A comparison of flare forecasting methods, I: results from the 'All-clear' workshop

Autor: Barnes, G., Leka, K.D., Schrijver, C.J., Colak, Tufan, Qahwaji, Rami S.R., Ashamari, Omar, Yuan, Y., Zhang, J., McAteer, R.T.J., Bloomfield, D.S., Higgins, P.A., Gallagher, P.T., Falconer, D.A., Georgoulis, M.K., Wheatland, M.S., Balch, C.
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Druh dokumentu: Článek
DOI: 10.3847/0004-637X/829/2/89
Popis: Yes
Solar flares produce radiation which can have an almost immediate effect on the near-Earth environ- ment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has prolifer- ated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, but have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from MDI, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends towards a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.
This work is the outcome of many collaborative and cooperative efforts. The 2009 “Forecasting the All-Clear” Workshop in Boulder, CO was sponsored by NASA/Johnson Space Flight Center’s Space Radiation Analysis Group, the National Center for Atmospheric Research, and the NOAA/Space Weather Prediction Center, with additional travel support for participating scientists from NASA LWS TRT NNH09CE72C to NWRA. The authors thank the participants of that workshop, in particular Drs. Neal Zapp, Dan Fry, Doug Biesecker, for the informative discussions during those three crazy days, and NCAR’s Susan Baltuch and NWRA’s Janet Biggs for organizational prowess. Workshop preparation and analysis support was provided for GB, KDL by NASA LWS TRT NNH09CE72C, and NASA Heliophysics GI NNH12CG10C. PAH and DSB received funding from the European Space Agency PRODEX Programme, while DSB and MKG also received funding from the European Union’s Horizon 2020 research and in- novation programme under grant agreement No. 640216 (FLARECAST project). MKG also acknowledges research performed under the A-EFFort project and subsequent service implementation, supported under ESA Contract number 4000111994/14/D/MPR. YY was supported by the National Science Foundation under grants ATM 09-36665, ATM 07-16950, ATM-0745744 and by NASA under grants NNX0-7AH78G, NNXO-8AQ90G. YY owes his deepest gratitude to his advisers Prof. Frank Y. Shih, Prof. Haimin Wang and Prof. Ju Jing for long discussions, for reading previous drafts of his work and providing many valuable comments that improved the presentation and contents of this work. JMA was supported by NSF Career Grant AGS-1255024 and by a NMSU Vice President for Research Interdisciplinary Research Grant.
Databáze: Networked Digital Library of Theses & Dissertations
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