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Offshore solar is seen as a promising technology for renewable energy generation. It can be particularly valuable when co-located within offshore wind farms, as these forms of energy generation are complementary. However, the environmental impact of offshore solar is not fully understood yet, and obtaining a better understanding of the possible impact is essential before this technology is applied at a large scale. An important aspect which is still unclear is how offshore solar affects the local hydrodynamics in the marine environment. This article describes the hydrodynamic wake generated by an offshore solar array, arising from the interaction between the array and a tidal current. A computational fluid dynamic (CFD) modeling approach was used, which applies numerical large eddy simulations (LES) in OpenFOAM. The simulations are verified using the numerical model TUDFLOW3D. The study quantifies the wake dimensions and puts them in perspective with the array size, orientation, and tidal current magnitude. The investigation reveals that wake width depends on array size and array orientation. When the array is aligned with the current, wake width is relatively confined and does not depend on the array size. When the array is rotated, the wake width experiences exponential growth, becoming approximately 30% wider than the array width. Wake length is influenced by factors such as horizontal array dimensions and current magnitude. The gaps in between the floaters decrease this dependency. Similarly, the wake depth showed similar dependencies, except for the current magnitude, and only affected the upper meters of the water column. Beneath the array, flow shedding effects occur, affecting a larger part of the water column than the wake. Flow shedding depends on floater size, gaps, and orientation. [ABSTRACT FROM AUTHOR]

The prediction of flame transfer functions, particularly in practically relevant systems, remains challenging and computationally demanding. Numerical approaches are a valuable addition to experimental acoustic characterizations of industrial configurations. Conventionally, fully compressible numerical simulations are used that naturally include acoustic fluctuations in their computations, but can be computationally expensive depending on the configuration. Therefore, a convenient approach to use tailored numerics for the underlying physics is considered in this work. In this work, this is realized by applying a runtime-coupled method of computational fluid dynamics and computational aeroacoustics to a single-sector aero-engine combustor. This hybrid computational fluid dynamics and computational aeroacoustics method captures fluid flow behavior and combustion dynamics in a low-Mach computational fluid dynamics domain while allowing for acoustic perturbations in the computational aeroacoustics. Runtime exchange of hydrodynamic and acoustic quantities between the two solvers allows for a bidirectional coupling and, by extension, a complete description of the combustion system. In this work, the hybrid computational fluid dynamics and computational aeroacoustics is applied in a high-fidelity large eddy simulation configuration. The flame transfer function is evaluated for both compressible and hybrid simulations. The results for both numerical approaches are validated with each other and compared to the experimentally obtained flame transfer function. Finally, the computational effort for the numerical approaches is considered. This article presents the first application of a high-fidelity computational fluid dynamics framework using large eddy simulation with bidirectional coupling with the acoustic solver to an industry-relevant configuration. The aim is to provide a roadmap towards investigating thermoacoustic instabilities in a real gas turbine engine at reduced computational costs. [ABSTRACT FROM AUTHOR]

This study investigates the impact of initial conditions/boundary conditions (ICs/BCs) and horizontal resolutions on forecast for average weather conditions, focusing on low-level weather variables such as 2-m temperature (T2m), 2-m water vapor mixing ratio (Q2m), and 10-m wind speed (WS10). A Weather Research and Forecasting (WRF) Model is used for regional mesoscale model simulations and large-eddy simulations (LESs). The 6-h-interval forecast fields generated by the Global Forecast System of the National Centers for Environmental Prediction and the Korean Integrated Model of the Korea Meteorological Administration are utilized as ICs/BCs for the regional models. Numerical experiments are performed for 24 h starting at 0000 UTC on each day in April 2021 when the average monthly wind speed was strongest during 10 years (2011–20). A comparison of model simulations with observations obtained around the Yeongjong Island, where Incheon International Airport is situated, shows that the regional models capture the time series of T2m, Q2m, and WS10 more effectively than the global model forecasts. Moreover, the LES experiments with a 100-m horizontal grid spacing simulate higher Q2m and lower WS10 during the daytime compared to the 1-km WRF. This results in a deterioration of their time-series correlation with the observations. Meanwhile, the 100-m LES forecasts time series of T2m over ocean stations and Q2m over land stations, as well as probability density functions of low-level weather variables, more accurately than that of the 1-km WRF. Our study also emphasizes the need for caution when comparing high-resolution model results with observation values at specific stations due to the high spatial variability in low-level meteorological fields. [ABSTRACT FROM AUTHOR]

This study investigates the parameterization of the geostrophic drag law (GDL) for conventionally neutral atmospheric boundary layers (CNBLs). Utilizing large eddy simulations, we confirm that in CNBLs capped by a potential temperature inversion, the boundary-layer height scales as u ∗ / Nf , where u ∗ represents the friction velocity, N the free-atmosphere Brunt–Väisälä frequency, and f the Coriolis parameter. Additionally, we confirm that the wind gradients normalized by the Brunt–Väisälä frequency have universal profiles above the surface layer. Leveraging these physical insights, we derived analytical expressions for the GDL coefficients A and B, correcting the earlier form of Zilitinkevich and Esau (Q J R Meteorol Soc 131:1863–1892, 2005). These expressions for A and B have been validated numerically, ensuring their accuracy in representing the geostrophic drag coefficient u ∗ / G (G is the geostrophic wind speed) and the cross-isobaric angle. This work extends the range for which the GDL has been validated up to u ∗ / G = [ 0.019 , 0.047 ] . This further supports the application of GDL to CNBLs over a broader range of u ∗ / G , which is useful for meteorological applications such as wind energy. [ABSTRACT FROM AUTHOR]

Shallow convective clouds play a crucial role in Earth's energy budget, as they modulate the radiative transfer in the atmosphere and participate in the vertical transport of aerosols, energy, and humidity. The parameterizations representing these complex, vital players in weather and climate models are mostly based on a description of steady‐state plumes and are a source of major uncertainty. Recently, several studies have shown that buoyant thermals are inherent in atmospheric convection and contain a toroidal (ring) vortex. This work studies those vortices in growing shallow cumulus (Cu) clouds using high‐resolution (10 m) Large Eddy Simulations that resolve these vortices in much detail. Recent analysis of such data showed that small‐scale turbulent diffusion is unable to explain the large diluted portion of the cloud. Here we advocate for the important role of the Cu toroidal vortex (TV) in cloud dilution and present the complex dynamics and structure of a Cu TV. Nevertheless, since the vortex dominates the cloud's dilution, simplicity emerges when considering the cloud's lateral mass flux profile. The cloud mixing is quantified using direct flux calculations and Eulerian tracers. In addition, Lagrangian tracers are used to identify the origin of the entrained air and its thermodynamic properties. It shows that most of the air entrained by the vortex is not recycled by the vortex, yet is significantly more humid than the environment. We suggest that the development of new models describing thermals, together with their toroidal vortices, might improve cloud parameterizations in weather and climate models. Plain Language Summary: Shallow convective clouds play a crucial role in climate as they transfer heat in the vertical dimension and affect radiation transfer in the atmosphere. These clouds are much smaller than climate models' resolution, and so they are represented by simplified equations in weather and climate models (parameterizations). This simple representation of such important processes is one of the largest sources of uncertainty in climate models. In particular, the process of clouds mixing with their dry surroundings is known to have a large contribution to the uncertainty reflected by clouds in climate prediction. In this work, we use high‐resolution simulations of cumulus clouds to investigate the toroidal (ring) vortex that is located at the top of a rising thermal (a known property of cumulus dynamics). We show that cloud‐scale vortices dominate cloud dilution and are at least as important as stochastic turbulent motions which are often considered in mixing parameterizations. These ideas can serve for future parameterizations of shallow cumulus clouds in coarse‐resolution models. Key Points: Coherent and turbulent toroidal (ring) vortices are presented in 10 m resolution LES of shallow cumulus cloudsThe toroidal vortex dominates the cloud's dilution, as shown by the cloud's lateral mass flux profile and Eulerian tracers analysisLagrangian tracers reveal that most entrained air is environmental (not recycled by the vortex) with high relative humidity [ABSTRACT FROM AUTHOR]

