ECI’s unique approach uses very large ensembles of simulations of regional climate models to run two different analyses: to represent the current climate as it was observed, and to represent the same events in the world that might have been without human-induced climate change.
This methodological approach is supported by its widespread use in submissions to the annual Bulletin of the American Meteorological Society Special Issue on Explaining Extreme Events from a Climate Perspective. This analysis used very large ensembles of a regional climate model over Europe embedded in a global circulation model to assess the change in risk of extreme precipitation under two very distinct versions of the event:
- the observed extreme weather event itself, and
- a model of the extreme weather event with the impact of anthropogenic greenhouse gas emissions removed.
Using a distributed computing framework — weather@home — members of the public facilitate multi-thousand-member ensemble weather simulation experiments at both global and regional scales.
To accelerate the attribution analysis, the ECI team has developed a novel approach based on using forecast sea surface temperatures (SSTs) instead of observed SSTs. The team used the 2014 United Kingdom floods as a case study to demonstrate the robustness of this approach.
Maarten van Aalst
The Climate Centre is a specialist reference center for the International Federation of Red Cross and Red Crescent Societies (IFRC) and helps the Red Cross and Red Crescent Movement and other partners reduce the impacts of climate change and extreme weather events on vulnerable people. It will use its humanitarian network to identify disasters that will be analyzed by the WWA initiative. Further analysis will help place the event in the larger context of patterns of changing risk, including trends in vulnerability and exposure. The Climate Centre team is also helping develop an index of published articles relevant to specific events and geographical regions that will be consulted when WWA assesses a specific event. This “living database” includes peer-reviewed studies on regional trends in extremes, and in hydrology, decadal variability, future projections, and other published attribution studies that will allow us to more quickly assess the state of the science.
Geert Jan van Oldenborgh
The KNMI team contributes statistical analysis tools and climate data built in the KNMI Climate Explorer for event attribution. This public web application has fits to standard and extreme value distributions with co-variates that are optimised for extreme event attribution. The group collects and updates observational data in real-time at the Climate Explorer for trend detection in the past record and computation of return periods of the extreme event using long records that reach until the event under study. It also makes available a large set of climate model output that can be used for attribution studies, and stores the data used for past attribution studies to aid reproducibility. Work is in progress to facilitate the synthesis stage of attribution studies.