edu.ucar.opensky::articles:26977 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T18:55:05.068440 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7b280fs https://doi.org/10.5281/zenodo.3871057 https Related Software #1 SunPy SuNeRF: 3D reconstruction of the solar EUV corona using neural radiance fields 2024-02-01T00:00:00Z publication https://n2t.org/ark:/85065/d7b280fs https://doi.org/10.3847/2041-8213/ad12d2 Jarolim, R. author Tremblay, Benoit author Muñoz-Jaramillo, A. author Bintsi, K. author Jungbluth, A. author Santos, M. author Vourlidas, A. author Mason, J. P. author Sundaresan, S. author Downs, C. author Caplan, R. M. author UCAR/NCAR - Library publisher To understand its evolution and the effects of its eruptive events, the Sun is permanently monitored by multiple satellite missions. The optically thin emission of the solar plasma and the limited number of viewpoints make it challenging to reconstruct the geometry and structure of the solar atmosphere; however, this information is the missing link to understand the Sun as it is: a 3D evolving star. We present a method that enables a complete 3D representation of the uppermost solar layer (corona) observed in extreme ultraviolet (EUV) light. We use a deep-learning approach for 3D scene representation that accounts for radiative transfer to map the entire solar atmosphere from three simultaneous observations. We demonstrate that our approach provides unprecedented reconstructions of the solar poles and directly enables height estimates of coronal structures, solar filaments, coronal hole profiles, and coronal mass ejections. We validate the approach using model-generated synthetic EUV images, finding that our method accurately captures the 3D geometry of the Sun even from a limited number of 32 ecliptic viewpoints ( divide latitude divide <= 7 degrees). We quantify the uncertainties of our model using an ensemble approach that allows us to estimate the model performance in the absence of a ground truth. Our method enables a novel view of our closest star and is a breakthrough technology for the efficient use of multi-instrument data sets, which paves the way for future cluster missions. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation