Prediction of extreme events
We make predictions of the probability of occurrence of extreme phenomena adapted to the needs of each case study.
The number of climate-related catastrophes has been progressively increasing over the past two decades and this trend, according to climate change projections, could be drastically exacerbated in the medium to long term.
In this framework, through a multidisciplinary team and a solid experience acquired in recent relevant projects, the ICARIA project promotes a modeling methodology to better understand the climate impacts produced by catastrophes, optimizing adaptation solutions, measuring their adequacy, sustainability and cost-effectiveness.
The FIC is responsible, within the framework of information processing for the development of ICARIA, for coordinating all tasks related to meteorology and climate, particularly: the analysis of meteorological information, the production of climate scenarios, and their subsequent integration into the workflow according to format requirements, data structures and implementation in the case studies.
Specifically, FIC leads the “Climate scenario building” task, where observed historical series of the variables of interest are analyzed and corrected thanks to the use of ERA5-Land reanalysis. These series are then used to apply the FICLIMA statistical downscaling methodology to 10 CMIP6 models, obtaining local climate change projections for the 3 case studies, both for average climate and for extreme events (torrential rain, droughts and heat waves, among others).
Finally, FIC provides support to the consortium in the determination of data requirements (format, structure and periods) for their subsequent integration and use in the rest of the project tasks, as well as support in the interpretation and use of the information generated.
Technical details:
Name: ICARIA. Improving ClimAte Resilience of crItical Assets (ICARIA)
Funding: Horizon Europe
Project ID: 101093806
Project Coordinator: Aquatec, Beniamino Russo
FIC Role: Partner
FIC Coordinator: César Paradinas
We make predictions of the probability of occurrence of extreme phenomena adapted to the needs of each case study.