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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Statistical Evaluation of WRF-LES Trace Gas Dispersion Using Project Prairie Grass Measurements

In recent years, new measurement systems have been deployed to monitor and quantify methane emissions from the natural gas sector. Large-eddy simulation (LES) has complemented measurement campaigns by serving as a controlled environment in which to study plume dynamics and sampling strategies. However, with few comparisons with controlled-release experiments, the accuracy of LES for modeling natural gas emissions is poorly characterized. In this paper, we evaluate LES from the Weather Research and Forecasting (WRF) Model against Project Prairie Grass campaign measurements and surface layer similarity theory. Using WRF-LES, we simulate continuous emissions from 30 near-surface trace gas sources in two stability regimes: strong convection and weak convection. We examine the impact of grid resolutions ranging from 6.25 to 52 m in the horizontal dimension on model results. We evaluate performance in a statistical framework, calculating fractional bias and conducting Welch’s t tests. WRF-LES accurately simulates observed surface concentrations at 100 m and beyond under strong convection; simulated concentrations pass t tests in this region irrespective of grid resolution. However, in weakly convective conditions with strong winds, WRF-LES substantially overpredicts concentrations—the magnitude of fractional bias often exceeds 30%, and all but one t test fails. The good performance of WRF-LES under strong convection correlates with agreement with local free convection theory and a minimal amount of parameterized turbulent kinetic energy. The poor performance under weak convection corresponds to misalignment with Monin–Obukhov similarity theory and a significant amount of parameterized turbulent kinetic energy.

17 WIND ENERGY↗
DOE OSTI2026

Horne et al. (2026) supporting files - WRF-LES model outputs for a summer heatwave event on June 2025 in Baltimore, MD

Brief Description Shown is the supporting information for Horne et al. (2026). These files include all outputs from the WRF model simulations and the observational datasets used for comparison in the study. Scripts are provided so users can recreate the manuscript's figures using the provided observational and modeling data. For more information regarding the study, please contact the primary author of the associated manuscript, Jason Horne. Horne, J. P., Pan, Y., Davis, K. J., Waugh, D., Ahlswede, B. J., Prince, N. E. (2026). Simulating near-surface environments in urban neighborhoods using WRF-LES: A case study of classic atmospheric boundary layer (ABL) during a heatwave event JAMES. (to be submitted)

atmosphere↗
DOE OSTI2026

Horne et al. (2026) supporting files - WRF-LES model outputs for a summer heatwave event on June 2025 in Baltimore, MD

Brief Description Shown is the supporting information for Horne et al. (2026). These files include all outputs from the WRF model simulations and the observational datasets used for comparison in the study. Scripts are provided so users can recreate the manuscript's figures using the provided observational and modeling data. For more information regarding the study, please contact the primary author of the associated manuscript, Jason Horne. Horne, J. P., Pan, Y., Davis, K. J., Waugh, D., Ahlswede, B. J., Prince, N. E. (2026). Simulating near-surface environments in urban neighborhoods using WRF-LES: A case study of classic atmospheric boundary layer (ABL) during a heatwave event JAMES.

