Summary
"State-of-the-art simulations and observations highlight the self-organization of convective clouds. Our recent work shows two aspects: these clouds are capable of unexpected increase in extreme precipitation when temperature rises; interactions between clouds produce the extremes. As clouds interact, they organize in space and carry a memory of past interaction and precipitation events. This evidence reveals a severe shortcoming of the conventional separation into ""forcing"" and ""feedback"" in climate model parameterizations, namely that the ""feedback"" develops a dynamics of its own, thus driving the extremes. The major scientific challenge tackled in INTERACTION is to make a ground-breaking departure from the established paradigm of ""quasi-equilibrium"" and instantaneous convective adjustment, traditionally used for parameterization of ""sub-grid-scale processes"" in general circulation models. To capture convective self-organization and extremes, the out-of-equilibrium cloud field must be described. In INTERACTION, I will produce a conceptual model for the out-of-equilibrium system of interacting clouds. Once triggered, clouds precipitate on a short timescale, but then relax in a ""recovery"" state where further precipitation is suppressed. Interaction with the surroundings occurs through cold pool outflow,facilitating the onset of new events in the wake. I will perform tailored numerical experiments using cutting-edge large-eddy simulations and very-high-resolution observational analysis to determine the effective interactions in the cloud system. Going beyond traditional forcing-and-feedback descriptions, I emphasize gradual self-organization with explicit temperature dependence. The list of key variables of atmospheric water vapor, temperature and precipitation must therefore be amended by variables describing organization. Capturing the self-organization of convection is essential for understanding of the risk of precipitation extremes today and in a future climate.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/771859 |
| Start date: | 01-07-2018 |
| End date: | 30-04-2024 |
| Total budget - Public funding: | 1 314 800,00 Euro - 1 314 800,00 Euro |
Cordis data
Original description
"State-of-the-art simulations and observations highlight the self-organization of convective clouds. Our recent work shows two aspects: these clouds are capable of unexpected increase in extreme precipitation when temperature rises; interactions between clouds produce the extremes. As clouds interact, they organize in space and carry a memory of past interaction and precipitation events. This evidence reveals a severe shortcoming of the conventional separation into ""forcing"" and ""feedback"" in climate model parameterizations, namely that the ""feedback"" develops a dynamics of its own, thus driving the extremes. The major scientific challenge tackled in INTERACTION is to make a ground-breaking departure from the established paradigm of ""quasi-equilibrium"" and instantaneous convective adjustment, traditionally used for parameterization of ""sub-grid-scale processes"" in general circulation models. To capture convective self-organization and extremes, the out-of-equilibrium cloud field must be described. In INTERACTION, I will produce a conceptual model for the out-of-equilibrium system of interacting clouds. Once triggered, clouds precipitate on a short timescale, but then relax in a ""recovery"" state where further precipitation is suppressed. Interaction with the surroundings occurs through cold pool outflow,facilitating the onset of new events in the wake. I will perform tailored numerical experiments using cutting-edge large-eddy simulations and very-high-resolution observational analysis to determine the effective interactions in the cloud system. Going beyond traditional forcing-and-feedback descriptions, I emphasize gradual self-organization with explicit temperature dependence. The list of key variables of atmospheric water vapor, temperature and precipitation must therefore be amended by variables describing organization. Capturing the self-organization of convection is essential for understanding of the risk of precipitation extremes today and in a future climate."
Status
SIGNEDCall topic
ERC-2017-COGUpdate Date
27-04-2024
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