The impact of clouds on the mixed layer (ML) is critical for understanding the evolution of boundary layer humidity and temperature over the course of a day. We found that accounting for moistening of the cloud layer (CL) by humidity originating in the ML dramatically alters the interaction between the ML and the CL in a one‐dimensional cloud‐topped boundary layer model: Chemistry Land‐surface Atmosphere Soil Slab (CLASS) (Vilà‐Guerau de Arellano et al., 2015, https://doi.org/10.1017/CBO9781316117422). We demonstrate that enabling CLASS to moisten the lower CL improves the prediction of humidity (and the flux of humidity) both above and below the ML top (h). To account for this moistening, we propose a length scale, L, above h, over which mixing of mass fluxes into the environment occurs. The mass fluxes are assumed to decrease linearly from h to a height L meters above h, analogous to a convective plume detraining into the environment at a height‐independent rate. Accounting for this process is accomplished by modifying the differential equations representing the growth of the jumps (sharp changes in humidity and temperature) at h. From analysis of a large number of diurnal Large Eddy simulations (covering approximately 11,000 different early morning initial conditions), we provide a regression model for parameterizing L from early morning weather variables. With the regression‐based estimate of L, the modified model (CLASS‐L) accounts for moistening the lower CL, and as a result, yields improved humidity dynamics, humidity flux profiles, and cloud growth under a broad range of conditions. Plain Language Summary: This study improved the representation of clouds above the mixed layer (ML) top in a simplified cloud‐topped atmospheric boundary layer model, Chemistry Land‐surface Atmosphere Soil Slab (CLASS) (Vilà‐Guerau de Arellano et al., 2015, https://doi.org/10.1017/CBO9781316117422). The CLASS model does not moisten the lower cloud layer (CL) when moisture originating from the ML reaches the CL. To address this, we propose a mixing length scale, L, above the ML top over which moisture originating from the ML is mixed into the environment, and name this model CLASS‐L. A power‐law regression is used to estimate L with regression coefficients based on a large set of daytime diurnal simulations (covering approximately 11,000 different initial conditions) using CLASS‐L and state‐of‐the‐art, three‐dimensional Large Eddy Simulation. With this simple enhancement to CLASS, CLASS‐L dramatically improved humidity dynamics, cloud growth, and humidity flux profiles both above and within the ML under a very broad range of initial conditions. Key Points: We enhance land‐atmosphere‐cloud interactions in a simplified model (Vilà‐Guerau de Arellano et al., 2015, https://doi.org/10.1017/CBO9781316117422)We propose an empirically determined length scale above the mixed layer over which mixing of humidity mass flux with the environment occursThe modifications (Chemistry Land‐surface Atmosphere Soil Slab‐L) dramatically alter the state and flux profiles in cloudy conditions, in agreement with Large Eddy Simulations [ABSTRACT FROM AUTHOR]

The present study introduces "WindAware", a wind and turbulence prediction system that provides nowcasts of wind and turbulence parameters every 5 min up to 6 h over a predetermined airway over Chicago, Illinois, USA, based on 100 m high-resolution simulations (HRSs). This system is a long short-term memory-based recurrent neural network (LSTM-RNN) that uses existing ground-based wind data to provide nowcasts (forecasts up to 6 h every 5 min) of wind speed, wind direction, wind gust, and eddy dissipation rate to support the Uncrewed Aircraft Systems (UASs) safe integration into the National Airspace System (NAS). These HRSs are validated using both ground-based measurements over airports and upper-air radiosonde observations and their skill is illustrated during lake-breeze events. A reasonable agreement is found between measured and simulated winds especially when the boundary layer is convective, but the timing and inland penetration of lake-breeze events are overall slightly misrepresented. The WindAware model is compared with the classic multilayer perceptron (MLP) and the eXtreme Gradient Boosting (XGBoost) models. It is demonstrated by comparison to high-resolution simulations that WindAware provides more accurate predictions than the MLP over the 6 h lead times and has almost similar performance as the XGBoost model although the XGBoost's training is the fastest using its parallelized implementation. WindAware also has higher prediction errors when validated against lake-breeze events data due to their under-representation in the training dataset. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOx) formation in a non-premixed industrial gas burner is analyzed with Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics, using the Flamelet Generated Manifold (FGM) approach for chemistry and the Reynolds stress model for turbulence closure. Analysis and validation of the numerical methodology use both the RANS and the Large Eddy Simulation methods to study the Sandia flame D experiment. Four regimes of the gas burner, differing by thermal power, are studied experimentally and numerically, comparing measured and computed flue gas temperature and emissions. The flow features leading to NOx formation are analyzed. At low power, most NOx formation occurs in the flame core, where temperatures are highest. At high power, a significant amount of NOx forms where a secondary stream of oxidizer meets the high-temperature burnt gas stream. The NOx formation rate is modeled either by summing the contributions of the main paths relevant to the studied problem or via two variants of the FGM scalar transport approach. One of these variants features a correction to the transported scalar approach that enables accounting for the effects of non-adiabatic phenomena, e.g. heat radiation, on NOx formation without increasing the look-up table dimensionality and the required memory usage. The correction is shown to improve emission predictions over the baseline model, although quantitative differences between predicted and measured emission levels remain significant. The approach computing the NOx formation rate as by summing contributions yields the best agreement with measurements when the thermal path predominates, and the formation of nitrogen dioxide is negligible.

