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  SCENARIO: Decadal climate forecasting for the energy-sector (SC2022_02)


   Department of Meteorology

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  Dr D Brayshaw, Dr L Shaffrey, Dr Hazel Thornton, Dr Doug Smith  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Throughout the world, power systems are undergoing massive change in response to the challenge of climate change. Renewable electricity sources – such as wind and solar PV – are playing an increasing role in power systems, fundamentally altering the way power systems operate. In Great Britain, for example, increasing levels of wind power installation now mean that shifts in wind speed are now as important as shifts in temperature in maintaining a secure (i.e., continuous and near-instantaneous) match between electricity-demand and electricity-supply and, as a result, anticipating low-wind-cold-snaps has become a key issue for supply security (Bloomfield et al 2018; Thornton et al 2017). Similar challenges around the integration of renewables into existing power systems are being faced by many countries across the world, raising an important question: how will climate variability and climate change affect the behaviour of power systems in the coming years and decades? 

Recent years have seen increased interest from both academia and industry into the risks posed by climate variability and change for power system operations and planning. Much of this research, however, has been based either on an assumption of an unchanging climate (i.e., using historical observations) or else very-long-term climate model projections (relating to 2050 or beyond). There is therefore a significant “decadal-scale information gap” (1-10 years) between these extremes which is significant for power system planning. High quality decadal-scale climate information could, for example, support the provision of early warning systems for stress periods such as low-wind years, or support the identification of optimal “pathways” for integrating new infrastructure over the course of several years. 

Decadal-scale climate forecasting is, however, scientifically challenging in that it seeks to make a concrete prediction of near-term future climate (i.e., statements about what will happen based on some initial starting state) as opposed to the long term projections more commonly with climate models (i.e., possible outcomes contingent on the occurrence of a particular greenhouse gas scenario). Until recently, it has been widely believed that the skill of decadal forecasting was rather limited, but recent developments have indicated surprising skill several years ahead (Smith et al, 2020). This PhD will build on these recent developments to explore the extent to which skilful decadal climate predictions can be used to inform the operation and management of the energy system from a season to several years ahead. 

Drawing upon a range of disciplines (climate science, mathematics, physics and engineering) – and with the support of a world-leading CASE partner - this project will therefore seek to pioneer the use of decadal forecasting for energy system applications. A central focus of the work will be to characterize and understand decadal forecast skill and to identify and develop applications through which it can be utilized. The student can therefore expect to be involved in:

1)     assessing and understanding the skill of decadal predictions;

2)     developing and applying models to “convert” predictions into energy-system relevant quantities; and

3)     engaging energy-sector stakeholders to develop sector-relevant applications of decadal forecasts.

It is intended that a prototype forecast application (e.g., a year- or decade- ahead energy demand forecast) will be produced by the end of the project. 

Training opportunities:

The student will join the Energy Meteorology research group (research.reading.ac.uk/met-energy) in the Meteorology Department at Reading University and work with an experienced supervisory team. World leading MSc-level training in meteorological science will be provided, and students encouraged to participate in relevant summer schools, seminars and workshops. Through a CASE studentship with the UK Met Office (co-supervisors Thornton and Smith) and it is expected there will be opportunities to engage with and undertake a substantial placement (3-months). On completion, it is expected that the student will have a good grounding in climate science and its applications with excellent career prospects, particularly within the growing Climate Services sector.

Student profile:

This project will suit an individual with a strong quantitative background in mathematical/physical science, engineering, statistics or similar. The student will undertake high-quality meteorological research with a focus on process-understanding. They must be enthusiastic about going beyond traditional subject boundaries and to engage with industry stakeholders.

Funding particulars:

CASE studentship with UK Met Office

To apply, please follow the instructions at https://research.reading.ac.uk/scenario/apply/


Environmental Sciences (13) Physics (29)

Funding Notes

This project is potentially funded by the Scenario NERC Doctoral Training Partnership, subject to a competition to identify the strongest applicants.
Due to UKRI rules, the DTP can only fund a very limited number of international students. We will only consider applications from international students with an outstanding academic background placing them in the top 10% of their cohort.

References

Bloomfield, H. C., Brayshaw, D. J., Shaffrey, L. C., Coker, P. J., & Thornton, H. E. (2018). The changing sensitivity of power systems to meteorological drivers: a case study of Great Britain. Environmental Research Letters, 13(5), 054028.
Ely, C. R., Brayshaw, D. J., Methven, J., Cox, J. and Pearce, O. (2013) Implications of the North Atlantic Oscillation for a UK–Norway renewable power system. Energy Policy, 62. pp. 1420-1427.
Hurrell, J. W., Kushnir, Y., Ottersen, G., & Visbeck, M. (2003). An overview of the North Atlantic oscillation. Geophysical Monograph-American Geophysical Union, 134, 1-36.
Smith, D.M., Scaife, A.A., … Zhang, L. (2020). North Atlantic climate far more predictable than models imply. Nature, 583, 796-800.
Thornton, H. E., Scaife, A. A., Hoskins, B. J., Brayshaw, D. J (2017). The relationship between wind power, electricity demand and winter weather patterns in Great Britain. Environ. Res. Lett. 12 064017
Thornton, H. E., Scaife, A., Hoskins, B., Brayshaw, D., Smith, D., Dunstone, N., Stringer, N. and Bett, P. E. (2019) Skilful seasonal prediction of winter gas demand. Environmental Research Letters, 14 (2). 024009.

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