Mooney, M. K., Marsh, M. S., Forsyth, C., Sharpe, M., Hughes, T., Bingham, S., Jackson, D. R., Rae, Jonathan and Chisham, G. (2021) Evaluating Auroral Forecasts Against Satellite Observations. Space Weather, 19 (8). e2020SW002688. ISSN 1542-7390
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Abstract
The aurora is a readily visible phenomenon of interest to many members of the public. However, the aurora and associated phenomena can also significantly impact communications, ground-based infrastructure and high altitude radiation exposure. Forecasting the location of the auroral oval is therefore a key component of space weather forecast operations. A version of the OVATION-Prime 2013 auroral precipitation model [Newell et al., 2014] was used by the UK Met Office Space Weather Operations Centre (MOSWOC). The operational implementation of the OVATION-Prime 2013 model at the UK Met Office delivered a 30-minute forecast of the location of the auroral oval and the probability of observing the aurora. Using weather forecast evaluation techniques, we evaluate the ability of the OVATION-Prime 2013 model forecasts to predict the location and probability of the aurora occurring by comparing the forecasts with auroral boundaries determined from data from the IMAGE satellite between 2000 and 2002. Our analysis shows that the operational model performs well at predicting the location of the auroral oval, with a relative operating characteristic (ROC) score of 0.82. The model performance is reduced in the dayside local time sectors (ROC score = 0.59) and during periods of higher geomagnetic activity (ROC score of 0.55 for Kp=8). As a probabilistic forecast, OVATION-Prime 2013 tends to under-predict the occurrence of aurora by a factor of 1.1 - 6, while probabilities of over 90% are over-predicted.
Item Type: | Article |
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Uncontrolled Keywords: | ROC scores, space weather, forecast verification, auroral forecasting, OVATION-Prime 2013, Aurora |
Subjects: | F300 Physics F500 Astronomy |
Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
Depositing User: | Rachel Branson |
Date Deposited: | 09 Aug 2021 12:52 |
Last Modified: | 08 Sep 2021 13:15 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/46884 |
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