Project 4:
Uncertainty in Climate Projections
The question of what climate we will experience in the future is a vital one, with many repercussions. Our interest is in how we quantify and explain uncertainty in climate research. As part of his PhD work, Damian Oyarzún highlighted a common deficiency with projections used to inform planning around future marine productivity. Maryam Ilyas focused on uncertainty in sparse observation networks, which led to us introducing the first probabilistic definition of El Niño. Clair Barnes and her work on converting multiple models’ weather predictions into an accurate measure of forecast spread has led to UCL being contracted by the UK Met. Office to assess the fidelity of their projections for future UK climate.
The OACD group has undertaken research on the impact of climate change across a range of disciplines, both by students and researchers. These have resulted in publications led by UCL Geography taught students on groundwater, future river flows, and tropical cyclones. We have been supported the efforts of UCL and latterly LSE to refresh and deploy the PAGE integrated assessment model (used for the Stern review on the Economics of Climate Change). Whilst these efforts are yet to fully reach fruition, we have undertaken consultancy work (for the UK Met. Office), published research report.
- Barnes, C., Chandler, R., & Brierley, C. (2019). New approaches to postprocessing of multi-model ensemble forecasts. Quarterly Journal of the Royal Meteorological Society. http://doi.org/10.1002/qj.3632
- Bharadwaj, B., & Brierley, C. M. (2017). Ratcheting up ambition on climate policy: ECRC Research Reports (182). Environmental Change Research Centre
- Ho, J. T., Thompson, J. R., & Brierley, C. (2016). Projections of hydrology in the Tocantins-Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble. Hydrological Sciences Journal, 61(3), 551-567. http://doi.org/10.1080/02626667.2015.1057513
- Ilyas, M., Brierley, C. M., & Guillas, S. (2017). Uncertainty in regional temperatures inferred from sparse global observations: Application to a probabilistic classification of El Niño. Geophysical Research Letters. http://doi.org/10.1002/2017GL074596
- Opie, S., Taylor, R. G., Brierley, C. M., Shamsudduha, M., & Cuthbert, M. O. (2020). Climate–groundwater dynamics inferred from GRACE and the role of hydraulic memory. Earth System Dynamics, 11(3), 775-791. http://doi.org/10.5194/esd-11-775-2020
- Oyarzún, D., & Brierley, C. M. (2018). The future of coastal upwelling in the Humboldt current from model projections. Climate Dynamics, 1-17. http://doi.org/10.1007/s00382-018-4158-7
- Studholme, J., Hodges, K. I., & Brierley, C. (2015). Objective determination of the extratropical transition of tropical cyclones in the Northern Hemisphere. Tellus, 67. http://doi.org/10.3402/tellusa.v67.24474