Evidence for Partial Taylor Relaxation from Changes in Magnetic Geometry and Energy during a Solar Flare

Solar flares are powered by energy stored in the coronal magnetic field, a portion of which is released when the field reconfigures into a lower energy state. Investigation of sunspot magnetic field topology during flare activity is useful to improve our understanding of flaring processes. Here we investigate the deviation of the non-linear field configuration from that of the linear and potential configurations, and study the free energy available leading up to and after a flare. The evolution of the magnetic field in NOAA region 10953 was examined using data from Hinode/SOT-SP, over a period of 12 hours leading up to and after a GOES B1.0 flare. Previous work on this region found pre- and post-flare changes in photospheric vector magnetic field parameters of flux elements outside the primary sunspot. 3D geometry was thus investigated using potential, linear force-free, and non-linear force-free field extrapolations in order to fully understand the evolution of the field lines. Traced field line geometrical and footpoint orientation differences show that the field does not completely relax to a fully potential or linear force-free state after the flare. Magnetic and free magnetic energies increase significantly ~ 6.5-2.5 hours before the flare by ~ 10^31 erg. After the flare, the non-linear force-free magnetic energy and free magnetic energies decrease but do not return to pre-flare 'quiet' values. The post-flare non-linear force-free field configuration is closer (but not equal) to that of the linear force-free field configuration than a potential one. However, the small degree of similarity suggests that partial Taylor relaxation has occurred over a time scale of ~ 3-4 hours.Comment: Accepted for Publication in Astronomy & Astrophysics. 11 pages, 11 figure

Performance of Major Flare Watches from the Max Millennium Program (2001-2010)

The physical processes that trigger solar flares are not well understood and significant debate remains around processes governing particle acceleration, energy partition, and particle and energy transport. Observations at high resolution in energy, time, and space are required in multiple energy ranges over the whole course of many flares in order to build an understanding of these processes. Obtaining high-quality, co-temporal data from ground- and space- based instruments is crucial to achieving this goal and was the primary motivation for starting the Max Millennium program and Major Flare Watch (MFW) alerts, aimed at coordinating observations of all flares >X1 GOES X-ray classification (including those partially occulted by the limb). We present a review of the performance of MFWs from 1 February 2001 to 31 May 2010, inclusive, that finds: (1) 220 MFWs were issued in 3,407 days considered (6.5% duty cycle), with these occurring in 32 uninterrupted periods that typically last 2-8 days; (2) 56% of flares >X1 were caught, occurring in 19% of MFW days; (3) MFW periods ended at suitable times, but substantial gain could have been achieved in percentage of flares caught if periods had started 24 h earlier; (4) MFWs successfully forecast X-class flares with a true skill statistic (TSS) verification metric score of 0.500, that is comparable to a categorical flare/no-flare interpretation of the NOAA Space Weather Prediction Centre probabilistic forecasts (TSS = 0.488).Comment: 19 pages, 2 figures, accepted for publication in Solar Physic

Flare Forecasting Using the Evolution of McIntosh Sunspot Classifications

Most solar flares originate in sunspot groups, where magnetic field changes lead to energy build-up and release. However, few flare-forecasting methods use information of sunspot-group evolution, instead focusing on static point-in-time observations. Here, a new forecast method is presented based upon the 24-hr evolution in McIntosh classification of sunspot groups. Evolution-dependent $\geqslant$C1.0 and $\geqslant$M1.0 flaring rates are found from NOAA-numbered sunspot groups over December 1988 to June 1996 (Solar Cycle 22; SC22) before converting to probabilities assuming Poisson statistics. These flaring probabilities are used to generate operational forecasts for sunspot groups over July 1996 to December 2008 (SC23), with performance studied by verification metrics. Major findings are: i) considering Brier skill score (BSS) for $\geqslant$C1.0 flares, the evolution-dependent McIntosh-Poisson method ($\text{BSS}_{\text{evolution}}=0.09$) performs better than the static McIntosh-Poisson method ($\text{BSS}_{\text{static}} = -0.09$); ii) low BSS values arise partly from both methods over-forecasting SC23 flares from the SC22 rates, symptomatic of $\geqslant$C1.0 rates in SC23 being on average $\approx$80% of those in SC22 (with $\geqslant$M1.0 being $\approx$50%); iii) applying a bias-correction factor to reduce the SC22 rates used in forecasting SC23 flares yields modest improvement in skill relative to climatology for both methods ($\mathrm{BSS}^{\mathrm{corr}}_{\mathrm{static}} = 0.09$ and $\mathrm{BSS}^{\mathrm{corr}}_{\mathrm{evolution}} = 0.20$) and improved forecast reliability diagrams.Comment: 21 pages, 9 figure

Ensemble Forecasting of Major Solar Flares: Methods for Combining Models

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Space weather researchers are increasingly looking towards methods used by the terrestrial weather community to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASAP, ASSA, MAG4, MOSWOC, NOAA, and MCSTAT). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. It is found that most ensembles achieve a better skill metric (between 5\% and 15\%) than any of the members alone. Moreover, over 90\% of ensembles perform better (as measured by forecast attributes) than a simple equal-weights average. Finally, ensemble uncertainties are highly dependent on the internal metric being optimized and they are estimated to be less than 20\% for probabilities greater than 0.2. This simple multi-model, linear ensemble technique can provide operational space weather centres with the basis for constructing a versatile ensemble forecasting system -- an improved starting point to their forecasts that can be tailored to different end-user needs.Comment: Accepted for publication in the Journal of Space Weather and Space Climat

The Influence of Magnetic Field on Oscillations in the Solar Chromosphere

Two sequences of solar images obtained by the Transition Region and Coronal Explorer in three UV passbands are studied using wavelet and Fourier analysis and compared to the photospheric magnetic flux measured by the Michelson Doppler Interferometer on the Solar Heliospheric Observatory to study wave behaviour in differing magnetic environments. Wavelet periods show deviations from the theoretical cutoff value and are interpreted in terms of inclined fields. The variation of wave speeds indicates that a transition from dominant fast-magnetoacoustic waves to slow modes is observed when moving from network into plage and umbrae. This implies preferential transmission of slow modes into the upper atmosphere, where they may lead to heating or be detected in coronal loops and plumes.Comment: 8 pages, 6 figures (4 colour online only), accepted for publication in The Astrophysical Journa