A new method of deriving Doppler velocities for Solar Orbiter SPICE

¹ Southwest Research Institute, 1301 Walnut St Suite 400 Boulder CO 80302, USA
² UKRI STFC, RAL Space Didcot OX11 0QX, UK
³ Université Paris-Saclay, CNRS, Institut d’Astrophysique Spatiale Bâtiment 121 91405 Orsay, France
⁴ Department of Physics, Catholic University of America 620 Michigan Avenue Washington DC 20064, USA
⁵ Heliophysics Division Goddard Space Flight Center Greenbelt MD 20771, USA
⁶ ETH-Zürich Wolfgang-Pauli-Str. 27 8093 Zürich, Switzerland
⁷ Physikalisch-Meteorologische Observatorium Davos/World Radiation Center (PMOD/WRC) Dorfstrasse 33 7260 Davos Dorf, Switzerland
⁸ Aerospace Engineering Sciences, University of Colorado 3775 Discovery Drive Boulder CO, USA

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Received: 31 May 2025
Accepted: 4 November 2025

Abstract

This paper presents a follow-up to previous work on correcting point-spread-function (PSF)-induced Doppler artifacts in observations by the SPICE spectrograph on Solar Orbiter. In a previous paper, we demonstrated the correction of these artifacts in the y − λ plane with PSF regularization, treating the forward problem with a method based on large sparse matrix inversion. It has since been found that similar apparent artifacts are also present in the x − λ direction, i.e., across adjacent slit positions. Correcting this is difficult (although not impossible) with the previous matrix inversion method due to the time variation between slit positions. We have therefore devised a new method that addresses both x − λ and y − λ artifacts simultaneously by applying wavelength-dependent shifts at each x − y plane of the spectral cube. This paper demonstrates the SPICE data issue, describes the new method, and shows a comparison with the previous one. We explore the time variation of the correction parameters for the SPICE data and show a clear orbit dependence. The results of the method are significantly higher-quality Doppler signals, which we estimate at less than ∼5 km/s uncertainty for brighter lines in the absence of other systematics. Furthermore, we show the new SPICE polar observation results as a demonstration. The correction codes are written in Python, publicly available on GitHub, and can be directly applied to SPICE level 2 datasets.