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DOE OSTI2023

Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations

Abstract We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO 2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO 2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗

DOE OSTI2024

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Geology↗

DOE OSTI2020

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Multifidelity validation of digital surrogates using variable-density turbulent mixing models

In this study, ensembles of experimental data are presented and utilized to compare and validate two models used in the simulation of variable-density (Atwood = 0.22), compressible turbulent mixing. Though models of this kind (Reynolds averaged NavierStokes and large-eddy simulations) have been validated extensively with more canonical flows in previous studies, here the present approach offers novelty in the complexity of the geometry, the ensemble-based validation, and the uniformity of the computational framework on which the models are tested. Moreover, all experimental and computational tasks were completed by the authors which has led to a tightly coupled experimental configuration with its “digital twin.” The experimental divergent-shock-tube facility and its data acquisition methods are described and replicated in simulation space. A 2D Euler model which neglects the turbulent mixing at the interface is optimized to experimental data using a Gaussian process. This model then serves as the basis for both the 2D RANS and 3D LES studies that make comparisons to the mixing-layer data from the experiment. A relatively simple RANS model is shown to produce good agreement with experimental data only at late flow development times. The LES ensembles generally show good agreement with experimental data but display sensitivity to the characterization of initial conditions. Resolution-dependent behavior is also observed for certain higher-order statistics of interest. Overall, the LES model successfully captures the effects of divergent geometry, compressibility, and combined nonlinear instabilities inherent to the problem. The successful prediction of mixing width and its growth rate highlight the existence of three distinct regimes in the development of the instability, each with similarities to previously studied instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Porting a fast-running wildfire plume model for use in national security and climate applications

In this project, the code for the fast-running Freitas wildfire plume model was successfully ported into the NARAC system, creating an operations-ready capability for predicting the transport of hazardous smoke from large wildfires. “Porting” refers to copying a section of code from one software package to another while accounting for unique dependencies in each software package. In this case, the code was ported from the Weather Research and Forecasting (WRF) Model, which is used extensively by the project team. To verify correct implementation, model results from the updated NARAC system were compared to those from WRF and the High-Resolution Rapid Refresh (HRRR) forecast model, which also employs the Freitas scheme. The NARAC User Interface (UI) and code documentation were also updated to include the new wildfire plume option, and a wildfire case was added to the NARAC test suite. The code was used in a real-time, semi-operational setup to predict smoke transport during the Cerro Pelado fire near Los Alamos National Laboratory in May 2022. The Freitas plume model was also tested for LLNL climate applications. Although the code was not ported into the Energy Exascale Earth System Model (E3SM), it was tested offline using E3SM atmospheric inputs, and results were compared to existing high-resolution plume predictions from large-eddy simulations in WRF. The code implementation and testing completed during this project will enable future work predicting smoke transport from large wildfires in LLNL national security and climate mission spaces.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Size dependence in chord characteristics from simulated and observed continental shallow cumulus

Abstract. In this study we compare long-term Doppler and Raman lidar observations against a full month of large eddy simulations of continental shallow cumulus clouds. The goal is to evaluate if the simulations can reproduce the mean observed vertical velocity and moisture structure of cumulus clouds and their associated subcloud circulations, as well as to establish if these properties depend on the size of the cloud. We propose methods to compare continuous chords of cloud detected from Doppler and Raman lidars with equivalent chords derived from 1D and 3D model output. While the individual chords are highly variable, composites of thousands of observed and millions of simulated chords contain a clear signal. We find that the simulations underestimate cloud size and fraction but successfully reproduce the observed structure of vertical velocity and moisture perturbations. There is a clear scaling of vertical velocity and moisture anomalies below the chords with chord size, but the moisture anomalies are only 1 %–2 % higher than the horizontal mean values. The differences between the observations and simulations are smaller than the difference in sampling the modeled chords in time or space. The shape of the vertical velocity and moisture anomalies from cloud chords sampled spatially from 3D model snapshots is almost perfectly symmetric. In contrast, the chords sampled temporally from the lidar observations and 1D model output have a marked asymmetry, with stronger updrafts and higher moisture anomalies occurring earlier on.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

Numerical Simulation of High-Speed Turbulent Reacting Flows

The purpose of this research is to continue our efforts in advancing the state of knowledge in large eddy simulation (LES) methods for computational analysis of high-speed reacting turbulent flows. We have just completed the first year of Phase 3 of this research.

