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EVE Report Summary

Project ID: 322208
Funded under: FP7-PEOPLE
Country: United Kingdom

Final Report Summary - EVE (Extreme Events Variability over Europe)

Meteorological and climatological extreme events have an extra-ordinary high impact on financial, economic as well as social conditions in Europe and are one of the most dangerous triggers of failures in the administrative and infra-structural system of our society. Steering factors for extreme event occurrence may work on different time scales from days to centuries and may stem from internal as well as external forcing factors.
Consequently, EVE will work to the following five Research Objectives:
1) Investigation of the synoptic scale event-to-event variability and assessment of reasons for different developments.
2) Identification of mechanisms steering the seasonal variability of extreme events, thus leading to potential predictability and its related predictive skill
3) Analysis of decadal to multi-decadal scale variability of extremes in relation to large-scale variability modes dominant for the North-Atlantic and Europe.
4) Identification of the potential anthropogenic climate change signal on extremes by means of the IPCC RCP scenario simulations.
5) Assessment of decadal to long-term variability of extreme event occurrence on impacts in society and economy and its uncertainty.
The work is organized into different time scales involved into the development of extreme events. Starting with synoptic scale process to transform a normal mid-latitude cyclone into a severe, damage prone surface wind event, followed by research carried out to the understanding and predictability of extreme cyclone occurrence on seasonal time scales, up to multi-decadal and centennial perspectives, the respective steering factors and main modes of variability are investigated.
On the synoptic time scale, a new methodological approach to analyse different influences of major forcing factors were developed and applied. Based on the two-fold identification of extreme events by the means of core pressure and extreme wind speeds, the cyclone-to-cyclone variability was analysed with an EOF-analysis based on Lagrangian cyclone composites to the time of the strongest intensification. Results reveal that different variability patterns for different forcing factors are of relevance for the transformation process.
We analysed the climatological representation and assess the seasonal prediction skill of extra-tropical cyclones and windstorms in three state-of-the-art multi-member seasonal prediction systems: ECMWF-System3, ECMWF-System4 and Met Office – HadGEM-GA3. In general, we find good agreement of spatial climatological distributions of both extra-tropical cyclones and windstorms in comparison with reanalysis data (ERA-Interim). Depending on the forecast model and region analysed there are however some positive and negative biases present. All seasonal prediction systems show widely small to moderate positive skill in forecasting the winter season frequency of extra-tropical cyclones and windstorms over the Northern Hemisphere. The skill is highest for extra-tropical cyclones at the downstream end of the Pacific stormtrack and for windstorms at the downstream end of the Atlantic stormtrack. We thus reveal for the first time significant, relevant skill for high-impact windstorms with fundamental implications for highly damage vulnerable regions across western central Europe. We also suggest, using the NAO is in the first place a very simple and effective method, but increased forecast skill is detected using the full information of the model suits and to identify and track windstorms directly. In consequence, this will mean that in addition to the large-scale influence of the NAO other factors may contribute to real predictability over impact relevant regions over Europe in the existing forecast suits.
In winter 2013-2014, the UK experienced exceptional stormy and rainy weather conditions. The period from December 2013 to February 2014 was the stormiest for at least 20 years according to the UK Met Office. This was accompanied by higher SSTs in the North Pacific and cold conditions in North America. A potential driver for positive sea surface temperature anomalies in the North Pacific and cold conditions in central North America further downstream is discussed to be warm surface waters of the tropical West Pacific (Palmer, 2014; Hartmann, 2015). It has been suggested that increasing sea surface temperatures in the tropical West Pacific could also be the cause for extreme weather over the British Isles. We show that the conditions in the Pacific and its induced anomalies over the North American continent are generally not sufficient to explain the extra-ordinary high winter windstorm frequency over the North East Atlantic and the British Isles. The induced conditions were favourable to increase the number of storms in winter 2013-14, but the explained variability is too small to attribute this particular extreme mainly to conditions in the tropical Pacific and its imprinted anthropogenic signal. One alternative potential driver partly explaining the anomalous high storm frequency in 2013-14 could have been the unprecedented anomalies of sea surface temperatures in the West Atlantic. In conclusion, the anomalous high number of windstorms in winter 2013-14 over the North East Atlantic and the British Isles can thus not directly be attributed to anthropogenic influenced responsible factors as apparent in the tropical West Pacific. Very suitable conditions of natural internal interannual variability, including conditions over the tropical and North Pacific, North America and the West Atlantic, favoured the record number of storm counts.
Further, we investigated long-term trends of extra-tropical cyclones and windstorms in ERA-20C and NOAA-20CR reanalyses. The results indicate substantial differences in low-frequency variability between the two datasets – especially in the first half of the 20th century – expressed in different signs and/or magnitudes of long-term trends. This is hampering a reliable analysis of real long-term trends of cyclone and windstorm activity. However, higher-frequency variability is in good agreement between both datasets especially for the Northern Hemisphere.
We analysed multiple major AOGCM simulations from the CMIP5 model data archive with respect to the strength, position, and eccentricity of the polar frontal structure. Results reveal a significant northward shift of the position of the polar front under anthropogenic climate change and thus a reduction of extend of the tropospheric Circumpolar Vortex (CPV) in an ensemble mean perspective with meridional different magnitudes. Connected to this will be a change in the major areas of baroclinic instability over the northern hemisphere, as well as a reduction in circularity and speed of the CPV affecting extreme event cyclone occurrence.
One of the fundamental aspect of impacts on e.g. insurance industry is the frequent occurrence of severe damage-producing windstorms in so-called clusters. This clustering behaviour has first to be understood to provide proper guidance on future climate change impacts, e.g. to the financial industry. This is realised by developing a statistical model relating the winter storm counts to known teleconnection patterns affecting European weather and climate conditions (e.g. North Atlantic Oscillation (NAO), Scandinavian Pattern (SCA), etc.). In addition to the SCA and the NAO that are found to be the essential drivers for most areas within the European domain, other teleconnections (e.g. East Atlantic Pattern) are found to be more significant for the inter-annual variability in certain regions. Furthermore, a statistical model allowing an estimation of the expected number of storms and the degree of clustering of an individual winter windstorm season was developed and showing positive usable skill. This feature is be of specific interest for the actuarial sector.
To determine the relationship between European heat wave event characteristics and large-scale modes of climate variability, a stepwise multiple linear regression model was developed in order to further aid explanatory analysis and to constitute the first step of a heat wave impact model. Results revealed an increase in warm extremes corresponding with a rise in global mean temperature since 1970.
In summary, beside the scientific peer reviewed publications, EVE has helped to deliver three important results and outputs for socio-economic aspects: At first, EVE could, for the first time ever, proof that there is useful skill of seasonal forecasts for severe European winter windstorms. This is of immense impact for the financial sector, e.g. the insurance industry.
At second, two models were developed with high potential of socio-economic applications: For extreme windstorms a clustering model, allowing prediction of the amount of clustering of damage prone windstorms and for European heatwaves a model to predict the impact of changes in large-scale variability modes on heatwave frequencies.

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United Kingdom


Life Sciences
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