Chaos control in high-resolution atmospheric predictions with a cloud-resolving model
DOI:
https://doi.org/10.5540/03.2025.011.01.0358Palavras-chave:
climate change, atmospheric water cycle, cloud-resolving model, high space resolution, high Reynolds number, IBM prediction method, model errorResumo
The atmospheric water cycle is dynamically unstable. The IBM prediction method is tested in high-resolution atmospheric water cycle predictions with a cloud-resolving model (CRM) with subgrid equations for viscous turbulence processes extracted from the compressible Navier-Stokes equations showing that the atmospheric water cycle has higher predictability under this method than under straightforward integrations of the CRM, both for moderate and high Reynolds numbers.
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