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EXTREME EVENTS: ARTIFICIAL INTELLIGENCE FOR DETECTION AND ATTRIBUTION

Descripción del proyecto

Inteligencia artificial para predecir los efectos del cambio climático sobre los fenómenos meteorológicos extremos

El cambio climático está modificando y exacerbando fenómenos meteorológicos extremos como, por ejemplo, las olas de calor, los incendios forestales de cuarta generación, los ciclones, las inundaciones y las sequías. El equipo del proyecto XAIDA, financiado con fondos europeos, empleará un método novedoso basado en datos y en el impacto para caracterizar, detectar y atribuir fenómenos meteorológicos extremos. Para ello, se utilizarán nuevas técnicas de inteligencia artificial y se contará con la ayuda de especialistas en atribución de fenómenos extremos, dinámica atmosférica, modelización del clima, aprendizaje automático e inferencia causal. Los hallazgos del proyecto proporcionarán información nueva sobre el efecto del cambio climático sobre fenómenos atmosféricos como los ciclones y las tormentas convectivas, que aún no se conocen ni cuantifican bien. También se desarrollarán herramientas para evaluar las rutas causales que provocan estos fenómenos meteorológicos extremos.

Objetivo

Often, extreme events provide representations of the future climate, but not all extremes are harbingers of the future. Thus, in order to be useful for adaptation in support to future projections, a causal link between events and human influence on climate must be established or refuted. This is why the “Extreme event attribution” field has recently developed. However, extreme event detection, attribution and projections studies currently face major limitations.
XAIDA will fill these gaps. Using new artificial intelligence techniques, and a strong two-way interaction with key stakeholders, it will (i) characterize, detect and attribute extreme events using a novel data-driven, impact-based approach, (ii) assess their underlying causal pathways and physical drivers using causal networks methods, and (iii) simulate high-intensity and as yet unseen events that are physically plausible in present and future climates.
To achieve this, XAIDA brings together teams of specialists in extreme event attribution, atmospheric dynamics, climate modelling, machine learning and causal inference, to:
● Understand the effect of climate change on a variety of impacting atmospheric phenomena currently poorly understood or quantified (cyclones, convective storms, long-lived anomalies, or summer compound events), both for past and future evolutions;
● Develop, in co-design with a community of key stakeholders, a novel, broader and impacts-based attribution and projection framework which extracts causal pathways of extremes;
● Develop storylines of events of unseen intensity, based on machine learning methods;
● Provide new tools for model assessment of causal pathways leading to extreme events and investigate the causes of disagreements between models and observations;
● Develop an interaction and communication platform with stakeholders with the ambition to improve training and education on climate change and impacts and to bring these developments to future operational climate services

Convocatoria de propuestas

H2020-LC-CLA-2018-2019-2020

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-LC-CLA-2020-2

Régimen de financiación

RIA - Research and Innovation action

Coordinador

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Aportación neta de la UEn
€ 1 026 261,25
Dirección
RUE MICHEL ANGE 3
75794 Paris
Francia

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Región
Ile-de-France Ile-de-France Paris
Tipo de actividad
Research Organisations
Enlaces
Coste total
€ 1 061 346,25

Participantes (16)