Offshore solar is seen as a promising technology for renewable energy generation. It can be particularly valuable when co-located within offshore wind farms, as these forms of energy generation are complementary. However, the environmental impact of offshore solar is not fully understood yet, and obtaining a better understanding of the possible impact is essential before this technology is applied at a large scale. An important aspect which is still unclear is how offshore solar affects the local hydrodynamics in the marine environment. This article describes the hydrodynamic wake generated by an offshore solar array, arising from the interaction between the array and a tidal current. A computational fluid dynamic (CFD) modeling approach was used, which applies numerical large eddy simulations (LES) in OpenFOAM. The simulations are verified using the numerical model TUDFLOW3D. The study quantifies the wake dimensions and puts them in perspective with the array size, orientation, and tidal current magnitude. The investigation reveals that wake width depends on array size and array orientation. When the array is aligned with the current, wake width is relatively confined and does not depend on the array size. When the array is rotated, the wake width experiences exponential growth, becoming approximately 30% wider than the array width. Wake length is influenced by factors such as horizontal array dimensions and current magnitude. The gaps in between the floaters decrease this dependency. Similarly, the wake depth showed similar dependencies, except for the current magnitude, and only affected the upper meters of the water column. Beneath the array, flow shedding effects occur, affecting a larger part of the water column than the wake. Flow shedding depends on floater size, gaps, and orientation.

Abstract: Large-eddy simulations of flow over a “horizontally” uniform model forest are used to investigate the effects of gentle topography on the turbulent kinetic energy (TKE) budget within the canopy roughness sublayer. Despite significant differences between simulations using idealized sinusoidal topography and real topography of the Amazon forest, results indicate that the effects of topography are located predominantly in the upper canopy and above, and are mostly caused by mean advection of TKE. The “horizontally” averaged TKE budget from idealized and real gentle topographies are almost identical to that for flat terrain, including a clear inertial layer above the roughness sublayer in which shear production is balanced by local dissipation. At topography crests, where observational towers are usually located, mean vertical advection of TKE can be as important as horizontal advection. We propose the use on an approximate TKE balance equation to estimate mean advection from single tower measurements, and introduce a new advection index that can be used as a proxy to quantify the importance of the topography on the TKE budget.

Recent studies have highlighted the importance of accurate meteorological conditions for urban transport and dispersion calculations. In this work, we present a novel scheme to compute the meteorological input in the Quick Urban & Industrial Complex (QUIC) diagnostic urban wind solver to improve the characterization of upstream wind veer and shear in the Atmospheric Boundary Layer (ABL). The new formulation is based on a coupled set of Ordinary Differential Equations (ODEs) derived from the Reynolds Averaged Navier–Stokes (RANS) equations, and is fast to compute. Building upon recent progress in modeling the idealized ABL, we include effects from surface roughness, turbulent stress, Coriolis force, buoyancy and baroclinicity. We verify the performance of the new scheme with canonical Large Eddy Simulation (LES) tests with the GPU-accelerated FastEddy solver in neutral, stable, unstable and baroclinic conditions with different surface roughness. Furthermore, we evaluate QUIC calculations with and without the new inflow scheme with real data from the Urban Threat Dispersion (UTD) field experiment, which includes Lidar-based wind measurements as well as concentration observations from multiple outdoor releases of a non-reactive tracer in downtown New York City. Compared to previous inflow capabilities that were limited to a constant wind direction with height, we show that the new scheme can model wind veer in the ABL and enhance the prediction of the surface cross-isobaric angle, improving evaluation statistics of simulated concentrations paired in time and space with UTD measurements. [ABSTRACT FROM AUTHOR]

In this study, the moist buffering halo region of shallow maritime cumulus clouds is systematically investigated using large eddy simulations with various grid resolutions and numerical choices. Autocorrelation analyses of cloud liquid water and relative humidity suggest a converged size of 200–300 m for moist patches outside clouds when the model resolution is below 50 m, but may overestimate this size due to noncloudy moist regions. Based on a composite analysis, the structure of the moist halo immediately outside individual clouds is examined. It is found that, regardless of model resolution, the distribution of relative humidity in the halo region does not depend on cloud size, but on the real distance away from the cloud boundary, indicating some size‐independent length scales are responsible for the halo formation. The relative humidity decays with distance more quickly with finer horizontal resolution, which is possibly related to the model resolution dependence of the cloud spectrum. The halo size near the cloud base is larger than that within the cloud layer and this feature is robust across all simulations. Further analyses of backward and forward Lagrangian trajectories originating from the moist halo region reveal the possible role for subcloud coherent structures in cloud‐base halo formation. Possible mechanisms explaining cloud halo sizes and associated length scales are discussed. [ABSTRACT FROM AUTHOR]

Cold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes. Plain Language Summary: Cold pools are cool gusty winds beneath thunderstorms that are formed by cooling from rainfall. They have many important impacts in the atmosphere and on society but are difficult to properly simulate in numerical weather models. The variability in cold pool temperature is an understudied feature of cold pools but which is important to represent in numerical models. In this study, we examine cold pool temperature variability from a dense network of surface weather station observations collected during a field campaign, and we compare those observations to numerical simulations of cold pools in a range of environments. We find that cold pools enhance temperature variability for distances greater than ∼5 km but suppress variability on smaller distances, and that the magnitude of cold pool temperature variability is strongly dependent on the environment and cold pool lifetime. We also show that numerical models, even at very high resolutions, are not able to properly simulate the magnitude of cold pool temperature variability. We highlight areas for improvement in numerical models that may help to improve simulations of cold pool variability, including land‐atmosphere interactions, turbulence, and conversion processes between water vapor and condensed water in storms. Key Points: Cold pool impacts on sub‐mesoscale temperature variability are quantified using variograms derived from observations and simulationsCold pools enhance temperature variability on scales between 5 and 15 km, but the magnitude varies strongly with lifetime and environmentHigh‐resolution case‐study and idealized simulations underestimate the magnitude of cold pool variability, irrespective of resolution [ABSTRACT FROM AUTHOR]

An idealized large-eddy simulation of a tropical marine cloud population was performed. At any time, it contained hundreds of clouds, and updraft width in shallow convection emerging from a subcloud layer appeared to be an important indicator of whether specific convective elements deepened. In an environment with 80%–90% relative humidity below the 0°C level, updrafts that penetrated the 0°C level were larger at and above cloud base, which occurred at the lifting condensation level near 600 m. Parcels rising in these updrafts appeared to emerge from boundary layer eddies that averaged ∼200 m wider than those in clouds that only reached 1.5–3 km height. The deeply ascending parcels (growers) possessed statistically similar values of effective buoyancy below the level of free convection (LFC) as parcels that began to ascend in a cloud but stopped before reaching 3000 m (nongrowers). The growers also experienced less dilution above the LFC. Nongrowers were characterized by negative effective buoyancy and rapid deceleration above the LFC, while growers continued to accelerate well above the LFC. Growers occurred in areas with a greater magnitude of background convergence (or weaker divergence) in the subcloud layer, especially between 300 m and cloud base, but whether the convergence actually led to eddy widening is unclear. Significance Statement: Cumulonimbus clouds are responsible for many extreme weather phenomena and are important contributors to Earth's energy balance. However, the processes leading to the growth of individual clouds are not completely understood nor well-represented in weather prediction models. We find that the clouds containing updrafts that start out wider at early stages of their life cycles grow taller, possibly because they are protected more from drier air outside the cloud than narrow clouds. In addition, this work shows how the initial width of clouds might be related to convergence in the lowest part of the atmosphere, at heights where clouds initially develop. However, meteorologists must be careful not to overinterpret these results because numerical simulations inherently include assumptions that may not reflect reality. This reinforces the need to also observe processes occurring at the scales of individual clouds. [ABSTRACT FROM AUTHOR]

