies and procedures to evaluate our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. We aim to bridge the gap between model developers and end-users to provide the community with an assessment of the state-of-the-art in solar wind forecasting. To this end, we develop an open online platform for validating solar wind models by comparing their solutions with in situ spacecraft measurements. The online platform will allow the space weather community to test the quality of state-of-the-art solar wind models with unified metrics providing an unbiased assessment of progress over time. In this study, we propose a metadata architecture and recommend community-wide forecasting goals and validation metrics. We conclude with a status update of the online platform and outline future perspectives.

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Assessment of CESE-HLLD ambient solar wind model results using multipoint observation

Cited by 7 publications

References 76 publications

Comparison of Synoptic Maps and PFSS Solutions for The Declining Phase of Solar Cycle 24

Comparison of Synoptic Maps and PFSS Solutions for The Declining Phase of Solar Cycle 24

Implicit Solar Coronal Magnetohydrodynamic (MHD) Modeling with a Low-dissipation Hybridized AUSM-HLL Riemann Solver

Unifying the Validation of Ambient Solar Wind Models

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