Validation for solar wind prediction at Earth: Comparison of coronal and heliospheric models installed at the CCMC

Abstract

Multiple coronal and heliospheric models have been recently upgraded at the Community Coordinated Modeling Center (CCMC), including the Wang-Sheeley-Arge (WSA)-Enlil model, MHD-Around-a-Sphere (MAS)-Enlil model, Space Weather Modeling Framework (SWMF), and heliospheric tomography using interplanetary scintillation data. To investigate the effects of photospheric magnetograms from different sources, different coronal models, and different model versions on the model performance, we run these models in 10 combinations. Choosing seven Carrington rotations in 2007 as the time window, we compare the modeling results with the Operating Mission as Nodes on the Internet data for near-Earth space environment during the late declining phase of solar cycle 23. Visual comparison is proved to be a necessary addition to the quantitative assessment of the models' capabilities in reproducing the time series and statistics of solar wind parameters. The MAS-Enlil model captures the time patterns of solar wind parameters better, while the WSA-Enlil model matches with the time series of normalized solar wind parameters better. Models generally overestimate slow wind temperature and underestimate fast wind temperature and magnetic field. Using improved algorithms, we have identified magnetic field sector boundaries (SBs) and slow-to-fast stream interaction regions (SIRs) as focused structures. The success rate of capturing them and the time offset vary largely with models. For this quiet period, the new version of MAS-Enlil model works best for SBs, while heliospheric tomography works best for SIRs. The new version of SWMF with more physics added needs more development. General strengths and weaknesses for each model are diagnosed to provide an unbiased reference to model developers and users. MotivationWe are motivated to validate the coronal and heliospheric models for the quasi-steady solar wind from the following three respects. First, a stream interaction region (SIR) forms when fast wind overtakes and interacts with the proceeding slow wind. It is in nature the same as the commonly known corotating interaction region [e.g., Smith and Wolfe, 1976;Gosling and Pizzo, 1999]. However, we use SIRs to emphasize that when the solar background changes within one Carrington rotation (CR), the resultant SIRs are short lived and do not corotate with the Sun to recur. In fact, Jian et al. [2006, 2011a] find 51% of SIRs near solar maximum and 10% at solar minimum do not recur at Earth. Large-amplitude Alfvén waves [Belcher and Davis, 1971] in SIRs and the following fast wind can drive a series of particle injections and affect the evolution of outer radiation belt (centered at about 4 R E ), as demonstrated in Miyoshi and Kataoka [2005]. Additionally, in geomagnetic storms, a large amount of energy is transferred from the solar wind into the magnetosphere and eventually dissipated in the thermosphere (about 90-600 km aboveground) and ionosphere (about 60-1000 km aboveground) by Joule heating and auroral precipitation [e.g., Gonzal...

Continuous solar wind forcing knowledge: Providing continuous conditions at Mars with the WSA‐ENLIL + Cone model

“…Compared to the performance at 1 AU of other coronal and heliospheric models installed at the CCMC, Jian et al . [] found that WSA‐ENLIL used with GONG magnetograms matches the median solar wind density the best and can capture the time series of normalized solar wind parameters well. In contrast, Jian et al .…”

“…In contrast, Jian et al . [] found that the weaknesses of the model at 1 AU include underestimating maximum density, maximum temperature, and maximum IMF strength, and overestimating slow solar wind speed and temperature. Gressl et al .…”

Data‐driven modeling of the solar wind from 1 Rs to 1 AU

“…For comparative analyses of current three‐dimensional numerical solar wind models, the readers may refer to Wu and Dryer []. Alternatively, a 3‐D iterative tomography, which modifies a time‐dependent three‐dimensional kinematic heliospheric model to fit interplanetary scintillation (IPS) observations, can supply solar wind velocity and density from 15 R s to 3 AU [ Jackson et al , ; Jian et al , ]. This 3‐D tomography technique can also be combined with some magnetic field models based on photospheric magnetograms to specify the bottom boundary conditions for the MHD solar wind simulations [ Yu et al , ; Jackson et al , ].…”

Influence of coronal mass ejections on parameters of high-speed solar wind: a case study

“…The quality of these models is evaluated by the disagreement between prediction and measurements of different solar wind parameters, among which the most important are the arrival time and speed at 1 AU (Zhao & Dryer, 2014;Jian et al, 2015;Reiss et al, 2016). The semi-empirical Wang-Sheeley-Arge model (WSA: Wang & Sheeley, 1990;Arge & Pizzo, 2000) based on the magnetic field expansion factor, the advanced Magnetohydrodynamic-based WSA-ENLIL prediction model (Odstrčil & Pizzo, 1999) and the empirical models based on the EUV-imaging (e.g.…”