High-Resolution Large-Eddy Simulations of Flow in a Steep Alpine Valley. Part I: Methodology, Verification, and Sensitivity Experiments

2006 ◽  
Vol 45 (1) ◽  
pp. 63-86 ◽  
Author(s):  
Fotini Katopodes Chow ◽  
Andreas P. Weigel ◽  
Robert L. Street ◽  
Mathias W. Rotach ◽  
Ming Xue

Abstract This paper investigates the steps necessary to achieve accurate simulations of flow over steep, mountainous terrain. Large-eddy simulations of flow in the Riviera Valley in the southern Swiss Alps are performed at horizontal resolutions as fine as 150 m using the Advanced Regional Prediction System. Comparisons are made with surface station and radiosonde measurements from the Mesoscale Alpine Programme (MAP)-Riviera project field campaign of 1999. Excellent agreement between simulations and observations is obtained, but only when high-resolution surface datasets are used and the nested grid configurations are carefully chosen. Simply increasing spatial resolution without incorporating improved surface data gives unsatisfactory results. The sensitivity of the results to initial soil moisture, land use data, grid resolution, topographic shading, and turbulence models is explored. Even with strong thermal forcing, the onset and magnitude of the upvalley winds are highly sensitive to surface processes in areas that are well outside the high-resolution domain. In particular, the soil moisture initialization on the 1-km grid is found to be crucial to the success of the finer-resolution predictions. High-resolution soil moisture and land use data on the 350-m-resolution grid also improve results. The use of topographic shading improves radiation curves during sunrise and sunset, but the effects on the overall flow are limited because of the strong lateral boundary forcing from the 1-km grid where terrain slopes are not well resolved. The influence of the turbulence closure is also limited because of strong lateral forcing and hence limited residence time of air inside the valley and because of the stable stratification, which limits turbulent stress to the lowest few hundred meters near the surface.

2006 ◽  
Vol 45 (1) ◽  
pp. 87-107 ◽  
Author(s):  
Andreas P. Weigel ◽  
Fotini K. Chow ◽  
Mathias W. Rotach ◽  
Robert L. Street ◽  
Ming Xue

Abstract This paper analyzes the three-dimensional flow structure and the heat budget in a typical medium-sized and steep Alpine valley—the Riviera Valley in southern Switzerland. Aircraft measurements from the Mesoscale Alpine Programme (MAP)-Riviera field campaign reveal a very pronounced valley-wind system, including a strong curvature-induced secondary circulation in the southern valley entrance region. Accompanying radio soundings show that the growth of a well-mixed layer is suppressed, even under convective conditions. Our analyses are based on the MAP-Riviera measurement data and the output of high-resolution large-eddy simulations using the Advanced Regional Prediction System (ARPS). Three sunny days of the measurement campaign are simulated. Using horizontal grid spacings of 350 and 150 m (with a vertical spacing as fine as 20 m), the model reproduces the observed flow features very well. The ARPS output data are then used to calculate the components of the heat budget of the valley atmosphere, first in profiles over the valley base and then as averages over almost the entire valley volume. The analysis shows that the suppressed growth of the well-mixed layer is due to the combined effect of cold-air advection in the along-valley direction and subsidence of warm air from the free atmosphere aloft. It is further influenced by the local cross-valley circulation. This had already been hypothesized on the basis of measurement data and is now confirmed through a numerical model. Averaged over the entire valley, subsidence turns out to be one of the main heating sources of the valley atmosphere and is of comparable magnitude to turbulent heat flux divergence. On the mornings of two out of the three simulation days, this subsidence is even identified as the only major heating source and thus appears to be an important driving mechanism for the onset of thermally driven upvalley winds.


