Large-Eddy Simulation of Stably Stratified Atmospheric Boundary Layer Turbulence: A Scale-Dependent Dynamic Modeling Approach

A new tuning-free subgrid-scale model, termed `locally-averaged scale-dependent dynamic' (LASDD) model, is developed and implemented in large-eddy simulations (LESs) of stable boundary layers. The new model dynamically computes the Smagorinsky coefficient and the subgrid-scale Prandtl number based on the local dynamics of the resolved velocity and temperature fields. Overall, the agreement between the statistics of the LES-generated turbulence and some well-established empirical formulations and theoretical predictions (e.g., Nieuwstadt's local scaling hypothesis) is remarkable. The results show clear improvements over most of the traditional subgrid-scale models in the surface layer. Moreover, in contrast to previous large-eddy simulations of stable boundary layers that have strong dependence on grid resolution, the simulated statistics obtained with the LASDD model show relatively little resolution dependence for the range of grid sizes considered here. In essence, we show that the new LASDD model is a robust subgrid-scale parameterization for reliable, tuning-free simulations of stable boundary layers, even with relatively coarse resolutions

Exploring the possible role of small scale terrain drag on stable boundary layers over land

This paper addresses the possible role of unresolved terrain drag, relative to the turbulent drag on the development of the stable atmospheric boundary layer over land. Adding a first-order estimate for terrain drag to the turbulent drag appears to provide drag that is similar to the enhanced turbulent drag obtained with the so-called long-tail mixing functions. These functions are currently used in many operational models for weather and climate, although they lack a clear physical basis. Consequently, a simple and practical quasi-empirical parameterization of terrain drag divergence for use in large-scale models is proposed and is tested in a column mode. As an outcome, the cross-isobaric mass flow (a measure for cyclone filling) with the new scheme, using realistic turbulent drag, appears to be equal to what is found with the unphysical long-tail scheme. At the same time, the new scheme produces a much more realistic less-deep boundary layer than is obtained by using the long-tail mixing function

Large Eddy Simulations of gaseous flames in gas turbine combustion chambers

Recent developments in numerical schemes, turbulent combustion models and the regular increase of computing power allow Large Eddy Simulation (LES) to be applied to real industrial burners. In this paper, two types of LES in complex geometry combustors and of specific interest for aeronautical gas turbine burners are reviewed: (1) laboratory-scale combustors, without compressor or turbine, in which advanced measurements are possible and (2) combustion chambers of existing engines operated in realistic operating conditions. Laboratory-scale burners are designed to assess modeling and funda- mental flow aspects in controlled configurations. They are necessary to gauge LES strategies and identify potential limitations. In specific circumstances, they even offer near model-free or DNS-like LES computations. LES in real engines illustrate the potential of the approach in the context of industrial burners but are more difficult to validate due to the limited set of available measurements. Usual approaches for turbulence and combustion sub-grid models including chemistry modeling are first recalled. Limiting cases and range of validity of the models are specifically recalled before a discussion on the numerical breakthrough which have allowed LES to be applied to these complex cases. Specific issues linked to real gas turbine chambers are discussed: multi-perforation, complex acoustic impedances at inlet and outlet, annular chambers.. Examples are provided for mean flow predictions (velocity, temperature and species) as well as unsteady mechanisms (quenching, ignition, combustion instabil- ities). Finally, potential perspectives are proposed to further improve the use of LES for real gas turbine combustor designs

Energy and moisture exchange processes over heterogeneous land-surfaces in a weather prediction model

