CLImate INTelligence: Extreme events detection, attribution and adaptation design using machine learning (CLINT)

Description:

Weather and climate extremes pose challenges for adaptation and mitigation policies as well as disaster risk management, emphasizing the value of Climate Services in supporting strategic decision-making. Today Climate Services can benefit from an unprecedented availability of data, in particular from the Copernicus Climate Change Service, and from recent advances in Artificial Intelligence (AI) to exploit the full potential of these data.

The main objective of CLINT is the development of an AI framework composed of Machine Learning (ML) techniques and algorithms to process big climate datasets for improving Climate Science in the detection, causation and attribution of Extreme Events, including tropical cyclones, heatwaves and warm nights, and extreme droughts, along with compound events and concurrent extremes. Specifically, the framework will support

1. the detection of spatial and temporal patterns, and evolutions of climatological fields associated with Extreme Events,
2. the validation of the physically based nature of causality discovered by ML algorithms, and
3. the attribution of past and future Extreme Events to emissions of greenhouse gases and other anthropogenic forcing.

The framework will also cover the quantification of the Extreme Events impacts on a variety of socio-economic sectors under historical, forecasted and projected climate conditions by developing innovative and sectorial AI-enhanced Climate Services. These will be demonstrated across different spatial scales, from the pan European scale to support EU policies addressing the Water-Energy-Food Nexus to the local scale in three types of Climate Change Hotspots. Finally, these services will be operationalized into Web Processing Services, according to most advanced open data and software standards by Climate Services Information Systems, and into a Demonstrator to facilitate the uptake of project results by public and private entities for research and Climate Services development.

Project information

Lead

POLITECNICO DI MILANO, Italy

Partners

FONDAZIONE CENTRO EURO-MEDITERRANEOSUI CAMBIAMENTI CLIMATICI, Italy
HELMHOLTZ-ZENTRUM HEREON GMBH, Germany
AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS, Spain
SVERIGES METEOROLOGISKA OCH HYDROLOGISKA INSTITUT, Sweden
HKV LIJN IN WATER BV, Netherlands
E3-MODELLING AE, Greece
THE CLIMATE DATA FACTORY, France
DEUTSCHES KLIMARECHENZENTRUM GMBH, Germany
STICHTING IHE DELFT INSTITUTE FOR WATER EDUCATION, Netherlands
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS, United Kingdom
UNIVERSIDAD DE ALCALA, Spain
JUSTUS-LIEBIG-UNIVERSITAET GIESSEN, Germany
OPEN GEOSPATIAL CONSORTIOM EUROPE, Belgium
UNIVERSIDAD COMPLUTENSE DE MADRID, Spain

Source of funding

H2020-EU.3.5.1.