ProjektAI4PEX – Artificial Intelligence for Enhanced Representation of Processes and Extremes in Earth System Models

Grunddaten

Akronym:
AI4PEX
Titel:
Artificial Intelligence for Enhanced Representation of Processes and Extremes in Earth System Models
Laufzeit:
01.04.2024 bis 31.03.2028
Abstract / Kurz- beschreibung:
Global warming continues at an alarming rate, presenting unprecedented challenges to society that require urgent, science-led
mitigation and adaptation. Earth system models (ESMs) are essential tools for projecting climate change, providing important
information to decision makers. However, confidence in predicted climate change is undermined by a number of uncertainties; (i)
ESMs disagree on how much the Earth will warm for a given increase in atmospheric CO2 (Earth’s equilibrium climate sensitivity); (ii)
how much emitted CO2 will stay in the atmosphere to warm the planet (half the CO2 emitted by humans has been absorbed by the
land and ocean) and (iii) how much excess heat in the Earth system will enter the ocean interior, delaying surface warming (~90% of
the heat in the Earth system goes into the ocean). Central to these uncertainties are poorly understood, and poorly modelled, Earth
system feedbacks, in particular cloud feedbacks, carbon cycle feedbacks and ocean heat uptake. Poor representation of these
phenomena degrades the accuracy of ESM projections, with implications for anticipating future climate extremes and societal
impacts. We aim to improve the representation of these feedbacks in ESMs, reducing uncertainty in global warming projections. We
propose a multidisciplinary approach, focused on “learning” how to accurately describe processes underpinning these feedbacks,
through a fusion of observations with advanced machine learning and artificial intelligence. Such data and approaches, constrained
by the laws of physics, will deliver a step change in the accuracy of Earth system models.
AI4PEX Artificial Intelligence and machine learning for enhanced representation of Processes and EXtremes in Earth system models:
will place Europe at the forefront of a revolution in Earth system modelling, leading to increased accuracy of climate change
projections and superior support for implementation of the Paris Climate Agreement and the European Green Deal.

Beteiligte Mitarbeiter/innen

Leiter/innen

Fachbereich Informatik
Mathematisch-Naturwissenschaftliche Fakultät
Fachbereich Informatik
Mathematisch-Naturwissenschaftliche Fakultät

Ansprechpartner/innen

Fachbereich Informatik
Mathematisch-Naturwissenschaftliche Fakultät
Wilhelm-Schickard-Institut für Informatik (WSI)
Fachbereich Informatik, Mathematisch-Naturwissenschaftliche Fakultät
Exzellenzcluster: Maschinelles Lernen: Neue Perspektiven für die Wissenschaft (CML)
Zentren oder interfakultäre wissenschaftliche Einrichtungen
Tübingen AI Center
Fachbereich Informatik, Mathematisch-Naturwissenschaftliche Fakultät

Lokale Einrichtungen

Wilhelm-Schickard-Institut für Informatik (WSI)
Fachbereich Informatik
Mathematisch-Naturwissenschaftliche Fakultät

Geldgeber

Brüssel, Belgien
Hilfe

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