Although mixing in stirred tanks is common in the chemical and process industry, it is complex and not fully understood. In recent years, computational fluid dynamics (CFD) simulations with large eddy simulation turbulence models have become an important modeling tool. In this study, its current state for applicability to stirred tanks was evaluated. First, the power characteristics of different impellers were simulated and compared with experimental data. Second, Rushton and pitched blade turbines were validated in terms of the local velocity components, dissipation rates, and the trailing vortex. Finally, mixing times for different viscosity ratios were obtained from the CFD results and compared with a literature study. Hydrodynamics can be well predicted. However, mixing times for viscosity ratios larger than 1:100 are error‐prone. [ABSTRACT FROM AUTHOR]

High Reynolds number turbulent reacting flows poses a modeling challenge due to the multi-regime, mixed-mode nature of the combustion processes. This study presents a novel unified index that includes the description of both premixed and nonpremixed combustion regimes and the occurrences of local extinction and re-ignition. This classifier is applied to large eddy simulations of the Darmstadt multi-regime burner for the nominal cases 18b and 26b. Lagrangian particles are transported along with the flow in order to monitor the evolution of the local flow-chemistry interaction. The simulations are validated against experimental data, and the Lagrangian properties are compared against the traditional premixed model in progress variable space and a generalized multi-modal manifold model in mixture fraction and generalized progress variable space. The comparison reveals that minor radical species are sensitive to the generalized progress variable dissipation rates, and the multi-modal manifold model is more suitable to reproduce the multi-regime flame structure. Using the multi-modal framework, the regime index is simply defined by the slope of the Lagrangian particle trajectory in the phase space and is able to detect the evolution of the combustion regimes and the occurrence of extinction events. Consistent with the previous experimental findings, the statistics of the regimes reveals that the leaner case 18b is more susceptible to extinction and re-ignition and the regime is predominantly premixed, while the richer 26b case is more pronounced in the nonpremixed regime. [ABSTRACT FROM AUTHOR]

Observations of neutron star mergers have the potential to unveil detailed physics of matter and gravity in regimes inaccessible by other experiments. Quantitative comparisons to theory and parameter estimation require nonlinear numerical simulations. However, the detailed physics of energy and momentum transfer between different scales, and the formation and interaction of small scale structures, which can be probed by detectors, are not captured by current simulations. This is where turbulence enters neutron star modelling. This review will outline the theory and current status of turbulence modelling for relativistic neutron star merger simulations. [ABSTRACT FROM AUTHOR]

Observations in the Pacific Equatorial Undercurrents (EUC) show that the nighttime deep-cycle turbulence (DCT) in the marginal-instability (MI) layer of the EUC exhibits seasonal variability that can modulate heat transport and sea surface temperature. Large-eddy simulations (LES), spanning a wide range of control parameters, are performed to identify the key processes that influence the turbulent heat flux at multiple time scales ranging from turbulent (minutes to hours) to daily to seasonal. The control parameters include wind stress, convective surface heat flux, shear magnitude, and thickness of the MI layer. In the LES, DCT occurs in discrete bursts during the night, exhibits high temporal variability within a burst, and modulates the mixed layer depth. At the daily time scale, turbulent heat flux generally increases with increasing wind stress, MI-layer shear, or nighttime convection. Convection is found to be important to mixing under weak wind, weak shear conditions. A parameterization for the daily averaged turbulent heat flux is developed from the LES suite to infer the variability of heat flux at the seasonal time scale. The LES-based parameterized heat flux, which takes into account the effects of all control parameters, exhibits a seasonal variability that is similar to the observed heat flux from the χ-pods. [ABSTRACT FROM AUTHOR]

This study investigates momentum transport in shallow cumulus clouds as simulated with the Dutch Atmospheric Large Eddy Simulation (DALES) for a 150 × 150 km2 domain east of Barbados during 9 days of EUREC4A. DALES is initialized and forced with the mesoscale weather model HARMONIE–AROME and subjectively reproduces observed cloud patterns. This study examines the evolution of momentum transport, which scales contribute to it, and how they modulate the trade winds. Daily-mean momentum flux profiles show downgradient zonal momentum transport in the subcloud layer, which turns countergradient in the cloud layer. The meridional momentum transport is nontrivial, with mostly downgradient transport throughout the trade wind layer except near the top of the surface layer and near cloud tops. Substantial spatial and temporal heterogeneity in momentum flux is observed with much stronger tendencies imposed in areas of organized convection. The study finds that while scales < 2 km dominate momentum flux at 200 m in unorganized fields, submesoscales O (2–2 0) km carry up to 50% of the zonal momentum flux in the cloud layer in organized fields. For the meridional momentum flux, this fraction is even larger near the surface and in the subcloud layer. The scale dependence of the momentum flux is not explained by changes in convective or boundary layer depth. Instead, the results suggest the importance of spatial heterogeneity, increasing horizontal length scales, and countergradient transport in the presence of organized convection. [ABSTRACT FROM AUTHOR]

The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot. Significance Statement: The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence. [ABSTRACT FROM AUTHOR]

Abstract The impact of clouds on the mixed layer (ML) is critical for understanding the evolution of boundary layer humidity and temperature over the course of a day. We found that accounting for moistening of the cloud layer (CL) by humidity originating in the ML dramatically alters the interaction between the ML and the CL in a one‐dimensional cloud‐topped boundary layer model: Chemistry Land‐surface Atmosphere Soil Slab (CLASS) (Vilà‐Guerau de Arellano et al., 2015, https://doi.org/10.1017/CBO9781316117422). We demonstrate that enabling CLASS to moisten the lower CL improves the prediction of humidity (and the flux of humidity) both above and below the ML top (h). To account for this moistening, we propose a length scale, L, above h, over which mixing of mass fluxes into the environment occurs. The mass fluxes are assumed to decrease linearly from h to a height L meters above h, analogous to a convective plume detraining into the environment at a height‐independent rate. Accounting for this process is accomplished by modifying the differential equations representing the growth of the jumps (sharp changes in humidity and temperature) at h. From analysis of a large number of diurnal Large Eddy simulations (covering approximately 11,000 different early morning initial conditions), we provide a regression model for parameterizing L from early morning weather variables. With the regression‐based estimate of L, the modified model (CLASS‐L) accounts for moistening the lower CL, and as a result, yields improved humidity dynamics, humidity flux profiles, and cloud growth under a broad range of conditions.