2009 ◽  
Vol 48 (6) ◽  
pp. 1161-1180 ◽  
Author(s):  
Francis L. Ludwig ◽  
Fotini Katopodes Chow ◽  
Robert L. Street

Abstract This paper demonstrates the importance of high-quality subfilter-scale turbulence models in large-eddy simulations by evaluating the resolved-scale flow features that result from various closure models. The Advanced Regional Prediction System (ARPS) model was used to simulate neutral flow over a 1.2-km square, flat, rough surface with seven subfilter turbulence models [Smagorinsky, turbulent kinetic energy (TKE)-1.5, and five dynamic reconstruction combinations]. These turbulence models were previously compared with similarity theory. Here, the differences are evaluated using mean velocity statistics and the spatial structure of the flow field. Streamwise velocity averages generally differ among models by less than 0.5 m s−1, but those differences are often significant at a 95% confidence level. Flow features vary considerably among models. As measured by spatial correlation, resolved flow features grow larger and less elongated with height for a given model and resolution. The largest differences are between dynamic models that allow energy backscatter from small to large scales and the simple eddy-viscosity closures. At low altitudes, the linear extent of Smagorinsky and TKE-1.5 structures exceeds those of dynamic models, but the relationship reverses at higher altitudes. Ejection, sweep, and upward momentum flux features differ among models and from observed neutral atmospheric flows, especially for Smagorinsky and TKE-1.5 coarse-grid simulations. Near-surface isopleths separating upward fluxes from downward are shortest for the Smagorinsky and TKE-1.5 coarse-grid simulations, indicating less convoluted turbulent interfaces; at higher altitudes they are longest. Large-eddy simulation (LES) is a powerful simulation tool, but choices of grid resolution and subfilter model can affect results significantly. Physically realistic dynamic mixed models, such as those presented here, are essential when using LES to study atmospheric processes such as transport and dispersion—in particular at coarse resolutions.


2010 ◽  
Vol 11 (4) ◽  
pp. 934-949 ◽  
Author(s):  
Rebecca Mott ◽  
Michael Lehning

Abstract The inhomogeneous snow distribution found in alpine terrain is the result of wind and precipitation interacting with the snow surface. During major snowfall events, preferential deposition of snow and transport of previously deposited snow often takes place simultaneously. Both processes, however, are driven by the local wind field, which is influenced by the local topography. In this study, the meteorological model Advanced Regional Prediction System (ARPS) was used to compute mean flow fields of 50-m, 25-m-, 10-m-, and 5-m grid spacing to investigate snow deposition patterns resulting from two snowfall events on a mountain ridge in the Swiss Alps. Only the initial adaptation of the flow field to the topography is calculated with artificial boundary conditions. The flow fields then drive the snow deposition and transport module of Alpine3D, a model of mountain surface processes. The authors compare the simulations with partly new measurements of snow deposition on the Gaudergrat ridge. On the basis of these four grid resolutions, it was possible to investigate the effects of numerical resolution in the calculation of wind fields and in the calculation of the associated snow deposition. The most realistic wind field and deposition patterns were obtained with the highest resolution of 5 m. These high-resolution simulations confirm the earlier hypothesis that preferential deposition is active at the ridge scale and true redistribution—mainly via saltation—forms smaller-scale deposition patterns, such as dunes and cornices.


2021 ◽  
Author(s):  
Lucile Ricard ◽  
Athanasios Nenes ◽  
Jakob Runge ◽  
Paraskevi Georgakaki

<p>Aerosol-cloud interactions remain the largest uncertainty in assessments of anthropogenic climate forcing, while the complexity of these interactions require methods that enable abstractions and simplifications that allow their improved treatment in climate models. Marine boundary layer clouds are an important component of the climate system as their large albedo and spatial coverage strongly affect the planetary radiative balance. High resolution simulations of clouds provide an unprecedented understanding of the structure and behavior of these clouds in the marine atmosphere, but the amount of data is often too large and complex to be useful in climate simulations. Data reduction and inference methods provide a way that to reduce the complexity and dimensionality of datasets generated from high-resolution Large Eddy Simulations.</p><p>In this study we use network analysis, (the δ-Maps method) to study the complex interaction between liquid water, droplet number and vertical velocity in Large Eddy Simulations of Marine Boundary Layer clouds. δ-Maps identifies domains that are spatially contiguous and possibly overlapping and characterizes their connections and temporal interactions. The objective is to better understand microphysical properties of marine boundary layer clouds, and how they are impacted by the variability in aerosols. Here we will capture the dynamical structure of the cloud fields predicted by the MIMICA Large Eddy Simulation (LES) model. The networks inferred from the different simulation fields are compared between them (intra-comparisons) using perturbations in initial conditions and aerosol, using a set of four metrics. The networks are then evaluated for their differences, quantifying how much variability is inherent in the LES simulations versus the robust changes induced by the aerosol fields. </p>


