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Pressure-gradient forcing methods for large-eddy simulations of flows in the lower atmospheric boundary layer

    • INRAE
    • Los Alamos National Laboratory

    Research output: Contribution to journalArticlepeer-review

    8 Scopus citations

    Abstract

    Turbulent flows over forest canopies have been successfully modeled using Large-Eddy Simulations (LES). Simulated winds result from the balance between a simplified pressure gradient forcing (e.g., a constant pressure-gradient or a canonical Ekman balance) and the dissipation of momentum, due to vegetation drag. Little attention has been paid to the impacts of these forcing methods on flow features, despite practical challenges and unrealistic features, such as establishing stationary velocity or streak locking. This study presents a technique for capturing the effects of a pressure-gradient force (PGF), associated with atmospheric patterns much larger than the computational domain for idealized simulations of near-surface phenomena. Four variants of this new PGF are compared to existing forcings, for turbulence statistics, spectra, and temporal averages of flow fields. Results demonstrate that most features of the turbulent flow are captured. The variants can either enable modelers to prescribe a wind speed and direction at a reference height close to the ground as required in wildfire simulations, and/or mitigate streaks locking by reproducing the stability of the Ekman balance. Conditions of use, benefits, and drawbacks are discussed. PGF approaches, therefore, provide a viable solution for precursor inflows, including for the specific domains used in fire simulations.

    Original languageEnglish
    Article number1343
    JournalAtmosphere
    Volume11
    Issue number12
    DOIs
    StatePublished - Dec 2020

    Keywords

    • Canopy flow
    • Coriolis force
    • Ekman balance
    • Large-eddy simulation
    • Large-scale pressure gradient
    • Persistent streaks
    • Precursor wind flow
    • Streaks locking
    • Wildfire
    • Wind energy

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