Exploring the boundary of skilful seasonal forecasts for extreme storms over the North-Atlantic (EX-Storms)
Lead Research Organisation:
University of Birmingham
Department Name: Sch of Geography, Earth & Env Sciences
Abstract
Severe synoptic-scale windstorm events in the Northwest Atlantic are affecting the UK and western Central Europe in winter (DJF). Damages in the magnitude of ca. EUR 3,610 million were recorded for the last season in 2021/22. Those damaging, rare events are linked to the development of strong storm cyclones in the climate system of the North-Atlantic. This project will explore the opportunity to provide skilful and useful predictions of the winter storm season ahead of the season in November. Thus, it will explore and understand our ability to predict whether it will be e.g., an active season (number of severe events) or not, whether we can have confidence in the forecast at the time of it being issued and what the reasons for this confidence would be.
Usability of predictions of the upcoming winter storm season depends a) on our understanding of the factors leading to the variability of storms, and b) on our understanding how a forecast for the next season will depend on these factors. This project will explore one potential critical factor and its role for the forecast skill of severe events leading to loss and damage.
One crucial factor of steering the climatic conditions in the North-Atlantic and Europe is the forcing of the atmospheric conditions (and here especially its baroclinicity) from anomalous sea-surface temperature patterns. So called re-emerging (in autumn/winter) temperature anomalies (from summer) would provide a potential mechanism for memory transport (via slow-varying components of the climate system) from late summer/early autumn to winter and finally resulting in extreme storm activity. Recent developments in seasonal forecast suites to forecast those oceanic re-emerging events are existing and this project will explore their role in steering variability of the storm season in reality as well as to quantify their potential role in gaining forecast skill in the model domain. EX-Storms will apply a novel approach (UNSEEN, i.a. pioneered by the applicant) to use non-realised but physically consistent events from century long seasonal and decadal hindcast (multi-member ensembles) to explore this physical pathway influencing the winter storm activity level. For the first time, EX-Storms will explore how far our current abilities allow for a pre-season view on the upcoming risk of severe storms.
Usability of predictions of the upcoming winter storm season depends a) on our understanding of the factors leading to the variability of storms, and b) on our understanding how a forecast for the next season will depend on these factors. This project will explore one potential critical factor and its role for the forecast skill of severe events leading to loss and damage.
One crucial factor of steering the climatic conditions in the North-Atlantic and Europe is the forcing of the atmospheric conditions (and here especially its baroclinicity) from anomalous sea-surface temperature patterns. So called re-emerging (in autumn/winter) temperature anomalies (from summer) would provide a potential mechanism for memory transport (via slow-varying components of the climate system) from late summer/early autumn to winter and finally resulting in extreme storm activity. Recent developments in seasonal forecast suites to forecast those oceanic re-emerging events are existing and this project will explore their role in steering variability of the storm season in reality as well as to quantify their potential role in gaining forecast skill in the model domain. EX-Storms will apply a novel approach (UNSEEN, i.a. pioneered by the applicant) to use non-realised but physically consistent events from century long seasonal and decadal hindcast (multi-member ensembles) to explore this physical pathway influencing the winter storm activity level. For the first time, EX-Storms will explore how far our current abilities allow for a pre-season view on the upcoming risk of severe storms.
People |
ORCID iD |
| Gregor Leckebusch (Principal Investigator) |