How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the "true" surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue. Plain Language Summary: Large swirling motions, called large turbulent eddies, efficiently transport water vapor, carbon dioxide, and heat up and down throughout the convective boundary layer (CBL). To what extent scalar fluxes in the atmospheric surface layer (ASL) are modulated by large turbulent eddies from the top of the CBL (i.e., top‐down eddies) remains a recalcitrant problem in many fields spanning atmospheric sciences, hydrology, ecology, and climate change. Here, high‐resolution computational simulations of the CBL show that scalar fluxes in the ASL linearly change with height across soil wetness conditions largely due to changes in the interactions of top‐down processes and bottom‐up surface exchange. Such linear height‐dependence of the fluxes indicates that reported fluxes from direct turbulent measurements in the ASL are not identical to their sought surface values. As a result, the non‐closure of the surface energy balance occurs across all soil moisture conditions but improves as soil becomes dry. CO2 measured fluxes are underestimated over wet soils and overestimated over dry soils, which has its implication when interpreting CO2 exchanges from global flux measuring networks utilizing turbulence theories. Height dependence of fluxes, which confirms that the constant flux layer assumption is not routinely satisfied, is a fundamental reason for the non‐closure. Key Points: Asymmetric flux transport by bottom‐up and top‐down processes leads to varying flux divergence/convergence (FDC) in the surface layerLatent heat and CO2 fluxes are underestimated when soil is wet and overestimated when dry, but sensible heat flux is always underestimatedNon‐closure of the surface energy balance is regulated by varying FDC and improves for dry soils due to overestimated latent heat flux [ABSTRACT FROM AUTHOR]

This study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (Nd). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that Nd is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low Nd characterizes the open cellular structure with a high in‐cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open‐cell clouds produce larger and deeper cold pools compared to closed‐cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation. Plain Language Summary: Low altitude clouds cover a wide area of the Earth's atmosphere and play an important climatic role by reflecting sunlight back to space, thereby having been the topic of decades of study via observation and numerical simulation. This study uses high‐resolution weather simulations to understand the influence of the winds and tiny particles on subtropical low clouds. We find that the tiny particles largely affect the cellular cloud organization (e.g., broken and unbroken clouds). When the wind near the surface is much weaker than wind above the surface, the cloud amount and thickness are decreased via mixing of the dry air at the cloud top. In addition, the different cloud organizations produced different cold pockets of dense air near the surface. The cold air resulting from broken clouds helps to initiate a new cloud downstream, and convection upstream of the unbroken cloud is enhanced by the cold air outflow. Key Points: Cloud droplet number concentration dominates vertical shear in determining the cellular cloud organization of idealized marine stratocumulusA stronger wind shear leads to a reduced cloud fraction associated with cloud thinning compared to cases with weaker shearIntermediate Nd simulations with negligible surface precipitation produce cold pools with comparable intensity as a low Nd configuration [ABSTRACT FROM AUTHOR]

This study focuses on the application of two standard inflow turbulence generation methods for growing convective boundary layer (CBL) simulations: the recycle-rescale (R-R) and the digital filter-based (DF) methods, which are used in computational fluid dynamics. The primary objective of this study is to expand the applicability of the R-R method to simulations of thermally driven CBLs. This method is called the extended R-R method. However, in previous studies, the DF method has been extended to generate potential temperature perturbations. This study investigated whether the extended DF method can be applied to simulations of growing thermally driven CBLs. In this study, idealized simulations of growing thermally driven CBLs using the extended R-R and DF methods were performed. The results showed that both extended methods could capture the characteristics of thermally driven CBLs. The extended R-R method reproduced turbulence in thermally driven CBLs better than the extended DF method in the spectrum and histogram of vertical wind speed. However, the height of the thermally driven CBL was underestimated in about 100 m compared with the extended DF method. Sensitivity experiments were conducted on the parameters used in the extended DF and R-R methods. The results showed that underestimation of the length scale in the extended DF method causes a shortage of large-scale turbulence components. The other point suggested by the results of the sensitivity experiments is that the length of the driver region in the extended R-R method should be sufficient to reproduce the spanwise movement of the roll vortices. SIGNIFICANCE STATEMENT: Inflow turbulence generation methods for large-eddy simulation (LES) models are crucial for the better downscaling of meteorological mesoscale models (RANS models) to microscale models (LES models). Various CFD methods have been developed, but few have been applied to simulations of thermally driven convective boundary layers (CBLs). To address this problem, we focused on a method that recycles turbulence [the recycle-rescale (R-R) method] and another method that synthetically generates turbulence [the digital filter-based (DF) method]. This study extends the R-R method to manage turbulence in thermally driven CBLs. In addition, this study investigated the applicability of the DF method to thermally driven CBL simulations. Both extended methods are effective for downscaling experiments and capture the characteristics of thermally driven CBLs. [ABSTRACT FROM AUTHOR]

Marine cold-air outbreaks (CAOs) occur in the postfrontal sector of midlatitude storms, usually accompanied by dry intrusions (DIs) shaping the free-tropospheric (FT) air aloft. Substantial rain initiates overcast to broken regime transitions in marine boundary layer (MBL) cloud decks that form where cold air first meets relatively high sea surface temperatures. An exemplary CAO in the northwest Atlantic shows earlier transitions (corresponding to reduced extents of overcast clouds) closer to the low pressure center. We hypothesize that gradients in the meteorological pattern imposed by the prevailing DI induced a variability in substantial rain onset and thereby transition. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MBL trajectories to show that postfrontal trajectories closer to the low pressure center are more favorable to rain formation (and thereby cloud transitions) because of 1) weaker FT subsidence rates, 2) greater FT humidity, 3) stronger MBL winds, and 4) a colder MBL with reduced lower-tropospheric stability. LES confirms the observed variability in transitions, with substantial rain appearing earlier where there is swifter reduction of cloud condensation nucleus (CCN) concentration and increase of liquid water path (LWP). Prior to substantial rain, CCN budgets indicate dominant loss terms from FT entrainment and hydrometeor collisions. LWP-enhancing cloud thickness increases more rapidly for weaker large-scale subsidence that enables faster MBL deepening. Mere MBL warming and moistening cannot explain cloud thickness increases. The generality of such a DI-imposed cloud transition pattern merits further investigation with more cases that may additionally be convoluted by onshore aerosol gradients. Significance Statement: Cold-air outbreaks (CAOs) lead to marine boundary layer (MBL) clouds that commonly undergo rain-initiated overcast to broken cloud regime transitions that can drastically impact reflected solar radiation. We aim to better understand what mechanisms control these transitions. For a CAO event in the northwest Atlantic that shows earlier transitions closer to the low pressure center, we find the transition timing to be largely governed by the coinciding dry intrusion that imposes an inhomogeneous large-scale meteorological pattern onto the overlying free troposphere and thereby affects MBL rain formation. Our findings update conceptual understanding of extratropical cyclones and motivate analyzing observations and conducting simulations for more postfrontal cases through a Lagrangian perspective as done here for one case, to assess the generality of our findings. [ABSTRACT FROM AUTHOR]