Jaberi, F. A.↗

NASA NTRS2001

The Numerical Analysis of a Turbulent Compressible Jet

A numerical method to simulate high Reynolds number jet flows was formulated and applied to gain a better understanding of the flow physics. Large-eddy simulation was chosen as the most promising approach to model the turbulent structures due to its compromise between accuracy and computational expense. The filtered Navier-Stokes equations were developed including a total energy form of the energy equation. Subgrid scale models for the momentum and energy equations were adapted from compressible forms of Smagorinsky's original model. The effect of using disparate temporal and spatial accuracy in a numerical scheme was discovered through one-dimensional model problems and a new uniformly fourth-order accurate numerical method was developed. Results from two- and three-dimensional validation exercises show that the code accurately reproduces both viscous and inviscid flows. Numerous axisymmetric jet simulations were performed to investigate the effect of grid resolution, numerical scheme, exit boundary conditions and subgrid scale modeling on the solution and the results were used to guide the three-dimensional calculations. Three-dimensional calculations of a Mach 1.4 jet showed that this LES simulation accurately captures the physics of the turbulent flow. The agreement with experimental data was relatively good and is much better than results in the current literature. Turbulent intensities indicate that the turbulent structures at this level of modeling are not isotropic and this information could lend itself to the development of improved subgrid scale models for LES and turbulence models for RANS simulations. A two point correlation technique was used to quantify the turbulent structures. Two point space correlations were used to obtain a measure of the integral length scale, which proved to be approximately 1/2 D(sub j). Two point space-time correlations were used to obtain the convection velocity for the turbulent structures. This velocity ranged from 0.57 to 0.71 U(sub j).

DeBonis, James R.↗

NASA NTRS2002

Filtered Mass Density Function for Design Simulation of High Speed Airbreathing Propulsion Systems

The objective of this research is to improve and implement the filtered mass density function (FDF) methodology for large eddy simulation (LES) of high speed reacting turbulent flows. NASA is interested in the design of various components involved in air breathing propulsion systems such as the scramjet. There is a demand for development of robust tools that can aid in the design procedure. The physics of high speed reactive flows is rich with many complexities. LES is regarded as one of the most promising means of simulating turbulent reacting flows.

Givi, P.↗

NASA NTRS2014

Investigation of Unsteady Flow Field in a Low-Speed One and a Half Stage Axial Compressor: Effects of Tip Gap Size On the Tip Clearance Flow Structure at Near Stall Operation - Part 2

The primary focus of this paper is to investigate the effect of rotor tip gap size on how the rotor unsteady tip clearance flow structure changes in a low speed one and half stage axial compressor at near stall operation (for example, where maximum pressure rise is obtained). A Large Eddy Simulation (LES) is applied to calculate the unsteady flow field at this flow condition with both a small and a large tip gaps. The numerically obtained flow fields at the small clearance matches fairly well with the available initial measurements obtained at the Johns Hopkins University with 3-D unsteady PIV in an index-matched test facility which renders the compressor blades and casing optically transparent. With this setup, the unsteady velocity field in the entire flow domain, including the flow inside the tip gap, can be measured. The numerical results are also compared with previously published measurements in a low speed single stage compressor (Maerz et al. [2002]). The current study shows that, with the smaller rotor tip gap, the tip clearance vortex moves to the leading edge plane at near stall operating condition, creating a nearly circumferentially aligned vortex that persists around the entire rotor. On the other hand, with a large tip gap, the clearance vortex stays inside the blade passage at near stall operation. With the large tip gap, flow instability and related large pressure fluctuation at the leading edge are observed in this one and a half stage compressor. Detailed examination of the unsteady flow structure in this compressor stage reveals that the flow instability is due to shed vortices near the leading edge, and not due to a three-dimensional separation vortex originating from the suction side of the blade, which is commonly referred to during a spike-type stall inception. The entire tip clearance flow is highly unsteady. Many vortex structures in the tip clearance flow, including the sheet vortex system near the casing, interact with each other. The core tip clearance vortex, which is formed with the rotor tip gap flows near the leading edge, is also highly unsteady or intermittent due to pressure oscillations near the leading edge and varies from passage to passage. For the current compressor stage, the evidence does not seem to support that a classical vortex breakup occurs in any organized way, even with the large tip gap. Although wakes from the IGV influence the tip clearance flow in the rotor, the major characteristics of rotor tip clearance flows in isolated or single stage rotors are observed in this one and a half stage axial compressor.

Unsteady↗

DOE OSTI2019

Scaling of an Atmospheric Model to Simulate Turbulence and Cloud Microphysics in the Pi Chamber

Abstract The Pi Cloud Chamber offers a unique opportunity to study aerosol‐cloud microphysics interactions in a steady‐state, turbulent environment. In this work, an atmospheric large‐eddy simulation (LES) model with spectral bin microphysics is scaled down to simulate these interactions, allowing comparison with experimental results. A simple scalar flux budget model is developed and used to explore the effect of sidewalls on the bulk mixing temperature, water vapor mixing ratio, and supersaturation. The scaled simulation and the simple scalar flux budget model produce comparable bulk mixing scalar values. The LES dynamics results are compared with particle image velocimetry measurements of turbulent kinetic energy, energy dissipation rates, and large‐scale oscillation frequencies from the cloud chamber. These simulated results match quantitatively to experimental results. Finally, with the bin microphysics included the LES is able to simulate steady‐state cloud conditions and broadening of the cloud droplet size distributions with decreasing droplet number concentration, as observed in the experiments. The results further suggest that collision‐coalescence does not contribute significantly to this broadening. This opens a path for further detailed intercomparison of laboratory and simulation results for model validation and exploration of specific physical processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Chapter 14: Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation

In this chapter we demonstrate how supervised deep learning techniques can be used to construct models for the filtered progress variable source term necessary for large eddy simulation (LES). The source data for the model is a direct numerical simulation (DNS) of a reacting flow in a low swirl burner configuration. Filtered quantities taken from the DNS data are used to train a deep neural network (DNN)-based model. An efficient data sampling strategy was devised to ensure that a uniform representation of all the states observed in the filtered DNS data are equally present in the training dataset. A-priori testing of the DNN-based model highlights the representative power of DNN to accurately reproduce the filtered reaction progress variable source term over a range of scales and various flame regimes as seen in an industrial burner.

combustion LES models↗

NASA NTRS2003

A Novel Strategy for Numerical Simulation of High-speed Turbulent Reacting Flows

The objective of this research is to improve and implement the filtered mass density function (FDF) methodology for large eddy simulation (LES) of high-speed reacting turbulent flows. We have just completed Year 1 of this research. This is the Final Report on our activities during the period: January 1, 2003 to December 31, 2003. 2002. In the efforts during the past year, LES is conducted of the Sandia Flame D, which is a turbulent piloted nonpremixed methane jet flame. The subgrid scale (SGS) closure is based on the scalar filtered mass density function (SFMDF) methodology. The SFMDF is basically the mass weighted probability density function (PDF) of the SGS scalar quantities. For this flame (which exhibits little local extinction), a simple flamelet model is used to relate the instantaneous composition to the mixture fraction. The modelled SFMDF transport equation is solved by a hybrid finite-difference/Monte Carlo scheme.

Sheikhi, M. R. H.↗

DOE OSTI2023

Direct Numerical Simulation of Partial Fuel Stratification Assisted Lean Premixed Combustion for Assessment of Hybrid G-Equation/Well-Stirred Reactor Model

Partial fuel stratification (PFS) is a promising fuel injection strategy to stabilize lean premixed combustion in spark-ignition (SI) engines. PFS creates a locally stratified mixture by injecting a fraction of the fuel, just before spark timing, into the engine cylinder containing homogeneous lean fuel/air mixture. Further, this locally stratified mixture, when ignited, results in complex flame structure and propagation modes similar to partially premixed flames and allows for faster and more stable flame propagation than a homogeneous lean mixture. This study focuses on understanding the detailed flame structures associated with PFS-assisted lean premixed combustion. First, a two-dimensional direct numerical simulation (DNS) is performed using detailed fuel chemistry, experimental pressure trace, and realistic initial conditions mapped from a prior engine large-eddy simulation (LES), replicating practical lean SI operating conditions. DNS results suggest that the conventional triple flame structure is prevalent during the initial stage of flame kernel growth. Both premixed and nonpremixed combustion modes are present with the premixed mode contributing dominantly to the total heat release. Detailed analysis further reveals the effects of flame stretch and fuel pyrolysis on flame displacement speed. Based on the DNS findings, the accuracy of a hybrid G-equation/well-stirred reactor (WSR) combustion model is assessed for the PFS-assisted lean operation in the LES context. It is found that the G-equation model qualitatively captures the premixed branches of the triple flame, while the WSR model predicts the nonpremixed branch of the triple flame. Finally, potential needs for improvements to the hybrid G-equation/WSR modeling approach are discussed.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Wind Energy Forecasting with the Weather Research and Forecasting Model

