Quality of STORM model predictions for a mid-latitude station
Recent theoretical model simulations of the ionospheric response to geomagnetic storms have provided an understanding for the development of an empirical storm-time ionospheric correction model (STORM). The empirical model is driven by the previous time-history of ap, and is designed to scale the qu...
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Published in | Geofísica internacional Vol. 41; no. 2; pp. 195 - 201 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Universidad Nacional Autónoma de México, Instituto de Geofísica
01.02.2002
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Subjects | |
Online Access | Get full text |
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Summary: | Recent theoretical model simulations of the ionospheric response to geomagnetic storms have provided an understanding for the development of an empirical storm-time ionospheric correction model (STORM). The empirical model is driven by the previous time-history of ap, and is designed to scale the quiet-time F-layer critical frequency (foF2) to account for storm-time changes in the ionosphere. The model provides a useful, yet simple tool for modeling of the perturbed ionosphere. The quality of the model prediction has been evaluated by comparing with the observed ionospheric response during the six biggest storms in 2000. The model output was compared with the actual ionospheric response at a mid-latitude station (Chilton, geographic coordinates: 51.6 N, 358.7 E). The comparisons show the model captures the decreases in electron density particularly well in summer conditions, and with some less quality for other conditions. The value of the model has been quantified by comparing the root mean square error (RMSE) of the STORM predictions with the monthly mean. The results of this study illustrate that the STORM model shows almost a 55 % improvement over the monthly median during the storm days, a significant improvement over climatology. STORM is now included in the latest version of the International Reference Ionosphere (IRI2000, Bilitza, 2001) as the correction for perturbed conditions. |
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ISSN: | 0016-7169 |