By Kaine Bunting (Aberystwyth University)
Tomography is used to gain the 3D plasma density of the solar corona (between 4-8Rs) using white light coronagraph observations (Morgan and Cook 2019). In this work, we use the density at 8Rs (e.g. figure 1a) to estimate velocity, providing an inner boundary condition for a heliospheric solar wind model. The results show that tomography can provide a valid (or improved) alternative to traditional photospheric-based magnetic models.
A simple inverse linear relationship converts densities to velocities. Extracted from Earth's latitude, the velocities form an inner boundary condition for the Time-dependent Heliospheric Upwind Extrapolation (HUXt) model (Owens et al. 2020). The model is then simulated for one Carrington rotation (CR), giving predicted velocities at Earth. The modelled velocities are compared to OMNI in-situ data, and the efficiency of HUXt allows an iterative fitting method optimises the parameters of the density-velocity conversion model by minimising a ‘distance’ metric using Dynamic Time Warping (DTW, Samara et al. 2022).
Figure 1 b) compares the output of HUXt based on Tomography-HUXt and MAS inner boundaries (Linker et al. 1999), where the MAS velocities have been optimised similarly to the tomography velocities for CR2210 (Nov 2018). Tomography-HUXt model outperforms the MAS-HUXt model: tomography-HUXt gives a MAE of 47.9 km s-1 compared to the 53.58 km s-1 of the MAS-HUXt model, and a higher Pearson correlation coefficient of 0.74 compared to that of MAS-HUXt (0.56). This work shows that inner boundary conditions derived using tomography are a valid alternative to magnetic models such as MAS.
Our current work investigates a more advanced relationship between coronal densities and velocities, and provides improved solar wind predictions over a whole solar cycle. This scheme is implemented as part of the SWEEP software suite for the UK Met Office's space weather forecasting capabilities from 2023 onwards.
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Morgan, H., and A. C. Cook, 2020. The Width, Density, and Outflow of Solar Coronal Streamers. The Astrophysical Journal, 893(1), 57. 10.3847/1538-4357/ab7e32
Owens, M. J., M. Lang, L. Barnard, P. Riley, M. Ben-Nun, et al. 2020. A Computationally Efficient, Time-Dependent Model of the Solar Wind for Use as a Surrogate to Three-Dimensional Numerical Magnetohydrodynamic Simulations. Solar Physics. 10.1007/s11207-020-01605-3
Samara, E., B. Laperre, R. Kieokaew, M. Temmer, C. Verbeke, et al. 2022. Dynamic Time Warping as a Means of Assessing Solar Wind Time Series. The Astrophysical Journal, 927(2), 187. 10.3847/1538-4357/ac4af6