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HEATforecast SIGNED

Dynamical constraints for the predictability of heat waves in current and future climates

Total Cost €

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EC-Contrib. €

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Partnership

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Project "HEATforecast" data sheet

The following table provides information about the project.

Coordinator
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH 

Organization address
address: Raemistrasse 101
city: ZUERICH
postcode: 8092
website: https://www.ethz.ch/de.html

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 1˙499˙849 €
 EC max contribution 1˙499˙849 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-STG
 Funding Scheme ERC-STG
 Starting year 2020
 Duration (year-month-day) from 2020-03-01   to  2025-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) coordinator 1˙499˙849.00

Map

 Project objective

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.

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The information about "HEATFORECAST" are provided by the European Opendata Portal: CORDIS opendata.

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