An idealized case of gradual oceanic transition from shallow to deep convection is simulated at three different horizontal resolutions: one that resolves most of the turbulent eddies, one typical of cloud-resolving models, and one typical of general circulation models. The former serves as a reference and allows the identification of clouds as individual objects, distinguishing shallow cumulus, congestus, and cumulonimbus. At coarser resolutions, parameterizations of convection are included and assessed, with a particular focus on congestus clouds and precipitation associated with shallow convective clouds. Congestus clouds are found to contribute the most to turbulent transport during the transition, while occupying a volume comparable to shallow cumulus and cumulonimbus. Kilometer-scale horizontal resolutions prove to be insufficient to resolve congestus, and parameterization schemes of shallow and deep convection are not necessarily appropriate to represent those intermediate clouds. The representation of rainfall in the shallow convection scheme plays a key role in the transition. Sensitivity experiments show that enhanced rainfall inhibits convection in single-column simulations, while it favors resolved convection and spatial heterogeneities in three-dimensional simulations with kilometer-scale resolution. Results highlight the need for an appropriate parameterization of congestus in both kilometer-scale and large-scale models. The case study and the methods presented here are proposed as a useful framework to evaluate models and their parameterizations in a shallow-to-deep convection transition context. [ABSTRACT FROM AUTHOR]

Turbulent, recirculating, lean propane-air flames with inlet mixture stratification and preheat have been simulated under stable and limiting burning conditions. The modeled burner setup comprises a supply tube enclosing three sequential disks producing two consecutive premixing cavities. Fuel is injected in the first cavity and is partially premixed with primary air flowing through this cavity system, resulting in a radially stratified equivalence ratio profile at the inlet of the afterbody disk flame stabilizer. Detailed velocity, turbulence, fuel-air mixing, and imaging data have been previously reported for inlet preheats from 300 to 573 K and for a range of fuel flow rates. The simulations were carried out with a finite-volume-based method, using the dynamic Smagorinsky subgrid model coupled with two combustion methodologies, a quasi-laminar reaction rate approach and the Thickened Flame Model approach. Propane oxidation was modeled with a 22-species skeletal scheme. OH* chemiluminescence distributions were also computed by post-processing quasi-steady state derived algebraic expressions, exploiting directly simulated species thus enabling comparisons with experimental images. The simulations were evaluated against velocity, turbulence, and temperature measurements as well as chemiluminescence images. These comparisons allowed for an assessment of the methodologies' capability to reproduce important trends such as the notable extension of stable operation to ultra-lean mixtures, the appreciable effect on the near flame aerodynamic stretch and the variations in the local flame structure. [ABSTRACT FROM AUTHOR]

To address critical gaps identified by the National Academies of Sciences, Engineering, and Medicine in the current Earth system observation strategy, the 2017–27 Decadal Survey for Earth Science and Applications from Space recommended incubating concepts for future targeted observables including the atmospheric planetary boundary layer (PBL). A subsequent NASA PBL Incubation Study Team Report identified measurement requirements and activities for advancing the maturity of the technologies applicable to the PBL targeted observables and their associated science and applications priorities. While the PBL is the critical layer where humans live and surface energy, moisture, and mass exchanges drive the Earth system, it is also the farthest and most inaccessible layer for spaceborne instruments. Here we document a PBL retrieval observing system simulation experiment (OSSE) framework suitable for assessing existing and new measurement techniques and determining their accuracy and improvements needed for addressing the elevated Decadal Survey requirements. In particular, the benefits of large-eddy simulation (LES) are emphasized as a key source of high-resolution synthetic observations for key PBL regimes: from the tropics, through subtropics and midlatitudes, to subpolar and polar regions. The potential of LES-based PBL retrieval OSSEs is explored using six instrument simulators: Global Navigation Satellite System–Radio Occultation, differential absorption radar, visible to shortwave infrared spectrometer, infrared sounder, Multi-angle Imaging SpectroRadiometer, and microwave sounder. The crucial role of LES in PBL retrieval OSSEs and some perspectives for instrument developments are discussed. [ABSTRACT FROM AUTHOR]

Populated urban areas along many coastal regions are vulnerable to landfalling tropical cyclones (TCs). To the detriment of surface parameterizations in mesoscale models, the complexities of turbulence at high TC wind speeds in urban canopies are presently poorly understood. Thus, this study explores the impacts of urban morphology on TC-strength winds and boundary layer turbulence in landfalling TCs. To better quantify how urban structures interact with TC winds, large-eddy simulations (LESs) are conducted with the Cloud Model 1 (CM1). This implementation of CM1 includes immersed boundary conditions (IBCs) to represent buildings and eddy recycling to maintain realistic turbulent flow perturbations. Within the IBCs, an idealized coastal city with varying scales is introduced. TC winds impinge perpendicularly to the urbanized coastline. Numerical experiments show that buildings generate distinct, intricate flow patterns that vary significantly as the city structure is varied. Urban IBCs produce much stronger turbulent kinetic energy than is produced by conventional surface parameterizations. Strong effective eddy viscosity due to resolved eddy mixing is displayed in the wake of buildings within the urban canopy, while deep and enhanced effective eddy viscosity is present downstream. Such effects are not seen in a comparison LES using a simple surface parameterization with high roughness values. Wind tunneling effects in streamwise canyons enhance pedestrian-level winds well beyond what is possible without buildings. In the arena of regional mesoscale modeling, this type of LES framework with IBCs can be used to improve parameters in surface and boundary layer schemes to more accurately represent the drag coefficient and the eddy viscosity in landfalling TC boundary layers. Significance Statement: This is among the first large-eddy simulation model studies to examine the impacts of tropical cyclone–like winds around explicitly resolved buildings. This work is a step forward in bridging the gap between engineering studies that use computational fluid dynamics models or laboratory experiments for flow through cities and mesoscale model simulations of landfalling tropical cyclones that use surface parameterizations specialized for urban land use. [ABSTRACT FROM AUTHOR]

Banner clouds are clouds in the lee of steep mountains or sharp ridges on otherwise cloud-free days. Previous studies investigated various aspects of banner cloud formation in numerical simulations, most of which were based on idealized orography and a neutrally stratified ambient atmosphere. The present study extends these simulations in two important directions by 1) examining the impact of various types of orography ranging from an idealized pyramid to the realistic orography of Mount Matterhorn and 2) accounting for an ambient atmosphere that turns from neutral to stably stratified below the mountain summit. Not surprisingly, realistic orography introduces asymmetries in the spanwise direction. At the same time, banner cloud occurrence remains associated with a coherent area of strong uplift, although this region does not have to be located exclusively in the lee of the mountain any longer. In the case of Mount Matterhorn with a westerly ambient flow, a large fraction of air parcels rises along the southern face of the mountain, before they reach the lee and are lifted into the banner cloud. The presence of a shallow boundary layer with its top below the mountain summit introduces more complex behavior compared to a neutrally stratified boundary layer; in particular, it introduces a dependence on wind speed, because strong wind is associated with strong turbulence that is able to raise the boundary layer height and, thus, facilitates the formation of a banner cloud. [ABSTRACT FROM AUTHOR]

Hydrofoil sections are broadly used in the field of fluid machinery. The leading edge of a hydrofoil structure is closely related to drag and cavitation performance. In this study, we adopt the concept of a bionic design. The fin structure of a fish is simplified and applied to the traditional National Advisory Committee for Aeronautics 0015 hydrofoil. We adopt the Grey–Taguchi method to calculate the best layout. This helps obtain the best drag and cavitation performance. Large eddy simulations are used to verify the scheme. When the ratio of fin depth to length h/L is 0.3, the fin layout length Xn is 7 L, the inclination of fins θ is 7°, and the bionic hydrofoil exhibits the best hydrodynamic performance. Application of the best bionic hydrofoil to the fluid machinery (pump) demonstrates that the hydraulic performance of the pump has been considerably improved. [ABSTRACT FROM AUTHOR]

Abstract Cold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes.

Abstract: Boundary layer turbulence in coastal regions differs from that in deep ocean because of bottom interactions. In this paper, we focus on the merging of surface and bottom boundary layers in a finite-depth coastal ocean by numerically solving the wave-averaged equations using a large-eddy simulation method. The ocean fluid is driven by combined effects of wind stress, surface wave, and a steady current in the presence of stable vertical stratification. The resulting flow consists of two overlapping boundary layers, i.e., surface and bottom boundary layers, separated by an interior stratification. The overlapping boundary layers evolve through three phases, i.e., a rapid deepening, an oscillatory equilibrium and a prompt merger, separated by two transitions. Before the merger, internal waves are observed in the stratified layer, and they are excited mainly by Langmuir turbulence in the surface boundary layer. These waves induce a clear modulation on the bottom-generated turbulence, facilitating the interaction between the surface and bottom boundary layers. After the merger, the Langmuir circulations originally confined to the surface layer are found to grow in size and extend down to the sea bottom (even though the surface waves do not feel the bottom), reminiscent of the well-organized Langmuir supercells. These full-depth Langmuir circulations promote the vertical mixing and enhance the bottom shear, leading to a significant enhancement of turbulence levels in the vertical column.

Abstract How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the “true” surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue.

The intense and moist winds in a tropical cyclone (TC) environment can produce strong mountain waves and enhanced precipitation over complex terrain, yet few studies have investigated how the orographic precipitation in a TC environment might respond to global warming. Here, we use large-eddy simulation to estimate the global warming–induced change in the precipitation near an idealized mountain (1 km maximum height) with pseudo global warming. Two regions exhibit enhanced precipitation, one over the mountain and the other in the downstream region 25–45 km away from the mountain. The enhanced precipitation in both regions is related to the seeder–feeder mechanism, although the enhancement in the downstream regions differs from the conventional definition and is referred to as the pseudo-seeder–feeder mechanism (PSF). In the PSF, mountain waves generate an intense cloud formation center in the midtroposphere above the lee slope, and the resulting hydrometeors drift downstream, intensifying downstream convection when they fall into proper locations. Under warming, the overmountain precipitation maximum exhibits minimal changes, while the downstream precipitation maximum exhibits a large sensitivity of 18% K−1. The small sensitivity of the first precipitation peak is due to the canceling effects of thermodynamic and dynamic changes. The large sensitivity in the downstream region is mainly due to the strengthening of the wave-induced midtroposphere cloud formation center, which supplies more hydrometeors to the downstream region and enhances precipitation efficiency through the enhanced PSF mechanism. However, the downstream precipitation sensitivity varies with mountain geometry. Higher mountain height enhances precipitation but lowers the sensitivity to warming. Significance Statement: The combination of typhoon environment and orography can produce intense precipitation and thereby severe flooding risks. Here, we investigate the global warming response of orographic precipitation in a typhoon environment with idealized, high-resolution simulations. The experiments suggest that under warming, a precipitation maximum may emerge in the downstream region of a mountain or strengthen and shift upwind if it already exists in the current climate. This surprising amplification of downstream-region precipitation is related to the enhancement of the midtropospheric cloud generation caused by mountain waves and has critical implications for flooding risk management in mountainous regions. [ABSTRACT FROM AUTHOR]

The devastating winds in extratropical cyclones can be assigned to different mesoscale flows. How these strong winds are transported to the surface is discussed for the Mediterranean windstorm Adrian (Vaia), which caused extensive damage in Corsica in October 2018. A mesoscale analysis based on a kilometer-scale simulation with the Meso-NH model shows that the strongest winds come from a cold conveyor belt (CCB). The focus then shifts to a large-eddy simulation (LES) for which the strongest winds over the sea are located in a convective boundary layer. Convection is organized into coherent turbulent structures in the form of convective rolls. It is their downward branches that contribute most to the nonlocal transport of strong winds from the CCB to the surface layer. On landing, the convective rolls break up because of the complex topography of Corsica. Sensitivity experiments to horizontal grid spacing show similar organization of boundary layer rolls across the resolution. A comparative analysis of the kinetic energy spectra suggests that a grid spacing of 200 m is sufficient to represent the vertical transport of strong winds through convective rolls. Contrary to LES, convective rolls are not resolved in the kilometer-scale simulation and surface winds are overestimated due to excessive momentum transport. These results highlight the importance of convective rolls for the generation of surface wind gusts and the need to better represent them in boundary layer parameterizations. [ABSTRACT FROM AUTHOR]

Through Euler/Euler large eddy simulation (LES) modeling, it is demonstrated that turbulent dispersion of bubbles can effectively indicate the impact of turbulent eddies on the bubble dynamics, i.e., the bubble oscillation behavior. This finding builds on previous work using the Euler/Lagrange LES modeling approach and leads to a significant improvement in predicting bubble lateral dispersion. Spatially filtered terms were proposed for the subgrid‐scale (SGS) turbulent dispersion and added mass stress force models, with a modification made to the SGS eddy viscosity to reflect bubble turbulent dispersion and oscillations. The proposed model substantially improves the prediction of bubble volume fraction distribution, bubble and liquid phase velocity profiles, the turbulent kinetic energy spectrum, and mass transfer. [ABSTRACT FROM AUTHOR]

Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh-Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed. [ABSTRACT FROM AUTHOR]

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber. [ABSTRACT FROM AUTHOR]

The observed development of deep mixed layers and the dependence of intense, deep-mixing events on wind and wave conditions are studied using an ocean LES model with and without an imposed Stokes-drift wave forcing. Model results are compared to glider measurements of the ocean vertical temperature, salinity, and turbulence kinetic energy (TKE) dissipation rate structure collected in the Icelandic Basin. Observed wind stress reached 0.8 N m2-2 with significant wave height of 4-6 m, while boundary layer depths reached 180 m. We find that wave forcing, via the commonly used Stokes drift vortex force parameterization, is crucial for accurate prediction of boundary layer depth as characterized by measured and predicted TKE dissipation rate profiles. Analysis of the boundary layer kinetic energy (KE) budget using a modified total Lagrangian-mean energy equation, derived for the wave-averaged Boussinesq equations by requiring that the rotational inertial terms vanish identically as in the standard energy budget without Stokes forcing, suggests that wind work should be calculated using both the surface current and surface Stokes drift. A large percentage of total wind energy is transferred to model TKE via regular and Stokes drift shear production and dissipated. However, resonance by clockwise rotation of the winds can greatly enhance the generation of inertial current mean KE (MKE). Without resonance, TKE production is about 5 times greater than MKE generation, whereas with resonance this ratio decreases to roughly 2. The results have implications for the problem of estimating the global kinetic energy budget of the ocean. [ABSTRACT FROM AUTHOR]

