scholarly journals Stochastic modeling of transient surface scalar and momentum fluxes in turbulent boundary layers

2021 ◽  
Author(s):  
Marten Klein ◽  
David O. Lignell ◽  
Heiko Schmidt
Keyword(s):  
Boundary Layers ◽  
Control Parameter ◽  
Layer Structure ◽  
Numerical Models ◽  
Turbulent Boundary Layers ◽  
Transport Processes ◽  
Surface Fluxes ◽  
One Dimensional ◽  
Weather And Climate ◽  
Normal Transport

<p>Turbulence is ubiquitous in atmospheric boundary layers and manifests itself by transient transport processes on a range of scales. This range easily reaches down to less than a meter, which is smaller than the typical height of the first grid cell layer adjacent to the surface in numerical models for weather and climate prediction. In these models, the bulk-surface coupling plays an important role for the evolution of the atmosphere but it is not feasible to fully resolve it in applications. Hence, the overall quality of numerical weather and climate predictions crucially depends on the modeling of subfilter-scale transport processes near the surface. A standing challenge in this regard is the robust but efficient representation of transient and non-Fickian transport such as counter-gradient fluxes that arise from stratification and rotation effects.</p><p>We address the issues mentioned above by utilizing a stochastic one-dimensional turbulence (ODT) model. For turbulent boundary layers, ODT aims to resolve the wall-normal transport processes on all relevant scales but only along a single one-dimensional domain (column) that is aligned with the vertical. Molecular diffusion and unbalanced Coriolis forces are directly resolved, whereas effects of turbulent advection and stratification are modeled by stochastically sampled sequence of mapping (eddy) events. Each of these events instantaneously modifies the flow profiles by a permutation of fluid parcels across a selected size interval. The model is of lower order but obeys fundamental conservation principles and Richardson's 1/4 law by construction.</p><p>In this study, ODT is applied as stand-alone tool in order to investigate nondimensional control parameter dependencies of the scalar and momentum transport in turbulent channel, neutral, and stably-stratified Ekman flows up to (friction) Reynolds number <em>Re</em> = <em>O</em>(10<sup>4</sup>). We demonstrate that ODT is able to capture the state-space statistics of transient surface fluxes as well as the boundary-layer structure and nondimensional control parameter dependencies of low-order flow statistics.<br>Very good to reasonable agreement with available reference data is obtained for various observables using fixed model set-ups. We conclude that ODT is an economical turbulence model that is able to not only capture but also predict the wall-normal transport and surface fluxes in multiphysics turbulent boundary layers.</p>

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.

Turbulent boundary-layer structure in supersonic flow

1991 ◽  
Vol 336 (1641) ◽  
pp. 81-93 ◽  
Keyword(s):  
Experimental Data ◽  
Supersonic Flow ◽  
Boundary Layers ◽  
Large Scale ◽  
Layer Structure ◽  
Turbulent Boundary Layers ◽  
Recent Experimental Data ◽  
Physical Mechanisms ◽  
Compressible Boundary Layers ◽  
Reynolds Number Dependence

A summary is given of the recent experimental data on the structure of turbulent boundary layers in supersonic flow. The physical mechanisms differentiating incompressible and compressible boundary layers are discussed, and a simple model for the Mach and Reynolds number dependence of the decay of the large-scale motions is proposed.

scholarly journals Land surface spinup for episodic modeling

2014 ◽  
Vol 14 (15) ◽  
pp. 8165-8172 ◽  
Author(s):  
W. M. Angevine ◽  
E. Bazile ◽  
D. Legain ◽  
D. Pino
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Layer Structure ◽  
Numerical Models ◽  
Surface Fluxes ◽  
Boundary Layer Structure ◽  
Soil Variables

Abstract. Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases – self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.

scholarly journals Land surface spinup for episodic modeling

2014 ◽  
Vol 14 (4) ◽  
pp. 4723-4744 ◽  
Author(s):  
W. M. Angevine ◽  
E. Bazile ◽  
D. Legain ◽  
D. Pino
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Layer Structure ◽  
Numerical Models ◽  
Surface Fluxes ◽  
Boundary Layer Structure ◽  
Soil Variables

Abstract. Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases, self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.

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