2012 ◽  
Vol 89 (3) ◽  
pp. 407-434 ◽  
Author(s):  
Amir Keshmiri ◽  
Mark A. Cotton ◽  
Yacine Addad ◽  
Dominique Laurence

2020 ◽  
Vol 12 (11) ◽  
pp. 1701
Author(s):  
Carlos Román-Cascón ◽  
Marie Lothon ◽  
Fabienne Lohou ◽  
Nitu Ojha ◽  
Olivier Merlin ◽  
...  

The use of soil moisture (SM) measurements from satellites has grown in recent years, fostering the development of new products at high resolution. This opens the possibility of using them for certain applications that were normally carried out using in situ data. We investigated this hypothesis through two main analyses using two high-resolution satellite-based soil moisture (SBSM) products that combined microwave with thermal and optical data: (1) The Disaggregation based on Physical And Theoretical scale Change (DISPATCH) and, (2) The Soil Moisture Ocean Salinity-Barcelona Expert Center (SMOS-BEC Level 4). We used these products to analyse the SM differences among pixels with contrasting vegetation. This was done through the comparison of the SM measurements from satellites and the measurements simulated with a simple antecedent precipitation index (API) model, which did not account for the surface characteristics. Subsequently, the deviation of the SM from satellite with respect to the API model (bias) was analysed and compared for contrasting land use categories. We hypothesised that the differences in the biases of the varied categories could provide information regarding the water retention capacity associated with each type of vegetation. From the satellite measurements, we determined how the SM depended on the tree cover, i.e., the denser the tree cover, the higher the SM. However, in winter periods with light rain events, the tree canopy could dampen the moistening of the soil through interception and conducted higher SM in the open areas. This evolution of the SM differences that depended on the characteristics of each season was observed both from satellite and from in situ measurements taken beneath a tree and in grass on the savanna landscape. The agreement between both types of measurements highlighted the potential of the SBSM products to investigate the SM of each type of vegetation. We found that the results were clearer for DISPATCH, whose data was not smoothed spatially as it was in SMOS-BEC. We also tested whether the relationships between SM and evapotranspiration could be investigated using satellite data. The answer to this question was also positive but required removing the unrealistic high-frequency SM oscillations from the satellite data using a low pass filter. This improved the performance scores of the products and the agreement with the results from the in situ data. These results demonstrated the possibility of using SM data from satellites to substitute ground measurements for the study of land–atmosphere interactions, which encourages efforts to improve the quality and resolution of these measurements.


Author(s):  
Puxuan Li ◽  
Steve J. Eckels ◽  
Ning Zhang ◽  
Garrett W. Mann

Parallel processing is an effective computation in which many calculations are carried out simultaneously. In this paper, effects of shared-memory parallel processing on Large Eddy Simulations (LES) in ANSYS Fluent are presented. Fluent provides parallel processing to improve the speed of running programs. LES is one of the most popular viscosity models for turbulence used in computational fluid dynamics (CFD). Three kinds of LES with different sub-grid turbulence models were evaluated: Smagorinsky-Lilly Model (Lilly model), Wall-Adapting Local Eddy-viscosity Model (WALE model) and Wall Modeled Large Eddy Simulation (WMLES model). The running speed of the different models simulating a square duct on a single computer are compared. The relationship between wall-clock time and number of processors reveals the performances of different LES models. The part of the time that is not parallelizable such as file IO and data transfer is also considered based on Amdahl’s law.


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