Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
NH11.1 | Predicting natural hazards and climate extremes on seasonal to decadal timescales
Predicting natural hazards and climate extremes on seasonal to decadal timescales
Convener: Julia Lockwood | Co-conveners: Gillian Kay, Mihaela Caian, Lisa Ruff
The extreme heat, wildfire and flooding events around the world in 2023 have highlighted the challenges posed by climate-driven or modulated natural hazards. The transition from La Niña to El Niño brings the expectation of more potentially impactful climate hazards in the coming months. In our warming world, climate extremes are rising in intensity and frequency and so too is the demand for forewarning for the seasons and years ahead. In recent years there have been substantial advances in the science and systems of initialized climate prediction from seasonal to decadal timescales. Skilful forecasts on seasonal to decadal timescales can provide decision-makers with a valuable tool in planning for the extreme events of today and the near future. However, many challenges remain in realizing the potential of seasonal to decadal prediction of natural hazards, from scientific and technical to the production of information for climate services. Given the multi-disciplinary nature of risk assessment and resilience planning, how should our various research communities engage to foster the production and use of seasonal to decadal information on natural hazards?

This session therefore welcomes a broad range of recent research on the prediction of natural hazards on seasonal to decadal timescales and the development of climate services. It will also provide a forum for sharing examples and ideas on the uptake of seasonal to decadal climate information. Topics may include, but are not limited to:

• Skill and reliability of predictions of natural hazards, such as tropical and extra-tropical cyclones, extreme precipitation, flooding, wind drought, marine and land-based heatwaves, droughts, cold spells and compound events, on seasonal to decadal timescales.
• Sources of predictability and early warning of natural hazards: Which large scale climate modes/processes drive hazards/extremes and how well are they represented in models?
• Challenges to initialized climate prediction of natural hazards/extremes
• Advanced algorithms for seasonal-decadal prediction, data driven and machine learning methods, e.g. downscaling, prediction, ensemble optimisation, and comparison with traditional approaches.
• Actual or potential uses of seasonal to decadal predictions of natural hazards to support decision-making, challenges to and successes in uptake of seasonal to decadal climate services.