We develop innovative analytical expressions for the mean wind and potential temperature flux profiles in convective boundary layers (CBLs). CBLs are frequently observed during daytime as Earth's surface is warmed by solar radiation. Therefore, their modeling is relevant for weather forecasting, climate modeling, and wind energy applications. For CBLs in the convective-roll-dominated regime, the mean velocity and potential temperature in the bulk region of the mixed layer are approximately uniform. We propose an analytical expression for the normalized potential temperature flux profile as a function of height, using a perturbation method approach in which we employ the horizontally homogeneous and quasi-stationary characteristics of the surface and inversion layers. The velocity profile in the mixed layer and the entrainment zone is constructed based on insights obtained from the proposed potential temperature flux profile and the convective logarithmic friction law. Combining this with the well-known Monin–Obukhov similarity theory allows us to capture the velocity profile over the entire boundary layer height. The proposed profiles agree excellently with large-eddy simulation results over the range of −L/z0 ∈ [3.6 × 102, 0.7 × 105], where L is the Obukhov length and z0 is the roughness length. [ABSTRACT FROM AUTHOR]

The results of numerical simulations of inclined negatively buoyant jets are presented. These simulations address previously highlighted difficulties in capturing sufficient detail of critical flow processes to effectively predict the detailed flow behaviour. In particular, the new simulations are able to accurately capture the details of the buoyancy-induced instabilities, which are clearly evident in associated experimental investigations and that have significant impacts on the flow behaviour. This new information is captured for inclined negatively buoyant jets discharged at 45° above a horizontal reference plane. A Large Eddy Simulation (LES) approach is implemented that makes use of a Lagrangian Dynamic Sub-grid scale (SGS) model and a novel criterion for the adaptive meshing system. Comparisons with previously published simulation results and experimental data demonstrate that these new Adaptive LES simulations provide improved predictions of flow path, concentration and velocity fields, and associated mean and turbulent statistics. In addition, this study provides a set of methods for generating high-quality LES data sets for free shear flows, which are well beyond the level of detail that can be captured by current experimental systems. [ABSTRACT FROM AUTHOR]

Periodic vortex shedding which forms when fluid moves over a circular cylinder creates a wake which causes fluctuating unsteady forces on structures. The oscillating wake may also serve to enhance heat transfer rates from a surface on which it impinges. In this paper we investigate the passive excitation of the impinging jet's velocity field using a cylindrical insert. The insert is placed just before where the jet issues from the circular pipe. The flow is examined using Large Eddy Simulations (LES). The jet's Reynolds number based on bulk inlet velocity is 23,000 and jet's outlet-to-target wall distance is two. It is found that using a cylindrical insert in the impingement pipe results in enhanced heat transfer rates for cooling applications.

This study proposes a cost-effective machine-learning based model for predicting velocity and turbulence kinetic energy fields in the wake of wind turbines for yaw control applications. The model consists of an auto-encoder convolutional neural network (ACNN) trained to extract the features of turbine wakes using instantaneous data from large-eddy simulation (LES). The proposed framework is demonstrated by applying it to the Sandia National Laboratory Scaled Wind Farm Technology facility consisting of three 225 kW turbines. LES of this site is performed for different wind speeds and yaw angles to generate datasets for training and validating the proposed ACNN. It is shown that the ACNN accurately predicts turbine wake characteristics for cases with turbine yaw angle and wind speed that were not part of the training process. Specifically, the ACNN is shown to reproduce the wake redirection of the upstream turbine and the secondary wake steering of the downstream turbine accurately. Compared to the brute-force LES, the ACNN developed herein is shown to reduce the overall computational cost required to obtain the steady state first and second-order statistics of the wind farm by about 85%.

Land–atmosphere interactions play a critical role in both the atmospheric water and energy cycles. Changes in soil moisture and vegetation alter the partitioning of surface water and energy fluxes, influencing diurnal evolution of the planetary boundary layer (PBL). The mixing-diagram framework has proven useful in understanding the evolution of the heat and moisture budget within the convective boundary layer (CBL). We demonstrate that observations from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site provide all of the needed inputs needed for the mixing-diagram framework, allowing us to quantify the impact from the surface fluxes, advection, radiative heating, encroachment, and entrainment on the evolution of the CBL. Profiles of temperature and humidity retrieved from the ground-based infrared spectrometer [Atmospheric Emitted Radiance Interferometer (AERI)] are a critical component in this analysis. Large-eddy simulation results demonstrate that mean mixed-layer values derived are shown to be critical to close the energy and moisture budgets. A novel approach demonstrated here is the use of network of AERIs and Doppler lidars to quantify the advective fluxes of heat and moisture. The framework enables the estimation of the entrainment fluxes as a residual, providing a way to observe the entrainment fluxes without using multiple lidar systems. The high temporal resolution of the AERI observations enables the morning, midday, and afternoon evolution of the CBL to be quantified. This work provides a new way to use observations in this framework to evaluate weather and climate models. Significance Statement: The energy and moisture budget of the planetary boundary layer (PBL) is influenced by multiple sources, and accurately representing this evolution in numerical models is critical for weather forecasts and climate predictions. The mixing-diagram approach, driven by profiling observations as illustrated here, provides a powerful way to quantify the contributions from each of these sources. In particular, the energy and moisture mixed into the PBL from above the PBL can be determined accurately from ground-based remote sensors using this approach. [ABSTRACT FROM AUTHOR]

In large-eddy simulations (LES), it is crucial to ensure that discretization errors do not contaminate the subgrid effect of the turbulence model in a wavelength range larger than the effective resolution. Recently, we showed that a seventh- or eighth-order accuracy is required for advection terms in planetary boundary layer simulations when using conventional gridpoint methods. However, a significant amount of communication between parallel computers is necessary to achieve high-order accuracy in gridpoint methods, and this can degrade computational efficiency. The discontinuous Galerkin method (DGM) is a promising approach for overcoming these limitations. Therefore, this study focuses on the numerical criteria of the DGM at LES from the viewpoint of numerical diffusion and dispersion. We extend our earlier study to the DGM framework and clarify the necessary order of the polynomial (p). We find that p = 4 is required based on the numerical criteria at the grid spacing of O(10) m with sufficiently scale-selective modal filters. The examination of temporal accuracy suggests that the fourth-order is sufficient when a fully explicit temporal scheme is used. In addition, we investigate the effect of hyperupwinding that is usually met when the Rusanov flux is employed in the low Mach number flows. It suggests that the choice of numerical flux has little effect on simulation results when the high-order DGM is used. Furthermore, we perform a series of LES in the planetary boundary layer and confirm that the indication obtained from the criteria holds for an actual LES. [ABSTRACT FROM AUTHOR]