atmosphere↗
DOE OSTI2022

Can lidars assess wind plant blockage in simple terrain? A WRF-LES study

Wind plant blockage reduces wind velocity upstream of wind plants, reducing the power generated by turbines adjacent to the inflow, and potentially throughout the plant as well. The nature of the mechanism that amplifies blockage as well as the velocity reductions in both the induction zone and potentially deeper into the array are not well understood. Field observations can provide valuable insight into the characteristics of the induction zone and the mechanisms that amplify it. However, the relatively small velocity reductions that have been measured experimentally pose a challenge in quantifying blockage, especially in onshore environments with flow heterogeneities that may be of the same scale as the blockage effect itself. We simulate the flow around the King Plains wind plant in the relatively simple terrain of Oklahoma, the location of the American WAKE experimeNt, to evaluate wind plant blockage in this environment. Using numerical simulations, we find the largest velocity deceleration (0.64 m s−1; 8%) immediately upstream of the wind plant, and 1% velocity deficits 24 rotor diameters upstream of the first turbine row. We also use virtual measurements upstream of the wind plant to analyze the uncertainties and difficulties in measuring blockage using a scanning lidar on shore. Based on our virtual lidar study, the induction zone of land-based wind plants can be incorrectly estimated using observations if the effects of nonuniform terrain on the flow are not carefully considered. Changes in terrain elevation produce local variations in wind speed (as measured by a scanning lidar) that exceed in magnitude the deceleration within the induction zone. We refer to these local changes in wind speed as terrain effects. A methodology to differentiate between terrain effects and blockage in experimental settings is proposed and evaluated herein, highlighting the difficulties and uncertainties associated with measurement and simulation of blockage in even relatively simple onshore environments.

17 WIND ENERGY↗
DOE OSTI2021

PNNL - WRF-LES - Convective - TTU

This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2021

ANL - WRF-LES - Convective - TTU

This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2021

LANL - WRF-LES - Convective - TTU

This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2021

LLNL - WRF-LES - Neutral - TTU

This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2021

ANL - WRF-LES - Neutral - TTU

This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2021

LANL - WRF-LES - Neutral - TTU

This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2023

LLNL - WRF-LES - Convective - TTU

This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2023

NREL - WRF-LES - Neutral - TTU

This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2023

SNL - WRF-LES - Convective - TTU

This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

17 WIND ENERGY↗
DOE OSTI2023

Sensitivity of deep convection and cross-tropopause water transport to microphysical parameterizations in WRF

Deep convective storms can overshoot the tropopause, thus altering the composition of the stratosphere by vertically transporting tropospheric air. The transport of water vapor and ice particles into a sub-saturated environment can hydrate the stratosphere, with implications for radiative forcing and ozone chemistry. Cloud-resolved models, if employed at high spatial resolutions, are used to probe process-level questions about cross-tropopause deep convective hydration and its controls. There is considerable diversity in model representations of processes associated with water transport and transformation, and the choice of a microphysics scheme affects model skill in simulating deep convective events. This motivates our evaluation of state-of-the-art, as well as widely used standard schemes, in a high spatial- and temporal-resolution framework. Six bulk microphysics schemes were employed in a WRF-LES setup, initialized with a sounding profile representative of a tropopause-overshooting storm. Here, we used an idealized framework to isolate the effect of microphysics on the dominant processes that control the reach of deep convection and stratospheric hydration. All schemes produced the highest reaching updrafts 8-12 hours into the simulation but the strength and persistence of updrafts varied across the schemes; maximum storm heights ranged 9.1-12.6 km across the schemes. Varying microphysics produced large differences in the vertical extent and horizontal aggregation of convection, and an order of magnitude spread in above-tropopause water vapor concentrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulating Real Atmospheric Boundary Layers at Gray-Zone Resolutions: How Do Currently Available Turbulence Parameterizations Perform?

Recent computational and modeling advances have led a diverse modeling community to experiment with atmospheric boundary layer (ABL) simulations at subkilometer horizontal scales. Accurately parameterizing turbulence at these scales is a complex problem. The modeling solutions proposed to date are still in the development phase and remain largely unvalidated. This work assesses the performance of methods currently available in the Weather Research and Forecasting (WRF) model to represent ABL turbulence at a gray-zone grid spacing of 333 m. We consider three one-dimensional boundary layer parameterizations (MYNN, YSU and Shin-Hong) and coarse large-eddy simulations (LES). The reference dataset consists of five real-case simulations performed with WRF-LES nested down to 25 m. Results reveal that users should refrain from coarse LES and favor the scale-aware, Shin-Hong parameterization over traditional one-dimensional schemes. Overall, the spread in model performance is large for the cellular convection regime corresponding to the majority of our cases, with coarse LES overestimating turbulent energy across scales and YSU underestimating it and failing to reproduce its horizontal structure. Despite yielding the best results, the Shin-Hong scheme overestimates the effect of grid dependence on turbulent transport, highlighting the outstanding need for improved solutions to seamlessly parameterize turbulence across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing the Atmospheric Response to Subgrid Surface Heterogeneity in the Single-Column Community Earth System Model, Version 2 (CESM2)

Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid-scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single-column simulations against high-resolution Weather Research and Forecasting (WRF) large-eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF-LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Behavior and mechanisms of Doppler wind lidar error in complex terrain: stable flow case study at Perdigão

A numerical experiment is carried out investigating the magnitude of biases in ground-based lidar measurements in complex flow conditions. Biases assessed include those arising from flow curvature and from the interaction of turbulence with the wind field reconstruction (WFR) algorithms used by a WindCube lidars and anemometers. RANS-CFD and WRF-LES simulations were performed for the Perdig˜ao Field Experiment site for a range of atmospheric conditions. Virtual anemometer and lidar data were generated for four locations: two near exposed ridge tops and two in low-speed regions in the valley. The LES data at these four locations show that the scalar inflation terms (the relation between scalar and vector averaged wind speed) for virtual lidar and virtual cups agree very well with predictions using perturbation theory. While the lidar errors vary greatly with location and height, the contribution from the flow curvature tends to be larger than the differences arising from scalar inflation. For one lidar/mast pair near the ridge top, comparisons between simulations and measurements are carried out for a resonant mountain wave event on June 14th, 2017, and for the whole duration of the Perdigão campaign for winds perpendicular to the ridges. The lidar error during the mountain wave, a period of strong stability and low inversion height, is significantly larger than the campaign average. The sensitivity of the lidar error to atmospheric stability is confirmed by the RANS simulations, which suggests strong sensitivity of flow curvature error to stability conditions and to the shape of the wind speed profile near the top of the boundary layer.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Boundary-Layer Cloud Modeling Challenges on the North Slope of Alaska

The accurate modeling and prediction of cloud base heights is critical for energy balance calculations and aviation operations, alike. Low-level (i.e., boundary-layer) Arctic clouds can be difficult to model, making prediction of formation and dissipation challenging. Primarily mixed-phase, these clouds typically contain low quantities of supercooled liquid water and often slowly precipitate relatively small amounts of moderately and heavily rimed snow particles. While this appears to be the predominant cloudy state on the North Slope of Alaska (NSA), the delicate balance of microphysical, dynamical, radiative, surface coupling, and advective processes can rapidly shift to heavy snow (with various degrees of riming) or to a complete dissipation of the cloud layer without any precipitation, depending on the dominant processes. Here we strive to disentangle these various processes. First, we compare the predictive performances of four different numerical weather models in forecasting the presence and base-heights of low-level clouds: the High-Resolution Rapid Refresh - Alaska (HRRR-AK) model, the Polar Weather Research and Forecasting (Polar WRF) model, the Unified Model (UM), and the European Centre for Medium-range Weather Forecasting (ECMWF) model. Initial results comparing model output at two U.S. Department of Energy Atmospheric Radiation Measurement (AMT) NSA sites, during the fall season in 2019 and 2022, show that the UM slightly outperforms the HRRR-AK in terms of accurately forecasting the presence of a low-level cloud layer (89% of the time). All models have a significant bias of 300 to 800 meters in forecasting cloud base height (lower than is observed); however, the UM and ECMWF models have the lowest biases. Finally, a case study for a particularly challenging April 2017 thin-cloud event is presented, wherein we compare the performance of four different bulk microphysical parameterization schemes using a higher-resolution large eddy simulation (LES) model, the WRF-LES. Initial results show that the Thompson scheme was the only one able to reproduce and sustain a substantial supercooled liquid layer, but it was unable to reproduce the transition from a deep, liquid-rich cloud to a thin layer with moderately and heavily rimed precipitation. This is the first step in linking simulated LES-scale riming processes with those parameterized at a coarser mesoscale model scale. This has important implications for forecasting low-level clouds in an operational environment, given the efficiency of the riming process.

cloud base heights↗