Land-surfaces exhibit significant variablity at very small scales - in contrast to the atmosphere, where horizontal diffusion reduces small scale fluctuations effectively. It is a challenging task for numerical weather prediction (NWP) to account for these different characteristics while calculating exchange fluxes between these two systems: Surface processes need to be considered with higher spatial resolution than atmospheric effects and high resolution initial conditions and parameters of the surface are required. This study evaluates methods to solve these surface heterogeneity problems on the basis of integrations of the non-hydrostatic weather prediction model Lokal-Modell (LM) both in a NWP configuration (grid spacing of 7 km) and in a regional climate model set up (grid spacing of 21 km). The runs are performed for the 30-day periode of the LITFASS-2003 experiment. Two heterogeneity parameterisation schemes, the mosaic and tile approach, have been implemented into LM. Both methods decompose the surface within one atmospheric grid box into several patches to resolve subgrid scale variability. The mosaic approach utilises an explicit, geographical sub-grid, whereas the tile approach subdivides the surface according to a certain criteria, e.g. land-use. In general, the tile method requires less computational time since fewer patches are used. However, the mosaic technique is more flexible since it takes multivariate heterogeneity into account. Two major model enhancements are needed to simulate the observed exchange fluxes during LITFASS-2003 successfully: land-use dependent stomatal resistance parameters and vegetation albedo, and the use of accurate soil moisture data for initialisation. The latter is obtained by multi-year assimilation runs of the soil module of LM driven exclusively by observations. This technique ensures a balanced model state and allows to capture heterogeneity effects due to soil moisture variations induced by inhomogeneous rainfall. The flux predictions of all integrations using these enhancements agree well with the observations within the range of measurement uncertainty independently from the representation of heterogeneity. The impact of improved surface fluxes on forecasts of atmospheric state variables is beneficial. Using high resolution integrations (e.g. grid spacing of 1 km) as reference, a clear ranking of parameterisation schemes can be established: The mosaic approach leads to very accurate flux predictions, followed by the tile approach, and the operational homogeneous approach. The deviations in forecasted surface fluxes of all methods decay significantly, if averages over larger scales are considered. The ranking of the methods can be explained by analysing the small scale variance of high resolution runs: The variance of surface quantities is by far larger than those of corresponding atmospheric quantities. This supports the assumption inherent to the mosaic and tile approach to refine the surface only. During LITFASS-2003, a considerable fraction of flux variability is explained by soil moisture variations which are not correlated with land-use. These subgrid scale heterogeneities can only be resolved by the mosaic approach and not by a tile scheme.Energie- und Feuchteaustausch über heterogenen Landoberflächen in einem Wettervorhersagemodell Landoberflächen zeichnen sich durch eine hohe Variabilität auf kleinen Skalen aus - im Gegensatz zur Atmosphäre, in der horizontale Diffusion kleinskalige Fluktuationen effektiv reduziert. Diese unterschiedlichen Eigenschaften bei der Berechnung der Austauschflüsse von Energie und Feuchte zwischen beiden Systemen zu berücksichtigen, ist eine schwierige Aufgabe für die numerische Wettervorhersage: Oberflächenprozesse erfordern eine höhere räumliche Auflösung als atmosphärische Effekte und entsprechend werden hochaufgelöste Anfangsbedingungen und Parameter der Oberfläche benötigt. Diese Studie erprobt Methoden zur Lösung dieser Heterogenitätsprobleme auf der Basis von Rechnungen mit dem nicht-hydrostatischen Wettervorhersagemodell Lokal-Modell (LM) sowohl in einer Konfiguration zur Wettervorhersage (Gitterweite 7 km) als auch in einer Einstellung, die einem regionalen Klimamodell entspricht (Gitterweite 21 km). Diese Simulationen werden für den 30-Tages-Zeitraum des LITFASS-2003 Experiments durchgeführt. Zwei Heterogenitätsparameterisierungen, der Mosaic- und der Tile-Ansatz, sind in das LM eingebaut worden. Beide Methoden zerlegen die Oberfläche innerhalb einer atmosphärischen Gitterbox in verschiedene Untergebiete, um kleinskalige Variabilität unterhalb der Modellmaschenweite aufzulösen. Der Mosaic-Ansatz verwendet ein explizites, geographisches Untergitter, wohingegen der Tile-Ansatz die Oberfläche nach einem bestimmten Kriterium, z.B. der Landnutzung, aufteilt. Im allgemeinen benötigt der Tile-Ansatz weniger Rechenzeit, da weniger Untergebiete verwendet werden. Der Mosaic-Ansatz ist flexibler, da auch multivariate Heterogenitäten berücksichtigt werden können. Zwei wesentliche Modifikationen des operationellen Modells sind nötig, um die während LITFASS-2003 beobachteten Austauschflüsse erfolgreich zu modellieren: landnutzungsabhängige Parameter des Stomatawiderstands und der Pflanzenalbedo, sowie genaue Bodenfeuchteanalysen. Letztere lassen sich aus mehrjährigen Assimilationsläufen mit dem Bodenmodell des LM bei ausschließlichem Antrieb mit Messdaten erstellen. Diese Technik garantiert einen balancierten Modellzustand und ermöglicht es, Heterogenitätseffekte infolge regeninduzierter Bodenfeuchtevariationen wiederzugeben. Die Flussvorhersagen aller Modellläufen, die diese Modifikationen nutzen, geben die Beobachtungen im Rahmen der Messgenauigkeit gut wieder - unabhängig von der Berücksichtung von Heterogenitäten. Diese genauer modellierten Austauschflüsse reduzieren auch Fehler in den Vorhersagen des atmosphärischen Zustands. Verwendet man hochaufgelöste Modellintegrationen (z.B. mit einer Maschenweite von 1 km) als Referenz, so ergibt sich eine klare Rangfolge für die verschiedenen Parameterisierungsmethoden: Der Mosaic-Ansatz führt zu sehr genauen Flussvorhersagen, gefolgt vom Tile-Ansatz und dem operationell verwendeten Ansatz einer homogenen Oberfläche. Die Unterschiede in den vorhergesagten bodennahen Flüssen verringern sich deutlich, wenn Mittel über größere Skalen betrachtet werden. Die Rangfolge der Methoden kann durch eine Analyse kleinskaliger Varianzen in hochaufgelösten Simulationen erklärt werden: Die Varianz von Oberflächenvariablen ist deutlich größer als die von entsprechenden atmosphärischen Größen und rechtfertigt damit die dem Mosaic- und Tile-Ansatz zugrundeliegenden Annahmen, nur die Oberfläche höher aufzulösen. Während LITFASS-2003 wird ein beachtlicher Anteil der Variabilität der bodennahen Flüsse durch Bodenfeuchtevariationen erklärt, die nicht mit der Landnutzung korreliert sind. Solche kleinskaligen Heterogenitäten können nur vom Mosaic-Ansatz aufgelöst werden, nicht aber durch ein Tile-Schema

