TY - JOUR
T1 - CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event
AU - Shim, J. S.
AU - Rastätter, L.
AU - Kuznetsova, M.
AU - Bilitza, D.
AU - Codrescu, M.
AU - Coster, A. J.
AU - Emery, B. A.
AU - Fedrizzi, M.
AU - Förster, M.
AU - Fuller-Rowell, T. J.
AU - Gardner, L. C.
AU - Goncharenko, L.
AU - Huba, J.
AU - McDonald, S. E.
AU - Mannucci, A. J.
AU - Namgaladze, A. A.
AU - Pi, X.
AU - Prokhorov, B. E.
AU - Ridley, A. J.
AU - Scherliess, L.
AU - Schunk, R. W.
AU - Sojka, J. J.
AU - Zhu, L.
N1 - Funding Information:
The vertical TEC data were provided by MIT Haystack Observatory (http://www. openmadrigal.org). This work is sup ported by grants from the National Science Foundation (NSF) Space Weather Program. Portions of this research were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a con tract with the National Aeronautics and Space Administration. This model vali dation study is supported by the Community Coordinated Modeling Center (CCMC) at the Goddard Space Flight Center.
Publisher Copyright:
©2017. American Geophysical Union. All Rights Reserved.
PY - 2017/10
Y1 - 2017/10
N2 - In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14–15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m−2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.
AB - In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14–15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m−2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.
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U2 - 10.1002/2017SW001649
DO - 10.1002/2017SW001649
M3 - Article
AN - SCOPUS:85034425777
SN - 1542-7390
VL - 15
SP - 1238
EP - 1256
JO - Space Weather
JF - Space Weather
IS - 10
ER -