SOURCE-LINKED INTELLIGENCE

Robust attribution of human-induced thermodynamic and dynamic contributions in historical changes of regional heat and cold waves over Europe

CORDIS · observation · Publication date unknown

nal details of heat and cold waves and circulation patterns by downscaling large ensembles of global-simulated data using the Weather Research and Forecasting (WRF) model and exploiting feature-based machine learning recognition; and iii) developing a Bayesian statistical approach to separate the human-induced thermodynamic and dynamic contributions. This robust attribution will address these current challenges, but also push event attribution research to a regional scale, greatly increasing confidence in attribution to human causes. Through this EXTREME project, I will increase my research skills, but also gain adequate soft skills in project management, supervision and dissemination with the ultimate intent to build a vibrant research group in Europe. heat and cold wave; temperature extreme; extreme event attribution; regional climate change and variability; global warming; land use/cover change; Weather Research and Forecasting model, WRF; CMIP6

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recordType

award

status

TERMINATED

region

EU

value

206887.68

unit

EUR