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Siemens Energy, Inc. (Siemens) to develop a wind resource forecasting tool. LLNL was to develop an independent high-resolution mesoscale modeling capability forecasting tool that could be implemented in conjunction with existing wind farm control and monitoring software to provide forecasting of wind resources using local observations of winds and temperature. Research with LLNL’s state-of-the-art large-eddy simulation meteorological prediction model, based on the community WRF model and innovative turbulence parameterizations, would improve that model’s applicability to large wind farms offshore and in complex terrain. The modeling capability would include uncertainty quantification. Finally, the application of the modeling tool and existing global climate change predictions would enable the delineation of the likely effects of climate change on wind resources. Siemens was to provide high time resolution hub-height wind speed and other meteorological data streams, including temperature profiles from wind farms, for LLNL to incorporate into the modeling system, to validate and tune this forecasting model for their locations of interest. These data streams would also be used for longer-term studies of correlations of wind resources to climate oscillations to indicate how long-term climate change trends may affect the available wind resource. Siemens would also provide information and observations of turbine wakes for incorporation into the modeling tool. By implementing state-of-the-art turbulence parameterizations into a simulation model and/or ensembles of simulation models, and by integrating real-time hub height wind speed and other meteorological datastreams from wind farms into that model or ensemble of models, LLNL would develop a forecasting tool that could be implemented by Siemens as an add-on to existing wind farm control and monitoring software to provide owners with useful resource forecasting. The desired outcome was that the accuracy level of the output would be sufficient to substantiate power output commitments. The final deliverable for this work would consist of a document outlining the algorithms and software tools that could be integrated into Siemens Wind Park Supervisor.

17 WIND ENERGY↗

DOE OSTI2026

Convective Biases in the US DOE Global Storm‐Resolving Model: Insights From Regionally Refined Simulations During the CACTI Campaign

Accurately simulating convective processes in complex terrain remains a critical challenge for global storm-resolving models (GSRMs). This study systematically evaluates moist convective biases in the Regionally Refined Mesh configuration of the U.S. Department of Energy Simple Cloud-Resolving E3SM Atmosphere Model (RRM-SCREAM) using comprehensive observations and large-eddy simulations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in the mountainous area of central Argentina. Comparisons of simulations with high-resolution observations and reanalysis data indicate that RRM-SCREAM effectively captures large-scale meteorological patterns, including regional atmospheric gradients and diurnal variability. However, RRM-SCREAM disproportionately produces smaller precipitation clusters referred to as “popcorn convection,” and exaggerated rainfall intensities compared to observations and reference models. Detailed examination of a representative orographic shallow-to-deep convective transition case shows that RRM-SCREAM delays initial shallow convection growth due to lower-tropospheric dryness and sustained convective inhibition, but once triggered, deep convection becomes overly vigorous with excessively strong vertical velocities and elevated cloud ice content, linked to a thermodynamic structure characterized by suppressed low-level moistening and excessive upper-level moisture retention. Our results highlight specific deficiencies in the model representation of convective vertical velocity, cloud microphysical processes, and convective precipitation organization within RRM-SCREAM. Addressing these biases is essential for improving the predictions of convective clouds and precipitation in the global high-resolution atmospheric models.

Su, Tianning [Lawrence Livermore National Laborato↗

DOE OSTI2022

Coupling Warm Rain With an Eddy Diffusivity/Mass Flux Parameterization: 1. Model Description and Validation

A new version of the stochastic multiplume Jet Propulsion Laboratory Eddy-Diffusivity/Mass-Flux (JPL-EDMF) parameterization which consistently couples the simplified Khairoutdinov and Kogan (2000), https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, warm phase cloud microphysical parameterization with the parameterization of cloud macrophysical and subgrid scale dynamical processes is described. The new parameterization combines the EDMF approach with an assumed shape of a joint probability density function of thermodynamic and kinematic variables which provide the basis for the computation of all parameterized processes. As far as we are aware this is the first attempt to consistently couple all of these parameterized processes in the EDMF framework. This paper is part one of a two paper series. Here, the JPL-EDMF parameterization is described and benchmark simulations of precipitating stratocumulus and cumulus convection are performed in a single-column-model framework. The parameterization results compare favorably to the reference large-eddy-simulation results. In the second part (Smalley et al., 2022, https://doi.org/10.1029/2021MS002729) the JPL-EDMF parameterization is validated for a wide range of observation-based scenarios covering the continuous transition from subtropical stratocumulus to cumulus convection derived from global reanalysis, and parameterization uncertainties are studied in detail.

54 ENVIRONMENTAL SCIENCES↗