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<p>Radiative surface heating over slopes induces buoyantly-driven anabatic winds that can transport air pollutants, heat, and moisture, affecting air quality and mountain weather via convection and evapotranspiration. This study uses multi-level turbulence observations over a steep Alpine slope in Val Ferret, Switzerland, to characterize daytime anabatic winds’ mean and turbulence structures and their evolution. It further investigates multiscale interactions between mean flow and turbulence across valley and local slope scales. The observed anabatic flow structure exhibits significant momentum and heat flux divergence associated with the jet-shaped velocity profiles, challenging the constant-flux layer assumption in Monin–Obukhov similarity theory. Sign reversals in surface-normal momentum and terrain-following heat fluxes provide a basis for estimating the anabatic jet height (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10546_2025_943_Article_IEq1.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="33" /> </InlineMediaObject> <EquationSource Format="TEX">\({h}_{jet})\)</EquationSource> </InlineEquation>, with higher <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10546_2025_943_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\({h}_{jet}\)</EquationSource> </InlineEquation> linked to stronger valley flows during the early afternoon. Budget analyses indicate that slope-parallel heat fluxes suppress turbulence kinetic energy (TKE) below the sign reversal height, while enhancing TKE above it. The Fourier cospectra for momentum fluxes exhibit multiscale transport near the estimated <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10546_2025_943_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\({h}_{jet}\)</EquationSource> </InlineEquation>, with large and small eddies demonstrating opposite signs, suggesting counter-gradient flux transport. These findings can help to improve surface-layer turbulence parameterizations and turbulent flux estimates derived from meteorological observations, e.g., using distributed sensor networks in watersheds.</p>

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The Turbulence Flow Structure of Anabatic Winds over a Steep Alpine Slope

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月15日

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  • Ting Wang,
  • Eric R. Pardyjak,
  • Marc B. Parlange,
  • Holly J. Oldroyd

摘要

Radiative surface heating over slopes induces buoyantly-driven anabatic winds that can transport air pollutants, heat, and moisture, affecting air quality and mountain weather via convection and evapotranspiration. This study uses multi-level turbulence observations over a steep Alpine slope in Val Ferret, Switzerland, to characterize daytime anabatic winds’ mean and turbulence structures and their evolution. It further investigates multiscale interactions between mean flow and turbulence across valley and local slope scales. The observed anabatic flow structure exhibits significant momentum and heat flux divergence associated with the jet-shaped velocity profiles, challenging the constant-flux layer assumption in Monin–Obukhov similarity theory. Sign reversals in surface-normal momentum and terrain-following heat fluxes provide a basis for estimating the anabatic jet height ( \({h}_{jet})\) , with higher \({h}_{jet}\) linked to stronger valley flows during the early afternoon. Budget analyses indicate that slope-parallel heat fluxes suppress turbulence kinetic energy (TKE) below the sign reversal height, while enhancing TKE above it. The Fourier cospectra for momentum fluxes exhibit multiscale transport near the estimated \({h}_{jet}\) , with large and small eddies demonstrating opposite signs, suggesting counter-gradient flux transport. These findings can help to improve surface-layer turbulence parameterizations and turbulent flux estimates derived from meteorological observations, e.g., using distributed sensor networks in watersheds.