Understanding Near-surface and In-cloud Turbulent Fluxes in the Coastal Stratocumulus-Topped Boundary Layers

2007 ◽  
Author(s):  
Qing Wang
Keyword(s):  
Boundary Layers ◽  
Turbulent Fluxes ◽  
Near Surface

scholarly journals 100 Years of Progress in Boundary Layer Meteorology

2019 ◽  
Vol 59 ◽  
pp. 9.1-9.85 ◽  
Author(s):  
Margaret A. LeMone ◽  
Wayne M. Angevine ◽  
Christopher S. Bretherton ◽  
Fei Chen ◽  
Jimy Dudhia ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Boundary Layers ◽  
Numerical Models ◽  
Cloud Microphysics ◽  
Lessons Learned ◽  
The Arctic ◽  
Surface Model ◽  
Near Surface ◽  
Boundary Layer Meteorology ◽  
Weather And Climate

AbstractOver the last 100 years, boundary layer meteorology grew from the subject of mostly near-surface observations to a field encompassing diverse atmospheric boundary layers (ABLs) around the world. From the start, researchers drew from an ever-expanding set of disciplines—thermodynamics, soil and plant studies, fluid dynamics and turbulence, cloud microphysics, and aerosol studies. Research expanded upward to include the entire ABL in response to the need to know how particles and trace gases dispersed, and later how to represent the ABL in numerical models of weather and climate (starting in the 1970s–80s); taking advantage of the opportunities afforded by the development of large-eddy simulations (1970s), direct numerical simulations (1990s), and a host of instruments to sample the boundary layer in situ and remotely from the surface, the air, and space. Near-surface flux-profile relationships were developed rapidly between the 1940s and 1970s, when rapid progress shifted to the fair-weather convective boundary layer (CBL), though tropical CBL studies date back to the 1940s. In the 1980s, ABL research began to include the interaction of the ABL with the surface and clouds, the first ABL parameterization schemes emerged; and land surface and ocean surface model development blossomed. Research in subsequent decades has focused on more complex ABLs, often identified by shortcomings or uncertainties in weather and climate models, including the stable boundary layer, the Arctic boundary layer, cloudy boundary layers, and ABLs over heterogeneous surfaces (including cities). The paper closes with a brief summary, some lessons learned, and a look to the future.

scholarly journals Turbulent fluxes in stably stratified boundary layers

2008 ◽  
Vol T132 ◽  
pp. 014010 ◽  
Author(s):  
Victor S L'vov ◽  
Itamar Procaccia ◽  
Oleksii Rudenko
Keyword(s):  
Boundary Layers ◽  
Turbulent Fluxes

Diffusive–Nondiffusive Flux Decompositions in Atmospheric Boundary Layers

2020 ◽  
Vol 77 (10) ◽  
pp. 3479-3494
Author(s):  
Tomas Chor ◽  
James C. McWilliams ◽  
Marcelo Chamecki
Keyword(s):  
Boundary Layers ◽  
A Priori ◽  
Eddy Diffusivity ◽  
Turbulent Fluxes ◽  
Atmospheric Boundary Layers ◽  
Convective Boundary ◽  
Atmospheric Sciences ◽  
Diffusive Term ◽  
Novel Method ◽  
Neutral Conditions

AbstractEddy diffusivity models are a common method to parameterize turbulent fluxes in the atmospheric sciences community. However, their inability to handle convective boundary layers leads to the addition of a nondiffusive flux component (usually called nonlocal) alongside the original diffusive term (usually called local). Both components are often modeled for convective conditions based on the shape of the eddy diffusivity profile for neutral conditions. This assumption of shape is traditionally employed due to the difficulty of estimating both components based on numerically simulated turbulent fluxes without any a priori assumptions. In this manuscript we propose a novel method to avoid this issue and estimate both components from numerical simulations without having to assume any a priori shape or scaling for either. Our approach is based on optimizing results from a modeling perspective and taking as much advantage as possible from the diffusive term, thus maximizing the eddy diffusivity. We use our method to diagnostically investigate four different large-eddy simulations spanning different stability regimes, which reveal that nondiffusive fluxes are important even when trying to minimize them. Furthermore, the calculated profiles for both diffusive and nondiffusive fluxes suggest that their shapes change with stability, which is an effect that is not included in most models currently in use. Finally, we use our results to discuss modeling approaches and identify opportunities for improving current models.

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