J. Space Weather Space Clim.
Volume 11, 2021
|Number of page(s)||10|
|Published online||15 February 2021|
Thermosphere modeling capabilities assessment: geomagnetic storms
CNES, Space Geodesy Office, 31401 Toulouse, France
2 University of Colorado, Space Weather Technology, Research & Education Center (SWx TREC), Boulder, 80309-0429 CO, USA
3 University of Colorado/CIRES and NOAA/SWPC, Boulder, 80305 CO, USA
* Corresponding author: email@example.com
Accepted: 8 January 2021
The specification and prediction of density fluctuations in the thermosphere, especially during geomagnetic storms, is a key challenge for space weather observations and modeling. It is of great operational importance for tracking objects orbiting in near-Earth space. For low-Earth orbit, variations in neutral density represent the most important uncertainty for propagation and prediction of satellite orbits. An international conference in 2018 conducted under the auspices of the NASA Community Coordinated Modeling Center (CCMC) included a workshop on neutral density modeling, using both empirical and numerical methods, and resulted in the organization of an initial effort of model comparison and evaluation. Here, we present an updated metric for model assessment under geomagnetic storm conditions by dividing a storm in four phases with respect to the time of minimum Dst and then calculating the mean density ratios and standard deviations and correlations. Comparisons between three empirical (NRLMSISE-00, JB2008 and DTM2013) and two first-principles models (TIE-GCM and CTIPe) and neutral density data sets that include measurements by the CHAMP, GRACE, and GOCE satellites for 13 storms are presented. The models all show reduced performance during storms, notably much increased standard deviations, but DTM2013, JB2008 and CTIPe did not on average reveal a significant bias in the four phases of our metric. DTM2013 and TIE-GCM driven with the Weimer model achieved the best results taking the entire storm event into account, while NRLMSISE-00 systematically and significantly underestimates the storm densities. Numerical models are still catching up to empirical methods on a statistical basis, but as their drivers become more accurate and they become available at higher resolutions, they will surpass them in the foreseeable future.
Key words: data and metrics for standardized thermosphere model assessment / assessments for TIE-GCM, CTIPe, NRLMSISE-00, JB2008 and DTM2013 / short descriptions are given for each of the models
© S. Bruinsma et al., Published by EDP Sciences 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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