Description du projet
Améliorer la prédiction des futures vagues de chaleur
Les vagues de chaleur peuvent avoir des effets néfastes sur la santé humaine. Les projections du changement climatique indiquent que la fréquence et la gravité des vagues de chaleur ne cesseront d’augmenter au cours des prochaines décennies. Toutefois, les modèles demeurent incapables de prédire les vagues de chaleur dans un délai de quelques semaines, un temps de planification essentiel. Les avertissements précoces sur les températures extrêmes seraient ainsi d’une grande importance. Le projet HEATforecast, financé par l’UE, mettra au point une hiérarchie fondée sur les processus pour les systèmes de prédiction afin d’améliorer la compréhension et la prédiction des vagues de chaleur. Le projet vise à renforcer les connexions entre les communautés de la prédictibilité et de la dynamique pour favoriser l’étude de la prédictibilité et de la dynamique des fluides atmosphériques au-delà des vagues de chaleur.
Objectif
In summer 2018, a devastating heat wave affected the entire Northern Hemisphere. Climate change projections indicate that the severity and frequency of such heat waves will further increase over the next decades. At the same time, models remain unable to predict heat waves at lead times of a few weeks – a crucial planning timescale. The poor prediction skill at timescales of weeks to months is to a large extent due to an incomplete understanding of the underlying physical drivers of heat waves. In particular, the atmospheric fluid dynamics responsible for heat waves and their prediction are not sufficiently understood and tend to be biased in models. The seasonal cycle further modulates the drivers and predictability of heat waves. Climate change projections disagree on the changes in atmospheric dynamics responsible for heat waves. The proposed research takes an unconventional path to address these open questions by building a process-based hierarchy of prediction systems ranging from a dry dynamical core to a prediction system using full physics. This hierarchy approach is novel for prediction systems. By systematically adding processes to the model, the relative contribution of atmospheric dynamics and surface drivers for heat waves and their predictability can be estimated throughout the seasonal cycle and for the projected changes in heat waves with climate change. While solving a fundamental question in atmospheric fluid dynamics, the proposed research aims to significantly extend the warning horizon and thereby minimize the societal consequences for future heat waves, which are expected to increase in frequency but so far remain unpredictable. This project combines the experience and strengths of the PI in atmospheric dynamics, predictability, and their application in a timely manner by increasing the connections between the dynamics and predictability communities that will benefit the study of atmospheric fluid dynamics and predictability beyond heat waves.
Champ scientifique
Programme(s)
Thème(s)
Régime de financement
ERC-STG - Starting GrantInstitution d’accueil
1015 LAUSANNE
Suisse