Thermosphere model assessment for geomagnetic storms from 2001 to 2023

We present an updated study for thermosphere model assessment under geomagnetic storm conditions, defined when the geomagnetic index ap = 80 or larger. Comparisons between five empirical models, NRLMSISE-00, JB2008, and three versions of DTM2020, and CHAMP, GRACE, GOCE, Swarm-A, and GRACE-FO neutral density data sets for 152 storms are presented. The storms are categorized according to ap, as single peak or multiple peaks. After applying a model debiasing procedure using the density data just before the onset of a storm, the models are on average only slightly biased, often only a few percent. This is an unexpected and reassuring result for these relatively simple models, which were fitted to different observations. The standard deviations of these averages are however up to 12% (1-sigma), which places the small biases into perspective. The smallest biases are achieved at the lowest altitude when comparing with GOCE data, and the highest for GRACE. The best results, i.e. smallest bias and standard deviation on average over all single-peak storms, over the entire 4-Phase storm period are obtained with DTM2020_Intermediate and DTM2020_Research models, while the oldest model, NRLMSISE-00, is the least precise. However, NRLMSISE-00 is the least biased when compared to multiple-peak storms. As could be expected, multiple-peak storms are reproduced with less precision than single-peak storms. The assessment reveals that model precision decreases with altitude, but that bias is independent of altitude, at least in the range covered by the data, 250–550 km.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-23
DOI
https://doi.org/10.1051/swsc/2024027/pdf
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Thermosphere model assessment for geomagnetic storms from 2001 to 2023

Springer Link (Chiba Institute of Technology)
Ionosphere and magnetosphere dynamics
article

Thermosphere model assessment for geomagnetic storms from 2001 to 2023

article en

Abstract

We present an updated study for thermosphere model assessment under geomagnetic storm conditions, defined when the geomagnetic index ap = 80 or larger. Comparisons between five empirical models, NRLMSISE-00, JB2008, and three versions of DTM2020, and CHAMP, GRACE, GOCE, Swarm-A, and GRACE-FO neutral density data sets for 152 storms are presented. The storms are categorized according to ap, as single peak or multiple peaks. After applying a model debiasing procedure using the density data just before the onset of a storm, the models are on average only slightly biased, often only a few percent. This is an unexpected and reassuring result for these relatively simple models, which were fitted to different observations. The standard deviations of these averages are however up to 12% (1-sigma), which places the small biases into perspective. The smallest biases are achieved at the lowest altitude when comparing with GOCE data, and the highest for GRACE. The best results, i.e. smallest bias and standard deviation on average over all single-peak storms, over the entire 4-Phase storm period are obtained with DTM2020_Intermediate and DTM2020_Research models, while the oldest model, NRLMSISE-00, is the least precise. However, NRLMSISE-00 is the least biased when compared to multiple-peak storms. As could be expected, multiple-peak storms are reproduced with less precision than single-peak storms. The assessment reveals that model precision decreases with altitude, but that bias is independent of altitude, at least in the range covered by the data, 250–550 km.

Springer Link (Chiba Institute of Technology)
Centre National d'Études Spatiales (FR)
Technische Universiteit Delft, Centre National d’Etudes Spatiales, Delft Research Centres, Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
Openalex Percentile: Top 68%
Ionosphere and magnetosphere dynamics
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Thermosphere model assessment for geomagnetic storms from 2001 to 2023 · Springer Link (Chiba Institute of Technology) (2024) | TGRS Research Map | TGRS