Open Access
| Issue |
J. Space Weather Space Clim.
Volume 10, 2020
|
|
|---|---|---|
| Article Number | 38 | |
| Number of page(s) | 17 | |
| DOI | https://doi.org/10.1051/swsc/2020042 | |
| Published online | 21 August 2020 | |
- Armstrong JS. 2001. Combining forecasts. Springer US, Boston, MA. https://doi.org/10.1007/978-0-306-47630-3_19. [Google Scholar]
- Barnes G, Leka KD, Schrijver CJ, Colak T, Qahwaji R, et al. 2016. A comparison of flare forecasting methods. I. Results from the “all-clear” workshop. Astrophys J 829 : 89. https://doi.org/10.3847/0004-637X/829/2/89. [Google Scholar]
- Bloomfield DS, Higgins PA, McAteer RTJ, Gallagher PT. 2012. Toward reliable benchmarking of solar flare forecasting methods. ApJ Lett 747 : L41. https://doi.org/10.1088/2041-8205/747/2/L41. [NASA ADS] [CrossRef] [Google Scholar]
- Colak T, Qahwaji R. 2008. Automated McIntosh-based classification of sunspot groups using MDI images. Sol Phys 248 : 277–296. https://doi.org/10.1007/s11207-007-9094-3. [NASA ADS] [CrossRef] [Google Scholar]
- Colak T, Qahwaji R. 2009. Automated solar activity prediction: A hybrid computer platform using machine learning and solar imaging for automated prediction of solar flares. Space Weather 7 : S06001. https://doi.org/10.1029/2008SW000401. [NASA ADS] [CrossRef] [Google Scholar]
- Crown MD. 2012. Validation of the NOAA Space Weather Prediction Center’s solar flare forecasting look-up table and forecaster-issued probabilities. Space Weather 10 : S06006. https://doi.org/10.1029/2011SW000760. [CrossRef] [Google Scholar]
- Falconer D, Barghouty AF, Khazanov I, Moore R. 2011. A tool for empirical forecasting of major flares, coronal mass ejections, and solar particle events from a proxy of active-region free magnetic energy. Space Weather 9 : S04003. https://doi.org/10.1029/2009SW000537. [NASA ADS] [CrossRef] [Google Scholar]
- Falconer DA, Moore RL, Barghouty AF, Khazanov I. 2014. MAG4 versus alternative techniques for forecasting active region flare productivity. Space Weather 12 : 306–317. https://doi.org/10.1002/2013SW001024. [NASA ADS] [CrossRef] [Google Scholar]
- Gallagher PT, Moon Y-J, Wang H. 2002. Active-region monitoring and flare forecasting I. Data processing and first results. Sol Phys 209(1): 171–183. https://doi.org/10.1023/A:1020950221179. [NASA ADS] [CrossRef] [Google Scholar]
- Gatz DF, Smith L. 1995. The standard error of a weighted mean concentration – I. Bootstrapping vs other methods. Atmos Environ 29(11): 1185–1193. https://doi.org/10.1016/1352-2310(94)00210-C. [NASA ADS] [CrossRef] [Google Scholar]
- Genre V, Kenny G, Meyler A, Timmermann A. 2013. Combining expert forecasts: Can anything beat the simple average? Int J Forecast 29 (1) : 108–121. [CrossRef] [Google Scholar]
- Gilleland E. 2015. Verification: Weather forecast verification utilities (v1.42). URL https://cran.r-project.org/package=verification . [Google Scholar]
- Granger CWJ, Ramanathan R. 1984. Improved methods of combining forecasts. J Forecast 3(2) : 197–204. https://doi.org/10.1002/for.3980030207. [CrossRef] [Google Scholar]
- Guerra JA, Pulkkinen A, Uritsky VM. 2015. Ensemble forecasting of major solar flares: First results. Space Weather 13 : 626–642. https://doi.org/10.1002/2015SW001195. [CrossRef] [Google Scholar]
- Hudson HS. 2007. The unpredictability of the most energetic solar events. Astrophys J Lett 663(1) : L45–L48. https://doi.org/10.1086/519923. [CrossRef] [Google Scholar]
- Knipp DJ. 2016. Advances in space weather ensemble forecasting. Space Weather 14 : 52–53. https://doi.org/10.1002/2016SW001366. [CrossRef] [Google Scholar]
- Kraft D. 1988. A software package for sequential quadratic programming. In: Forschungsbericht. Deutsche Forschungs- und Versuchsanstalt für Luft- und Raumfahrt, DFVLR, 88-28 . [Google Scholar]
- Leka K, Barnes G. 2018. Chapter 3 – Solar flare forecasting: Present methods and challenges. In: Extreme events in geospace, Buzulukova N (Ed.), Elsevier, pp. 65–98. https://doi.org/10.1016/B978-0-12-812700-1.00003-0. [CrossRef] [Google Scholar]
- Leka KD, Park S-H, Kusano K, Andries J, Barnes G, et al. 2019. A comparison of flare forecasting methods. II. Benchmarks, metrics, and performance results for operational solar flare forecasting systems. Astrophys J Suppl Ser 243(2) : 36. https://doi.org/10.3847/1538-4365/ab2e12. [CrossRef] [Google Scholar]
- Murray SA. 2018. The importance of ensemble techniques for operational space weather forecasting. Space Weather 16(7) : 777–783. https://doi.org/10.1029/2018SW001861. [CrossRef] [Google Scholar]
- Murray SA, Bingham S, Sharpe M, Jackson DR. 2017. Flare forecasting at the Met Office Space Weather Operations Centre. Space Weather 15 : 577–588. https://doi.org/10.1002/2016SW001579. [CrossRef] [Google Scholar]
- Oliphant TE. 2007. Python for scientific computing. Comput Sci Eng 9(3) : 10–20. https://doi.org/10.1109/MCSE.2007.58. [Google Scholar]
- Pesnell WD, Thompson BJ, Chamberlin PC. 2012. The solar dynamics observatory (SDO). Sol Phys 275 : 3–15. https://doi.org/10.1007/s11207-011-9841-3. [Google Scholar]
- Sharpe MA, Murray SA. 2017. Verification of space weather forecasts issued by the Met Office Space Weather Operations Centre. Space Weather 15 : 1383–1395. https://doi.org/10.1002/2017SW001683. [CrossRef] [Google Scholar]
- Stock JH, Watson MW. 2004. Combination forecasts of output growth in a seven-country data set. J Forecast 23(6) : 405–430. https://doi.org/10.1002/for.928. [CrossRef] [Google Scholar]
- Tsagouri I, Belehaki A, Bergeot N, Cid C, Delouille V, et al. 2013. Progress in space weather modeling in an operational environment. J Space Weather Space Clim 3 : A17. https://doi.org/10.1051/swsc/2013037. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.