Summary
Vertical exchange in the atmospheric boundary is primarily due to turbulence, but turbulence may cease locally as a consequence of stable density stratification. This state of turbulence intermittency challenges traditional geophysical approaches to represent turbulent mixing. Field observations of the phenomenon are hard to obtain because of broad-scale interacting processes. Existing numerical approaches based on bulk turbulence closures reach their limits because they neglect the relevance of large-scale intermittency for turbulent mixing. Hence, process-level insight to turbulence intermittency in the atmospheric boundary layer is lacking which has dramatic consequences for the forecast of minimum temperature, of frost and fog situations, and of the potential for wind-power extraction.
trainABL recognizes the geophysical phenomenon of turbulence intermittency in the atmospheric boundary layer as a fluid mechanics problem. A virtual-lab approach based on direct numerical simulation yields an appropriate turbulence-resolving representation of the intermittently turbulent atmospheric boundary layer. The quantitative insight into large-scale intermittency offered by direct numerical simulation in combination with large-eddy simulation and observational data allows to transfer the emerging physical understanding to the geophysical range of parameters. This paves the avenue towards a novel turbulence mixing representation based on factorization of the turbulent flux into a reference flux and pre-factor accounting for large-scale intermittency. trainABL will thus provide a first physically consistent turbulent mixing parametrization that acknowledges the importance of turbulence intermittency, covers the entire vertical range of the atmospheric boundary layer, and is valid for all regimes of stratification.
trainABL recognizes the geophysical phenomenon of turbulence intermittency in the atmospheric boundary layer as a fluid mechanics problem. A virtual-lab approach based on direct numerical simulation yields an appropriate turbulence-resolving representation of the intermittently turbulent atmospheric boundary layer. The quantitative insight into large-scale intermittency offered by direct numerical simulation in combination with large-eddy simulation and observational data allows to transfer the emerging physical understanding to the geophysical range of parameters. This paves the avenue towards a novel turbulence mixing representation based on factorization of the turbulent flux into a reference flux and pre-factor accounting for large-scale intermittency. trainABL will thus provide a first physically consistent turbulent mixing parametrization that acknowledges the importance of turbulence intermittency, covers the entire vertical range of the atmospheric boundary layer, and is valid for all regimes of stratification.
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| Web resources: | https://cordis.europa.eu/project/id/851374 |
| Start date: | 01-06-2020 |
| End date: | 28-02-2026 |
| Total budget - Public funding: | 1 872 581,00 Euro - 1 872 581,00 Euro |
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Original description
Vertical exchange in the atmospheric boundary is primarily due to turbulence, but turbulence may cease locally as a consequence of stable density stratification. This state of turbulence intermittency challenges traditional geophysical approaches to represent turbulent mixing. Field observations of the phenomenon are hard to obtain because of broad-scale interacting processes. Existing numerical approaches based on bulk turbulence closures reach their limits because they neglect the relevance of large-scale intermittency for turbulent mixing. Hence, process-level insight to turbulence intermittency in the atmospheric boundary layer is lacking which has dramatic consequences for the forecast of minimum temperature, of frost and fog situations, and of the potential for wind-power extraction.trainABL recognizes the geophysical phenomenon of turbulence intermittency in the atmospheric boundary layer as a fluid mechanics problem. A virtual-lab approach based on direct numerical simulation yields an appropriate turbulence-resolving representation of the intermittently turbulent atmospheric boundary layer. The quantitative insight into large-scale intermittency offered by direct numerical simulation in combination with large-eddy simulation and observational data allows to transfer the emerging physical understanding to the geophysical range of parameters. This paves the avenue towards a novel turbulence mixing representation based on factorization of the turbulent flux into a reference flux and pre-factor accounting for large-scale intermittency. trainABL will thus provide a first physically consistent turbulent mixing parametrization that acknowledges the importance of turbulence intermittency, covers the entire vertical range of the atmospheric boundary layer, and is valid for all regimes of stratification.
Status
SIGNEDCall topic
ERC-2019-STGUpdate Date
27-04-2024
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