Summary
Extreme weather and climate events, such as heat waves, droughts and their combinations, are intrinsic aspects of the evolution of the climate system, and they can have substantial environmental and socio-economic impacts. Every extreme event is the result of a superposition of external drivers, natural and anthropogenic, and internal variability. Risk-based or probabilistic extreme event attribution assesses to what extent anthropogenic drivers modify the probability and magnitude, and hence the risk of an extreme event or a class of events to understand regional impacts of climate change. Surface conditions depend on the patterns of atmospheric circulation. Thus, in a specific region human-induced thermodynamic influence can be amplified or counteracted by human-induced change in the atmospheric circulation. The main goal of ANDANTE is to separate human-induced dynamic (i.e. circulation/flow) and thermodynamic contributions to the risk of selected extreme events in Europe and Africa. Since we are dealing with rare events we need large or even better very large ensembles of model simulations (~1,000 members) to do the flow-conditional probabilistic event attribution in statistically sound way (i.e. to get well-resolved probability distributions) with the methods of flow clusters (weather regimes/climate modes) and flow analogues. The project will make a key contribution to the development of the next-generation prediction and event attribution system. The produced new very large ensembles will be combined with the current-generation ensembles as well as multi-model climate simulations and multi-member reanalysis products to perform robust multi-method estimates of the univariate and multivariate (i.e. multi-variable) risk indicators. The risk assessment of selected extreme events manifested in surface temperature, precipitation, potential evapotranspiration and fire weather index can be useful to a wide spectrum of stakeholders interested in climate change impacts.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/846824 |
| Start date: | 01-03-2020 |
| End date: | 20-03-2023 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original description
Extreme weather and climate events, such as heat waves, droughts and their combinations, are intrinsic aspects of the evolution of the climate system, and they can have substantial environmental and socio-economic impacts. Every extreme event is the result of a superposition of external drivers, natural and anthropogenic, and internal variability. Risk-based or probabilistic extreme event attribution assesses to what extent anthropogenic drivers modify the probability and magnitude, and hence the risk of an extreme event or a class of events to understand regional impacts of climate change. Surface conditions depend on the patterns of atmospheric circulation. Thus, in a specific region human-induced thermodynamic influence can be amplified or counteracted by human-induced change in the atmospheric circulation. The main goal of ANDANTE is to separate human-induced dynamic (i.e. circulation/flow) and thermodynamic contributions to the risk of selected extreme events in Europe and Africa. Since we are dealing with rare events we need large or even better very large ensembles of model simulations (~1,000 members) to do the flow-conditional probabilistic event attribution in statistically sound way (i.e. to get well-resolved probability distributions) with the methods of flow clusters (weather regimes/climate modes) and flow analogues. The project will make a key contribution to the development of the next-generation prediction and event attribution system. The produced new very large ensembles will be combined with the current-generation ensembles as well as multi-model climate simulations and multi-member reanalysis products to perform robust multi-method estimates of the univariate and multivariate (i.e. multi-variable) risk indicators. The risk assessment of selected extreme events manifested in surface temperature, precipitation, potential evapotranspiration and fire weather index can be useful to a wide spectrum of stakeholders interested in climate change impacts.Status
SIGNEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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