Dr Antje Weisheimer (she)

ASPECT (Adaptation-oriented Seamless Predictions of European ClimaTe)

ASPECT aims for the setup and demonstration of a seamless climate information system with a time horizon up to 30yr, accompanied by underpinning research and utilisation of climate information for sectoral applications. The goal is to improve existing climate prediction systems and merge their outputs across timescales together with climate projections to unify a seamless climate information system as a standard for sectoral decision-making. The focus will be on European climate information but we will also look more widely where there is a policy interest and in regions of European interest. We will maintain a strong link into an exploit learning from the WCRP lighthouse activities on explaining and predicting earth system change.

Funders: Horizon Europe, UKRI

Duration: Jan 2023 to Dec 2026

People:

• Dr Beena Balan Sarojini
• Dr Muhammad Adnan Abid

Machine Learning for Early Warning Systems

Skillful early warnings and weather forecasts delivered by national and regional meteorological centres like KMD, EMI and ICPAC play a vital role in any effective disaster risk management system. The technical support from ECMWF, coupled with their global medium-range weather forecasting model and the longstanding collaboration with WFP, forms the foundation of this project’s objective. With partners in place, support from Google.org and the collective interest to challenge the status quo, the project entails training meteorological centres to run, adapt, and optimize Generative Adversarial Network (GAN) models to the complex rainfall patterns in eastern Africa. 

Funder: World Food Programme (WFP) 

Collaborators: ICPAC, Kenya Meteorological Department (KMD), ECMWF and Ethiopia Meteorological Institute (EMI)

Duration: October 2023 to March 2026

See also https://www.physics.ox.ac.uk/news/ai-led-science-innovation-protects-communities-hit-climate-change and https://www.youtube.com/watch?v=jgqvkLISF7Y&t=7s

People:

• Dr Fenwick Cooper
• Dr Shruti Nath
• Prof Tim Palmer

The forecast-based attribution approach utilises state-of-the-art high resolution operational weather and climate forecast models that successfully predicted the specific extreme event in question to study the role of certain climate drivers for the characteristics of the extreme.

Publications led our group:

• Leach, N., A. Weisheimer, M.R. Allen, and T.N. Palmer (2021). Forecast-based attribution of a winter heatwave within the limit of predictability. PNAS, https://doi.org/10.1073/pnas.2112087118
• Leach, N.J., C.D. Roberts,M. Aengenheyster, D. Heathcote, D.M. Mitchell, V. Thompson, T.N. Palmer, A. Weisheimer and M.R. Allen (2024). Heatwave attribution based on reliable operational weather forecasts. Nature Commun., ,doi:10.1038/s41467-024-48280-7
• Ermis, S., Leach, N.J., F. Lott, S. Sparrow and A. Weisheimer (2024). Event attribution of a midlatitude windstorm using ensemble weather forecasts. Env. Res.: Climate, doi:10.1088/2752-5295/ad4200
• Weisheimer, A., T.N. Palmer, N.J. Leach, M.R. Allen, C.D. Roberts and M.A. Abid (2025). CO2-induced Climate Change Assessment for the extrme 2022 Pakistan Rainfall using Seasonal Forecasts. npj climate and atmospheric science, 8, 262, doi:10.1038/s41612-025-01136-3

People:

• Dr Nick Leach
• Shirin Ermis
• Olivia Vashti Ayim
• Lei Gu

This has been a topic of much interest and covers a wide range of studies. 

Relevant studies:

• Patterson, M. D.J. Befort, J. Lockwood, J. Slattery and Weisheimer, A. (2025). The representation of temperature trends in C3S seasonal forecast systems. Atmos. Sci. Lett.,doi:10.1002/asl.1316/
• O'Reilly, C.H., D. MacLeod, D.J. Befort, T.G. Shepherd and Weisheimer, A. (2025). Evaluating seasonal forecast improvements over the past two decades. Q. J. R. Meteorol. Soc. ,doi:10.1002/qj.70036/
• Weisheimer, A., L.H. Baker, J. Broecker, C.I. Garfinkel, S.C. Hardiman, D.L.R. Hodson, T.N. Palmer, J.I. Robson, A.A. Scaife, J.A. Screen, T.G. Shepherd, D.M. Smith and R.T. Sutton (2024). The Signal-to-Noise Paradox in Climate Forecasts: Revisiting our Understanding and Identifying Future Priorities. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-24-0019.1
• Wright, M.J., A. Weisheimer, and T. Woollings (2024). Multi-decadal skill variability in predicting the spatial patterns of ENSO events Geophys. Res. Lett., doi:10.1029/2023GL107971
• Patterson, M., D. Befort, C. O'Reilly and A. Weisheimer, (2024). The ECMWF SEAS5 seasonal forecast of the hot and dry European summer of 2022. Q. J. R. Meteorol. Soc., doi:10.1002/qj.4851
• Weisheimer, A., M. Balmaseda, T. Stockdale, M. Mayer, S. Sharmila, H. Hendon and O. Alves (2022). Variability of ENSO forecast skill in 2-year global reforecasts over the 20th Century. Geophys. Res. Lett.,  doi:10.1029/GL2022097885
• Patterson, M., Weisheimer, A., D. Befort and C. O'Reilly (2022). The strong role of external forcing in seasonal forecasts of European summer temperature Env. Res. Lett.,  doi:10.1088/1748-9326/ac9243
• Weisheimer, A., D. Befort, D. MacLeod, T.N. Palmer, C. O'Reilly and K. Strommen (2020). Seasonal forecasts of the 20th Century Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-19-0019.1
• O'Reilly, C., A. Weisheimer, D. MacLeod, D. Befort and T.N. Palmer (2020). Assessing the robustness of multidecadal variability in Northern Hemisphere wintertime seasonal forecast skill. Q. J. R. Meteorol. Soc., doi:10.1002/qj.3890
• Weisheimer, A., D. Decremer, D. MacLeod, C. O'Reilly, T. Stockdale, S. Johnson and T.N. Palmer (2018). How confident are predictability estimates of the winter North Atlantic Oscillation? Q. J. R. Meteorol. Soc., doi:10.1002/qj.3446
• O'Reilly, C.H., T. Woollings, L. Zanna and A. Weisheimer (2018). The impact of tropical precipitation on summertime Euro-Atlantic circulation via a circumglobal wave-train. J. Clim, doi:10.1175/JCLI-D-17-0451.1
• MacLeod, D., C. O'Reilly, T.N. Palmer and A. Weisheimer (2018). Flow dependent ensemble forecast spread in seasonal forecasts of the boreal winter extratropics. Atm. Sci. Lett., doi:10.1002/asl.815
• O'Reilly, C.H., A. Weisheimer, T. Woollings, L. Gray and D. MacLeod (2018). The importance of stratospheric initial conditions for winter North Atlantic Oscillation predictability and implications for the signal-to-noise paradox. Q. J. R. Meteorol. Soc., doi:10.1002/qj3413
• Weisheimer, A., N. Schaller, C. O'Reilly, D. MacLeod and T.N. Palmer (2017). Atmospheric seasonal forecasts of the 20th Century: multi-decadal variability in predictive skill of the winter North Atlantic Oscillation and their potential value for extreme event attribution. Q. J. R. Meteorol. Soc., 143, 917-926, doi:10.1002/qj.2976
• O'Reilly, C.H., J. Heatley, D. MacLeod, A. Weisheimer, T.N. Palmer, N. Schaller, and T. Woollings (2017). Variability in seasonal forecast skill of Northern Hemisphere winters over the 20th Century. Geophys. Res. Lett., doi:10.1002/2017GL073736
• Shi, W., N. Schaller, D. MacLeod, T.N. Palmer and A. Weisheimer (2015). Impact of hindcast length on estimates of seasonal climate predictability. Geophys. Res. Lett. , 42, doi:10.1002/2014GL062829.

People:

• Matt Wright
• Benjamin Keller

Previously:

• Tim Hempel (now at German Weather Service DWD)
• Matt Patterson (now at NCAS St Andrews)
• Chris O'Reilly (now at University of Reading)
• Daniel Befort (now at ECMWF)
• David MacLeod (now at University of Cardiff)

HURACAN (HUrricane Risk Amplification and Changing north Atlantic Natural disasters)

Huracán is a strategic collaboration between the UK and US with the overarching objective to deliver a new, physically based understanding of the risks posed to the British Isles/Western Europe and the Northeast United States by Cyclones of Tropical Origin (CTOs) in a changing climate. The risk of CTOs is currently poorly quantified, owing to a fundamental lack of evidence; yet these events are high-impact and are expected to become more frequent in the future. Poor theoretical understanding impedes confident prediction. Huracán brings together world-leading expertise—from both sides of the Atlantic—to study, for the first time, the full life cycle of CTOs, a key requirement for scientific progress. Huracán will address fundamental knowledge gaps exploiting diverse observations, theoretical advances and hypothesis-driven analysis of a wealth of numerical simulations, to provide actionable information to decision-makers. Huracán will explore physically plausible scenarios, given the predictable components of future climate and the conditional dependence of cyclone processes on those components. Huracán will experiment with the simulation of CTO-specific impacts and investigate worst-case configurations of the physical climate system. This concerted effort will transform the assessment of CTO risks across the North Atlantic mid-latitudes.

Funders: NERC, NSF

Duration: March 2023 to Feb 2027

People: 

• Dr Stella Bourdin
• Callum Pemberton (MPhys student 2023/24, AOPP)
• Lewis Grant (MPhys student 2024/25, AOPP, now at University of Reading)

DART (Dengue Advanced Readiness Tool)

DART aims at developing an integrated digital system for dengue outbreak prediction and monitoring. Researchers at the University of Oxford  and Oxford University Clinical Research Unit in Vietnam will develop an automated forecasting system that integrates datasets from across Hanoi and Ho Chi Minh. The team are to build a mobile and desktop application  capable of supporting predictions of dengue within cities; the application will integrate weather and disease forecasts in order to improve understanding of the relationship between them. 

Funder: Wellcome Trust

Duration: Dec 2022 to Nov 2025

People:

• Dr Iago Perez Fernandez (Department of Engineering Science)
• Lucy Main (MPhys student 2022/23 in AOPP)
• Dr Sarah Sparrow (PI, Department of Engineering Science)
• Prof David Wallom (Department of Engineering Science)
• Prof Sophie Yacoub (Oxford University Clinical Research Unit, Centre for Tropical Medicine and Global Health)

Publications:

Main, L., S. Sparrow, Weisheimer, A. and M. Wright (2024). Verification of ECMWF probabilistic precipitation and temperature forecasts over Vietnam for use in dengue warning system Meteorolog. Apps., submitted