“Boosted” realities: exploring the plausible limits of extreme weather through ensemble forecasts

High-impact low-likelihood extreme weather events and their impacts are of considerable interest to a variety of stakeholders across both the public and private sectors. Within the financial sector, there has been a focus on understanding how these kinds of extremes may change in the future, and quantifying the impact of such changes. However, we suggest that significant effort is still needed to fully assess the present day risk from such extremes, especially given the recent increase in apparently “unprecedented” extremes.

Within academic research, the “UNSEEN” framework has recently gained traction as one approach to understanding the limits of extreme weather. However, this framework has typically focussed on using seasonal forecast simulations as they explore a wider range of longer-scale modes of climate variability than near-term forecasts. Using seasonal forecast simulations, however, places limits on the direct applicability to local extremes and introduces challenges resulting from model drift. Here, we present a corresponding approach using state-of-the-art medium-range reforecasts to explore the extreme upper tail of the weather distribution, inspired by the ensemble boosting methodology, which has thus far been implemented within relatively coarse resolution climate models. A key feature of basing our analysis on weather forecast simulations, as opposed to high resolution climate model simulations, is that the events produced are explicitly linked to the weather that actually occurred. We can analyse dynamically what would have had to happen differently for the UNSEEN extreme to become reality — and therefore assess how plausible it is and find the key synoptic precursors.

These “boosted realities” are of wide utility - they provide physically consistent event storylines which can be used for emergency management and infrastructure design, or for the validation of the upper tail of event sets produced by the natural catastrophe models used in insurance. These plausible extremes could be ideal candidates for generating so called “Tales of Future Weather”, through the application of recently developed approaches in extreme weather attribution.