Operation Attribution Service : ClimaMeter
In the aftermath of an extreme weather event, the event is studied more and more often by an operational attribution service. Two examples of such operational attribution services are used within XAIDA. These operational services generally answer slightly different questions and are complementary.
ClimaMeter is an international consortium designed to attribute extreme weather events to climate change, providing scientifically robust and actionable insights to inform public discourse and policy.
Description
ClimaMeter works collaboratively with researchers globally to assess how climate change influences the frequency and intensity of extreme weather events. By integrating state-of-the-art statistical tools and historical weather data, ClimaMeter delivers rapid assessments of extreme weather events within days to weeks of their occurrence. The initiative also examines meteorological conditions to highlight the exceptionality of the events analyzed.
The objects studied (i.e., « the events ») are surface-pressure patterns over certain regions and averaged over a certain number of days, that have led to extreme weather conditions leading to heatwaves, coldspells, floods, windstorms and wildfires. The analogues methodology consists of looking for weather conditions similar to those that caused the extreme events of interest using physics-informed machine-learning methodologies. The focus is 1950 to present, when widespread observations of climate variables from satellites became available.
All reports are available with a DOI within the platform Zenodo. ClimaMeter reports are already widely used and cited by the international press but also in scientific and Wikipedia articles and used for climate litigation purposes.
Potential User Groups
ClimaMeter caters to diverse audiences through tailored outputs:
i) General Public and Media: Press releases with accessible language for non-specialist audiences.
ii) Science-Informed Readers: Web summaries providing key insights and context.
iii) Scientific Community: Comprehensive technical reports detailing methodologies and findings.
References
Faranda, D., Messori, G., Coppola, E., Alberti, T., Vrac, M., Pons, F., Yiou, P., Saint Lu, M., Hisi, A. N. S., Brockmann, P., Dafis, S., Mengaldo, G., and Vautard, R.: ClimaMeter: contextualizing extreme weather in a changing climate, Weather Clim. Dynam., 5, 959–983, (2024).
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003469.
Tools
GreenEarthNet is a machine learning-powered toolkit for predicting ecosystem responses to climate changes by leveraging Earth observation data and climate models. It supports effective environmental monitoring and forecasting for improved climate action.
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Stochastic Weather Generation is a computationally light tool to simulate temperatures for worse case heat extremes, at city up to country level.
In the aftermath of an extreme weather event, the event is studied more and more often by an operational attribution service. Two examples of such operational attribution services are used within XAIDA. These operational services generally answer slightly different questions and are complementary.
World Weather Attribution (WWA), an initiative founded
Importance sampling is a way to preferentially select out of a range of model simulations the ones that will lead to extremes of the metric of interest in an early stage of simulation, thus increasing computing efficiency for the cases of interest.
Ensemble boosting uses climate models to efficiently generate very intense and rare weather and climate extremes that can be analyzed for planning and stress testing of critical infrastructure.
The Artificial Intelligence for Disentangling Extremes (AIDE) toolbox allows for tackling generic problems of detection and impact assessment of events such as tropical cyclones and severe convective storms, heat waves, and droughts, as well as persistent winter extremes, among others
In the aftermath of an extreme weather event, the event is studied more and more often by an operational attribution service. Two examples of such operational attribution services are used within XAIDA. These operational services generally answer slightly different questions and are complementary.
ClimaMeter is an international consortium designed to
Storyline is a methodology to determine when in the future extreme heat events above a chosen threshold become likely in cities, and to present the meteorological conditions that lead up to it.
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