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) |
| Description | The project, Exploring the Boundary of Skilful Seasonal Forecasts for Extreme Storms over the North-Atlantic (Ex-Storms), aims to improve our understanding of the pre-season ability to skilfully forecast the severity of an upcoming European winter (December-February) windstorm season. Particularly we explore on the role of the ocean state in seasonal prediction systems. The knowledge, whether a pre-season forecast would be skilful, will open up vast opportunities for applications from private sector, such as risk management, to climate services. Our current key findings include: (i) Many European seasonal prediction systems show skills in predicting European winter windstorms. (ii) For the first time, multi-model ensemble prediction skill for windstorm frequency over Western and Central Europe has been identified. (iii) The difference of monthly climatological state (based on top 300 m mean potential temperature) of 3 ocean reanalyses in active and inactive European winter windstorms seasons have been explored for the period October to February. Our results show that while the spatial pattern of climatological thetaot300 is different for different reanalyses, there exists certain similarities, such as a. The importance of the positive thetaot300 anomalies located around the Caribbean in October and November. b. The progressively strengthening positive anomalies over the western boundary current (WBC) and the "gulf stream" over the winter months. c. Positive anomalies developed over the English Channel, the North Sea, and the Baltic Sea in December, January, and February. d. Similar observations could be reproduced with the ERA5 SST. (iv) The monthly climatological states (e.g. thetaot300) of 3 seasonal prediction systems (DWD, Meteo_France, and CMCC) have been evaluated against their respective ocean reanalysis that was used as initialisation. Independent of the initialisation months of interest (September, October, and November), there exists positive bias in the seasonal prediction system thetaot300 climatology over the WBC [except for DWD November initialisation]. The positive biases tend to progressively strengthen throughout the winter. a. The positive bias over the WBC could provide explanation that these seasonal prediction systems, the ratio of active EUWS season and inactive seasons is higher (2.70-3.97) than ERA5 (1.43). b. This is linked to enhancement of Eady growth rate in the upstream end of the storm tracks and thus provide much more baroclinity for storm formation in comparison to observations. |
| Exploitation Route | The project is not finished yet, and further outcomes will be produced expamding the portfolio of potential users. |
| Sectors | Agriculture Food and Drink Energy Environment Financial Services and Management Consultancy Leisure Activities including Sports Recreation and Tourism Government Democracy and Justice Retail Transport |
| Description | UK-China Coastal Climate Risk Management Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | In January 2024, Professor Leckebusch was invited, as an invited speaker and panel member, to give a presentation in the UK-China Coastal Climate Risk Management Workshop in Shenzhen, China. This workshop was organized by Professor Laixiang Sun (SOAS, University of Maryland) and Professor Zhan Tian (SuSTech) in collaboration with FCDO. In the workshop, we have engaged with representatives from various sectors, including National Meteorological Administration of China, Zhongzai Catastrophe Risk Management Co. Ltd, Deltares, Gallagher Research Centre, HR Wallingford, and Swiss Re. |
| Year(s) Of Engagement Activity | 2024 |