Solar energy paper index
Determination of the horizontal velocity field in the solar atmosphere: Method validation using 3D MHD model
One-line summary
A solar energy research paper on Determination of the horizontal velocity field in the solar atmosphere: Method validation using 3D MHD model.
Engineering notes
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Chinese explanation / 中文解读
中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
We present an improved version and further validation of a method, originally introduced by Stodilka (2016), for reconstructing horizontal velocity fields in the solar atmosphere from physical parameters typically derived from spectroscopic observations through inversion techniques. This approach relies on the continuity equation and the assumption of negligible vertical vorticity. Several algorithmic modifications were implemented to allow application to large spatial grids, including the compact storage of a sparse matrix of the system of linear equations. The method was tested using snapshots from the realistic 3D MHD Bifrost simulation en024048_hion of the solar atmosphere, covering heights from 20 to 980 km. Horizontal velocities were reconstructed from model density and vertical velocity values. A sinc filter with a Lanczos window was applied to the reconstructed horizontal velocity maps to reduce artefacts related primarily to the use of horizontal periodic boundary conditions. In the photospheric layers, the reconstructed horizontal velocity fields show a high level of agreement with the model values, with the Pearson correlation coefficient in the range 0.8-0.9. The method performs best within granules, whereas larger discrepancies occur in intergranular lanes due to complex counter-streaming flows. In the chromospheric layers, the reconstruction quality decreases significantly with height, consistent with the increasing importance of vortex motions and the breakdown of the underlying assumption. The method provides a reliable and efficient tool for reconstructing horizontal flows in the solar photosphere. The proposed improvements make the method applicable to large observational datasets.
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