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Diagnosing lee wave rotor onset using a linear model including a boundary layer

Teixeira, M. A. C. (2017) Diagnosing lee wave rotor onset using a linear model including a boundary layer. Atmosphere, 8 (1). 5. ISSN 2073-4433

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To link to this item DOI: 10.3390/atmos8010005

Abstract/Summary

A linear model is used to diagnose the onset of rotors in flow over 2D hills, for atmospheres that are neutrally stratified near the surface and stably stratified aloft, with a sharp temperature inversion in between, where trapped lee waves may propagate. This is achieved by coupling an inviscid two-layer mountain-wave model and a bulk boundary-layer model. The full model shows some ability to diagnose flow stagnation associated with rotors as a function of key input parameters, such as the Froude number and the height of the inversion, in numerical simulations and laboratory experiments carried out by previous authors. While calculations including only the effects of mean flow attenuation and velocity perturbation amplification within the surface layer represent flow stagnation fairly well in the more non-hydrostatic cases, only the full model, taking into account the feedback of the surface layer on the inviscid flow, satisfactorily predicts flow stagnation in the most hydrostatic case, although the corresponding condition is unable to discriminate between rotors and hydraulic jumps. Versions of the model not including this feedback severely underestimate the amplitude of trapped lee waves in that case, where the Fourier transform of the hill has zeros, showing that those waves are not forced directly by the orography.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:68594
Uncontrolled Keywords:flow over mountains; trapped lee waves; rotors; linear theory; boundary layer; bulk model
Additional Information:This article belongs to the Special Issue 'Atmospheric Gravity Waves'. A correction to this article was published in Atmosphere 2018, 9 (12), 491. This is available at: https://doi.org/10.3390/atmos9120491
Publisher:MDPI

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