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Hybrid dry–hot Extremes prediction and AdapTation

Project description

Mitigating heatwaves and droughts with AI and land-based adaptation practices

As climate change intensifies, heatwaves are becoming more frequent and severe. This highlights the need to mitigate their impact on human health. The half a million deaths annually due to heat stress is a reminder that action must be taken. Funded by the European Research Council, the HEAT project seeks to address this issue by generating subseasonal forecasts of droughts and heatwaves, which cause human heat stress. Using a hybrid approach that combines physics-based models with AI algorithms, the project aims to understand the climatic drivers. HEAT will also explore land-based adaptation practices, such as afforestation, crop selection, and large-scale irrigation. Overall, HEAT aims to increase preparedness and resilience to future heat stress episodes.

Objective

Half a million people die due to heat stress every year. These numbers keep rising as climate continues to change. Heatwaves are becoming more frequent and severe, and disproportionally synchronised with droughts. Droughts reduce the ability of the land surface to cool down via evaporation, further enhancing heatwave temperatures. Nonetheless, how these compound drought–heatwave events spatially propagate, and their future lethality, remains unclear. Counterintuitive findings now indicate that drought can even dampen heatwave deadliness by reducing air humidity.

Consequently, our ability to forecast dry–hot events and their impacts on human health remains limited. Subseasonal timescales, between two weeks and two months, have traditionally been a blind spot: conventional weather forecast models are not tailored to these scales. However, the adoption of Artificial Intelligence (AI) may hold the key to fill this gap and reliably predict the upcoming occurrence of heat stress episodes weeks in advance. This would bring enormous societal benefits by enabling emergency planning.

In this project, we will explore an innovative way to generate subseasonal forecasts of droughts and heatwaves, and their consequent human heat stress episodes. A 'hybrid' approach will be embraced, i.e. an approach based on physics-based models combined with AI algorithms. Building upon this approach, we will deepen our understanding of the climatic drivers of human heat stress, and explore the future benefits of land-based adaptation practices designed to attenuate these events, including afforestation, crop selection, and large-scale irrigation.

Altogether, HEAT will foster our preparedness and resilience to future heat stress episodes – by improving their prediction, investigating the mechanisms that trigger them globally, and providing realistic and effective land-adaptation strategies to mitigate them – while heralding the adoption of hybrid approaches in climate science.

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Topic(s)

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Funding Scheme

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Call for proposal

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(opens in new window) ERC-2022-COG

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Host institution

UNIVERSITEIT GENT
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 983 000,00
Address
SINT PIETERSNIEUWSTRAAT 25
9000 GENT
Belgium

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Region
Vlaams Gewest Prov. Oost-Vlaanderen Arr. Gent
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 983 000,00

Beneficiaries (1)

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