About the Project
Solar flares are among the most energetic events in the solar system, affecting physical systems from the solar surface to the heliosphere, geo-space and beyond. Flares, alongside coronal mass ejections (CMEs), are major contributors to space weather – changing conditions in the near-Earth space, magnetosphere and upper atmosphere. Flares mostly occur in active regions; parts of the solar atmosphere dominated by magnetic field. Flows move field around and, after enough energy accumulates and conditions are suitable, active regions can release free energy as flares/CMEs.
Free energy stored by the magnetic field can be obtained from (computationally expensive) non-linear force-free field (NLFFF) extrapolations and is known to be sufficient to power flares/CMEs. However, the conditions required to initiate these events are unclear, limiting our ability to forecast them. The main forms of active region energy injection are known to be emergence of magnetic field through the solar surface and horizontal flows acting on previously emerged field, but we lack quantitative understanding of the contributions these injection processes provide to active region flaring/eruption energy budgets. Twisted magnetic field in active region atmospheres indicate that the field holds free energy, and directly relates to the complexity of magnetic-polarity spatial mixing on the surface. Quantifying the degree of polarity mixing and its relation to NLFFF-extrapolated energy budgets will provide a novel, computationally inexpensive free-energy proxy that has not previously been considered, while studying the motion/evolution of polarities in active regions will shed light on flare triggers. This project concerns the magnetic conditions that power and initiate flares, with the potential to impact on the quality/timeliness of adverse space weather forecasting and increasing the operational capacity of space-weather forecast centres (e.g., UK Met Office).
This project aims to understand the roles that energy injection/storage and polarity mixing play in the production of flares in active regions, before utilizing this knowledge to develop new machine-learning flare forecasting schemes. The study of active region magnetic energy is dominated by case studies, but this work will provide a step change in understanding active region energetics by considering a large statistical sample. The aim will be achieved by:
1) investigating the contributions of flux emergence and surface flows to magnetic energy evolution in flaring and non-flaring active regions;
2) developing new measures to quantify the degree of magnetic-polarity mixing;
3) examining the relation of flaring to energy injection/storage, polarity mixing, and motion/evolution of polarities within active regions;
4) implementing machine-learning schemes to forecast flares using these measures/behaviours and quantifying their performance using verification metrics.
This project suits students with an Astrophysics, Physics or Applied Mathematics degree. Prior programming experience is desirable (e.g., Python/IDL), but training in all necessary skills will be provided. The student will be based in the Solar and Space Physics group in the Department of Mathematics, Physics and Electrical Engineering, aligned to the Extreme Environments Multi-Disciplinary Research Theme. They will be supported to publish their work in leading peer-reviewed journals and will have opportunities to present at national/international conferences.
The principal supervisor for this project is Dr. Shaun Bloomfield (E-mail: [Email Address Removed]).
Please note eligibility requirement:
· Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
· Appropriate IELTS score, if required.
· Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere or if they have previously been awarded a PhD.
For further details of how to apply, entry requirements and the application form, see
Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. STFC22/EE/MPEE/BLOOMFIELDShaun) will not be considered.
Deadline for applications: 1 March 2022
Start Date: 1 October 2022
Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community.
Georgoulis, M.K., Bloomfield, D.S. + 26 co-authors (2021) Journal of Space Weather and Space Climate, 11, 39
The flare likelihood and region eruption forecasting (FLARECAST) project: flare forecasting in the big data & machine learning era
Kontogiannis, I., Georgoulis, M.K., Guerra, J.A., Park, S.-H., Bloomfield, D.S. (2019) Solar Physics, 294, 130
Which Photospheric Characteristics Are Most Relevant to Active-Region Coronal Mass Ejections?
Leka, K.D., Park, S.-H., Kusano, K., Andries, J., Barnes, G., Bingham, S., Bloomfield, D.S. + 17 co-authors (2019) The Astrophysical Journal, 881, 101
A Comparison of Flare Forecasting Methods. III. Systematic Behaviors of Operational Solar Flare Forecasting Systems
Leka, K.D., Park, S.-H., Kusano, K., Andries, J., Barnes, G., Bingham, S., Bloomfield, D.S. + 17 co-authors (2019) The Astrophysical Journal Supplement Series, 243, 36
A Comparison of Flare Forecasting Methods. II. Benchmarks, Metrics, and Performance Results for Operational Solar Flare Forecasting Systems
Park, S.-H., Guerra, J.A., Gallagher, P.T., Georgoulis, M.K., Bloomfield, D.S. (2018) Solar Physics, 293, 114
Photospheric Shear Flows in Solar Active Regions and Their Relation to Flare Occurrence
McCloskey, A.E., Gallagher, P.T., Bloomfield, D.S. (2018) Journal of Space Weather and Space Climate, 8, A34
Flare forecasting using the evolution of McIntosh sunspot classifications
Florios, K., Kontogiannis, I., Park, S.-H., Guerra, J.A., Benvenuto, F., Bloomfield, D.S., Georgoulis, M.K. (2016) Solar Physics, 293, 28
Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning
Padinhatteeri, S., Higgins, P.A., Bloomfield, D.S., Gallagher, P.T. (2016) Solar Physics, 291, 41
Automatic Detection of Magnetic Delta in Sunspot Groups
Barnes, G., Leka, K.D., Schrijver, C.J., Colak, T., Qahwaji, R., Ashamari, O.W., Yuan, Y., Zhang, J., McAteer, R.T.J., Bloomfield, D.S. + 8 co-authors (2016) The Astrophysical Journal, 829, 89
A Comparison of Flare Forecasting Methods. I. Results from the “All-Clear” Workshop
McCloskey, A.E., Gallagher, P.T., Bloomfield, D.S. (2016) Solar Physics, 291, 1711
Flaring Rates and the Evolution of Sunspot Group McIntosh Classifications