Validation of Ionospheric Modeled TEC in the Equatorial Ionosphere During the 2013 March and 2021 November Geomagnetic Storms

Author:

Chou Min‐Yang12ORCID,Yue Jia12ORCID,Wang Jack12ORCID,Huba J. D.3,El Alaoui Mostafa12ORCID,Kuznetsova Maria M.1,Rastätter Lutz1,Shim Ja Soon4,Fang Tzu‐Wei5ORCID,Meng Xing6ORCID,Fuller‐Rowell Dominic5,Retterer John M.7ORCID

Affiliation:

1. NASA Goddard Space Flight Center Community Coordinated Modeling Center Greenbelt MD USA

2. Department of Physics Catholic University of America Washington DC USA

3. Syntek Technologies Fairfax VA USA

4. Department of Atmospheric Sciences Yonsei University Seoul South Korea

5. NOAA Space Weather Prediction Center Boulder CO USA

6. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

7. Institute for Scientific Research Boston College Chestnut Hill MA USA

Abstract

AbstractThis paper presents the validation of modeled total electron content (TEC) from 14 ionospheric models, including empirical, physics‐based, and data assimilation (DA) models, hosted by the NASA/NSF Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center, and NASA Jet Propulsion Laboratory (JPL). This study aims to assess the current progress and capability of the CCMC‐hosted ionospheric models in capturing the storm time ionosphere during the low and moderate solar flux years. We focus on the low‐latitude ionosphere (i.e., ±40° in magnetic latitude) and compare the modeled TEC with the Madrigal TEC during the 2013 March and 2021 November storms. Multiple metrics are used to quantitatively assess the models' accuracy, precision, association, bias, and capability in capturing the TEC changes in response to the storms. The skill score based on the metric scores is further proposed to evaluate the overall performance of ionospheric models against the reference model (International Reference Ionosphere 2016; IRI‐2016). The results indicate that the DA model GLObal Total Electron Content and JPL Global Ionospheric Map models show good performance in modeling the TEC and reasonably reflect the storm time TEC changes spatially and temporally. The empirical models IRI‐2016 and 2020 show relatively good performance compared with the physics‐based models regarding the model‐data comparison; however, it is difficult to characterize the TEC changes caused by storms. The physics‐based models can simulate the storm effect in spatial and temporal TEC variations better than the empirical model. The performance of ionospheric models in capturing the storm time TEC anomaly is presented and discussed.

Funder

Goddard Space Flight Center

National Aeronautics and Space Administration

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

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