Climate change is expected to impact extreme weather, including changes in the frequency of floods, heatwaves and droughts in many parts of the world (Meehl et al, 2007, Seneviratne et al, 2012). Globally there is evidence that an increase in the frequency of warm temperature extremes and a decrease in the frequency of cold temperature extremes have already been observed (Alexander, et al, 2006, Trenberth et al, 2007, Seneviratne et al, 2012). Mounting evidence from across the climate system, including changes in temperatures, precipitation sea ice, snow cover, and oceanic temperature and salinity shows that there is an increasingly remote possibility that climate change is dominated by natural rather than anthropogenic factors (Stott et al, 2010). Regardless of the future trajectory of greenhouse gas emissions, societies already need to adapt to a changing climate, and, given the lags in the climate system’s response to changing forcing, are likely to have to adapt to further changes in climate which are locked in and unavoidable.

There is therefore a clear need to adapt effectively to climate change, particularly in Europe, where recent heatwaves (Schär et al., 2004; Beniston, 2004; Barriopedro et al, 2011, Dole et al., 2011), floods (Pall et al. 2011; Christensen and Christensen, 2004) and droughts (Feyen and Dankers, 2009) have demonstrated the vulnerability of European citizens to extreme weather. However, scientifically robust information about the extent to which recent extreme weather can be linked to climate change is often lacking (Schiermeier, 2011) and there is still substantial uncertainty in past trends in droughts and floods, due to methodological issues and to the lack of reliability of relevant observations (Seneviratne et al. 2012, Sheffield et al. 2012). This is important, because if weather-related risks and their possible changes with human influence on climate are not well understood, societies could be adapting poorly to ill conceived perceptions of their vulnerability to climate-related changes in extreme weather.

There is now an excellent opportunity to remedy this situation, because the science of climate attribution is beginning to address the challenge of quantifying the link between climate change and recent extreme weather events (Peterson et al, 2012). It has already been demonstrated that it is possible to estimate attributable changes in climate risks, with studies showing that human influence very likely more than doubled the chances of the European heatwave of 2003 (Stott et al, 2004), increased the risk of floods occurring in England and Wales in Autumn 2000 (Pall et al, 2011) and contributed to an enhanced risk of the Texas heatwave in 2011 (Rupp et al, 2011). But such studies are still thin on the ground, are research based and provide at times apparently contradictory conclusions, as was the case with analyses of the Russian heatwave of 2010 (Dole et al, 2011; Rahmstorf et al, 2011; Otto et al, 2012).

The vision is to develop a quasi-operational attribution system, well calibrated on a set of test cases for European extreme weather, that will provide to targeted groups of users, well verified, well understood assessments on the extent to which certain weather-related risks have changed due to human influences on climate. The system will include an ensemble of diagnostics that will help better understand the processes driving the events and the reliability of the methodologies used.

EUCLEIA has five top level objectives each of which is associated with project milestones and deliverables as follows, and which map directly onto the five Work Packages.

1) Derive the requirements that targeted user groups (including regional stakeholders, re-insurance companies, general public/media) have from attribution products and demonstrate the value to these users of the attribution products developed under EUCLEIA (WP4);

2) Develop experimental designs and clear ways of framing attribution studies in such a way that attribution products provide a fair reflection of current evidence on attributable risk. (WP5);

3) Develop the methodology for representing the level of confidence in attribution results so that attribution products can be trusted to inform decision making (WP6);

4) Demonstrate the utility of the attribution system on a set of test cases of European weather extremes (WP7);

5) Produce traceable and consistent attribution assessments on European climate and weather extremes on a range of timescales; on a fast-track basis in the immediate aftermath of extreme events, on a seasonal basis to our stakeholder groups, and annually to the BAMS attribution supplement (WP8).

These objectives relate to the topics addressed by the call as follows :

  • By producing evidence for whether the risk of similar events to those that have occurred in Europe has increased, decreased or remained stable (WP7 for test cases, WP8 for ongoing evaluation in near-real time);
  • By studying a number of historical cases, related to flooding, droughts and storm surge events (WP7);
  • By proposing exhaustive diagnostics of driving climate processes of events under study in order to properly evaluate the attribution system’s ability to simulate them and deliver user-relevant products together with appropriate reliability assessments (WP6);
  • By identifying those types of events where the science is too uncertain and observations insufficient to make a robust assessment of attributable risk (WP6,7,8);
  • By delivering a quasi-operational system that contributes significantly to the pre-operational capacities in the climate context of Copernicus by providing regularly updated, reliably calibrated information on the extent to which extreme weather and climate events are attributable to natural and anthropogenic factors (WP8);
  • By facilitating the development of climate adaptation strategies through working with stakeholder groups representing both commercial activities (insurance industry) and policy initiatives (regional managers, public) (WP4).


A key feature of the proposed approach is that it will start from stakeholder needs in developing and delivering attribution products. It will benefit considerably from international efforts to develop the underpinning science and to engage stakeholders. Many of the partners in this consortium are active participants in the long running International ad-hoc Detection and Attribution group (IDAG), which has over many years developed the science of detection and attribution and produced review papers summarising the progress in the field (IDAG, 2005; Stott et al, 2010) and which strongly supports EUCLEIA (see letter of support in Appendix 3). The Attribution of Climaterelated Events (ACE) group was formed at the IDAG meeting of 2009. It held its first meeting of scientists and, stakeholders in August, 2010 in Broomfield, Colorado, USA and its second meeting in Oxford, UK in September, 2012 and it is envisaged that future meetings will be held on an annual basis and will involve a substantial contribution from EUCLEIA (see also letters of support from ACE collaborators in Appendix 3). Crucially also, the project has close links with the development of seasonal climate forecasting as represented by the EUPORIAS and SPECS consortia and through the involvement of groups at the Met Office and EC-Earth. In addition, it also has close links to the EU-FP7 project DROUGHT-RSPI, which develops hydrological forecasting methodologies for droughts. The project will also benefit from the experience and data acquired from recent new Climate Model Intercomparison Project (CMIP5) simulations, and from several recently developed international in situ and remote sensing observation data sets. Seasonal forecasting is closely tied to the development of attribution systems, both in the aspect of model verification, a crucial aspect of both activities, and in the aspect of putting extreme weather into the long term context of climate variability and change. Our attribution system will be based on the model used for the Met Office seasonal forecasting, maximising the mutual benefit to both attribution and seasonal forecasting endeavours.

Consortium :

  • Met Office, UK
  • Eidgenoessische Technische Hochschule Zurich (ETH Zurich), Switzerland
  • National Centre for Scientific Research (CNRS), France
  • University of Edinburgh, UK
  • Fundacio Institut Catala De Ciencies Del Clima (IC3), Spain
  • Danmarks Meteorologiske Institut (DMI), Denmark
  • Koninklijk Nederlands Meteorologisch Instituut (KNMI), Netherlands
  • University of Reading, UK
  • University of Oxford, UK
  • Helmholtz-Zentrum Geesthacht Zentrum Für Material- Und Küstenforschung GmbH (HZG), Germany
  • Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), France


Involved members:

  • Yorghos Remvikos
  • Jean-Paul Vanderlinden (partner PI)




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