Impacts of Land-Atmosphere Interactions on Regional Convection and Rainfall

High resolution (1-10 km) numerical weather prediction (NWP) models face major challenges trying to improve representation of moist processes. In particular, simulating the interaction between the land surface and regional convection and rainfall is a source of uncertainties and presents three main barriers: (i) NWP models generally have simple land surface schemes, (ii) land-atmosphere coupling is not properly represented in models, and (iii) many assumptions made in deriving the theory of convective parameterizations are no longer valid at “gray scales” (e.g., 1-10 km). In this dissertation, interactions between land-surface heterogeneities, land-atmosphere coupling, and moist convection and related mesoscale circulations were investigated in four major studies to improve and advance the understanding of high-resolution model simulations of regional convection and precipitation. A number of short-term (i.e., 24-48 hours) retrospective numerical experiments were conducted over a variety of land-atmosphere coupling hotspot regions across the globe

Simulation of Boundary-Layer Cumulus and Stratocumulus Clouds using a Cloud-Resolving Model With Low- and Third-Order Turbulence Closures

The effects of subgrid-scale condensation and transport become more important as the grid spacings increase from those typically used in large-eddy simulation (LES) to those typically used in cloud-resolving models (CRMs). Incorporation of these effects can be achieved by a joint probability density function approach that utilizes higher-order moments of thermodynamic and dynamic variables. This study examines how well shallow cumulus and stratocumulus clouds are simulated by two versions of a CRM that is implemented with low-order and third-order turbulence closures (LOC and TOC) when a typical CRM horizontal resolution is used and what roles the subgrid-scale and resolved-scale processes play as the horizontal grid spacing of the CRM becomes finer. Cumulus clouds were mostly produced through subgrid-scale transport processes while stratocumulus clouds were produced through both subgrid-scale and resolved-scale processes in the TOC version of the CRM when a typical CRM grid spacing is used. The LOC version of the CRM relied upon resolved-scale circulations to produce both cumulus and stratocumulus clouds, due to small subgrid-scale transports. The mean profiles of thermodynamic variables, cloud fraction and liquid water content exhibit significant differences between the two versions of the CRM, with the TOC results agreeing better with the LES than the LOC results. The characteristics, temporal evolution and mean profiles of shallow cumulus and stratocumulus clouds are weakly dependent upon the horizontal grid spacing used in the TOC CRM. However, the ratio of the subgrid-scale to resolved-scale fluxes becomes smaller as the horizontal grid spacing decreases. The subcloud-layer fluxes are mostly due to the resolved scales when a grid spacing less than or equal to 1 km is used. The overall results of the TOC simulations suggest that a 1-km grid spacing is a good choice for CRM simulation of shallow cumulus and stratocumulus

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions

There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40gm. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10gm, but not beyond. Obviously, the default grid spacing of 40gm is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale