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- ItemThe flare likelihood and region eruption forecasting (FLARECAST) project: flare forecasting in the big data & machine learning era(Les Ulis : EDP Sciences, 2021) Georgoulis, Manolis K.; Bloomfield, D. Shaun; Piana, Michele; Massone, Anna Maria; Soldati, Marco; Gallagher, Peter T.; Pariat, Etienne; Vilmer, Nicole; Buchlin, Eric; Baudin, Frederic; Csillaghy, Andre; Sathiapal, Hanna; Jackson, David R.; Alingery, Pablo; Benvenuto, Federico; Campi, Cristina; Florios, Konstantinos; Gontikakis, Constantinos; Guennou, Chloe; Guerra, Jordan A.; Kontogiannis, Ioannis; Latorre, Vittorio; Murray, Sophie A.; Park, Sung-Hong; Stachelski, Samuel von; Torbica, Aleksandar; Vischi, Dario; Worsfold, MarkThe European Union funded the FLARECAST project, that ran from January 2015 until February 2018. FLARECAST had a research-to-operations (R2O) focus, and accordingly introduced several innovations into the discipline of solar flare forecasting. FLARECAST innovations were: first, the treatment of hundreds of physical properties viewed as promising flare predictors on equal footing, extending multiple previous works; second, the use of fourteen (14) different machine learning techniques, also on equal footing, to optimize the immense Big Data parameter space created by these many predictors; third, the establishment of a robust, three-pronged communication effort oriented toward policy makers, space-weather stakeholders and the wider public. FLARECAST pledged to make all its data, codes and infrastructure openly available worldwide. The combined use of 170+ properties (a total of 209 predictors are now available) in multiple machine-learning algorithms, some of which were designed exclusively for the project, gave rise to changing sets of best-performing predictors for the forecasting of different flaring levels, at least for major flares. At the same time, FLARECAST reaffirmed the importance of rigorous training and testing practices to avoid overly optimistic pre-operational prediction performance. In addition, the project has (a) tested new and revisited physically intuitive flare predictors and (b) provided meaningful clues toward the transition from flares to eruptive flares, namely, events associated with coronal mass ejections (CMEs). These leads, along with the FLARECAST data, algorithms and infrastructure, could help facilitate integrated space-weather forecasting efforts that take steps to avoid effort duplication. In spite of being one of the most intensive and systematic flare forecasting efforts to-date, FLARECAST has not managed to convincingly lift the barrier of stochasticity in solar flare occurrence and forecasting: solar flare prediction thus remains inherently probabilistic.
- ItemA LOFAR observation of ionospheric scintillation from two simultaneous travelling ionospheric disturbances(Les Ulis : EDP Sciences, 2020) Fallows, Richard A.; Forte, Biagio; Astin, Ivan; Allbrook, Tom; Arnold, Alex; Wood, Alan; Dorrian, Gareth; Mevius, Maaijke; Rothkaeh, Hanna; Matyjasiak, Barbara; Krankowski, Andrzej; Anderson, James M.; Asgekar, Ashish; Avruch, I. Max; Bentum, Mark; Bisi, Mario M.; Butcher, Harvey R; Ciardi, Benedetta; Dabrowski, Bartosz; Damstra, Sieds; de Gasperin, Francesco; Duscha, Sven; Eislöffel, Jochen; Franzen, Thomas M.O.; Garrett, Michael A.; Griessmeier, Jean-Matthias; Gunst, Andre W.; Hoeft, Matthias; Horandel, Jorg R.; Iacobelli, Marco; Intema, Huib T.; Koopmans, Leon V.E.; Maat, Peter; Mann, Gottfried; Nelles, Anna; Paas, Harm; Pandey, Vishambhar N.; Reich, Wolfgang; Rowlinson, Antonia; Ruiter, Mark; Schwarz, Dominik J.; Serylak, Maciej; Shulevski, Aleksander; Smirnov, Oleg M.; Soida, Marian; Steinmetz, Matthias; Thoudam, Satyendra; Toribio, M. Carmen; van Ardenne, Arnold; van Bemmel, Ilse M.; van der Wiel, Matthijs H.D.; van Haarlem, Michiel P.; Vermeulen, Rene C.; Vocks, Christian; Wijers, Ralph A.M.J.; Wucknitz, Olaf; Zarka, Philippe; Zucca, PietroThis paper presents the results from one of the first observations of ionospheric scintillation taken using the Low-Frequency Array (LOFAR). The observation was of the strong natural radio source Cassiopeia A, taken overnight on 18–19 August 2013, and exhibited moderately strong scattering effects in dynamic spectra of intensity received across an observing bandwidth of 10–80 MHz. Delay-Doppler spectra (the 2-D FFT of the dynamic spectrum) from the first hour of observation showed two discrete parabolic arcs, one with a steep curvature and the other shallow, which can be used to provide estimates of the distance to, and velocity of, the scattering plasma. A cross-correlation analysis of data received by the dense array of stations in the LOFAR “core” reveals two different velocities in the scintillation pattern: a primary velocity of ~20–40 ms−1 with a north-west to south-east direction, associated with the steep parabolic arc and a scattering altitude in the F-region or higher, and a secondary velocity of ~110 ms−1 with a north-east to south-west direction, associated with the shallow arc and a scattering altitude in the D-region. Geomagnetic activity was low in the mid-latitudes at the time, but a weak sub-storm at high latitudes reached its peak at the start of the observation. An analysis of Global Navigation Satellite Systems (GNSS) and ionosonde data from the time reveals a larger-scale travelling ionospheric disturbance (TID), possibly the result of the high-latitude activity, travelling in the north-west to south-east direction, and, simultaneously, a smaller-scale TID travelling in a north-east to south-west direction, which could be associated with atmospheric gravity wave activity. The LOFAR observation shows scattering from both TIDs, at different altitudes and propagating in different directions. To the best of our knowledge this is the first time that such a phenomenon has been reported.