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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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NASA NTRS2001

Model of Wave Driven Flow Oscillation for Solar Cycle

At low latitudes in the Earth's atmosphere, the observed zonal flow velocities are dominated by the semi-annual and quasi-biennial oscillations with periods of 6 months and 20 to 32 months respectively. These terrestrial oscillations, the SAO and QBO respectively, are driven by wave-mean flow interactions due to upward propagating planetary-scale waves (periods of days) and small-scale gravity waves (periods of hours). We are proposing (see also Mayr et al., GRL, 2001) that such a mechanism may drive long period oscillations (reversing flows) in stellar and planetary interiors, and we apply it to the Sun. The reversing flows would occur below the convective envelope where waves can propagate. We apply a simplified, one dimensional, analytical flow model that incorporates a gravity wave parameterization due to Hines (1997). Based on this analysis, our estimates show that relatively small wave amplitudes less than 10 m/s can produce zonal flow amplitudes of 20 m/s, which should be sufficient to generate the observed variations in the magnetic field. To produce the 22-year period of oscillation, a low buoyancy frequency must be chosen, and this places the proposed flow in a region that is close to (and below) the base of the convective envelope. Enhanced turbulence associated with this low stability should help to generate the dynamo currents. With larger stability at deeper levels in the solar interior, the model can readily produce also oscillations with much longer periods. To provide an understanding of the fluid dynamics involved, we present numerical results from a 2D model for the terrestrial atmosphere that exemplify the non-linear nature of the wave interaction for which a mechanical analog is the escapement mechanism of the clock.

Mayr, Hans G.↗
NASA NTRS1982

A parameterized model for global insolation under partially cloudy skies

A simple and efficient parameterization of insolation under partially cloudy skies is discussed and compared with a set of exact radiative transfer results for clear skies, an empirical equation and observations. The parameterization is physically based and requires, as input variables, the ozone path length, precipitable water, Angstrom turbidity, surface air pressure and albedo, fractional cloud-cover and cloud thickness. Multiple reflection between the surface and the overlying atmosphere, and clouds are considered. The albedo of the earth-atmosphere system is also formulated and compared with a set of exact radiative transfer results. As compared to the exact radiative transfer results, the errors in the insolations are generally less than 1 percent, and in the albedo of the earth-atmosphere system less than 10 percent. The errors in the calculated insolations using climatological data are 2-3 percent when compared with many years averaged observations at Maudheim (Antarctica) and at Rockville (U.S.A.). A parametric equation for calculating directly the daily total insolation is also given.

Choudhury, B.↗
NASA NTRS1992

Parameterization of surface heat fluxes above a forest with satellite thermal sensing

The authors discuss the feasibility of determining the surface flux of sensible heat from forests with surface temperatures measured by satellites together with temperature soundings in the unstable atmospheric boundary layer (ABL). The latent heat flux is derived from the sensible heat flux by means of the energy budget. The study makes use of data collected during HAPEX-MOBILHY (Hydrologic Atmospheric Pilot Experiment-Modelization du Bilan Hydrique). The methodology is based on turbulence similarity for the unstable ABL. The surface temperature data were derived from measurements by the advanced very high resolution radiometer (AVHRR) aboard the NOAA-9 satellite; the atmospheric profiles were obtained by radiosondes.

Brutsaert, Wilfried↗
DOE OSTI2024

Linear Time-Invariant Models of a Large Cumulus Ensemble

Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.

Meteorology & Atmospheric Sciences↗
NASA NTRS1976

A study of some effects of vertical shear on thunderstorms

Evidence is presented for the existence of vortices and vortex pairs in thunderstorms. A preliminary parameterized model of the nonthermal generation of thunderstorm vortices derived from field observations of storms and laboratory observations of a jet in crossflow is reported, together with an explanation of how such a model might be used to guide analysis of mesoscale rawinsonde, radar, and satellite data toward an improved capability for prediction of thunderstorm motion and growth. Preliminary analyses of radar and satellite data from Atmospheric Variability Experiment IV are used with available rawinsonde data to develop a correlation between wind shears, instability, and thunderstorm motion and development. Specific studies are recommended for best development of concepts and utilization of data from Atmospheric Variability and Atmospheric Variability Severe Storms Experiments.

Connell, J.↗
NASA NTRS1995

A mesoscale modeling study of the atmospheric circulation of high southern latitudes

The meteorology of high southern latitudes during winter is simulated using a cloud-free version of The Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model version 4 (MM4) with a 100-km horizontal resolution. Comparisons between idealized simulations of Antarctic with MM4 and with the mesoscale model of Parish and Waight reveal that both models produce similarly realistic velocity fields in the boundary layer. The latter model tends to produce slightly faster drainage winds over East Antarctica. The intensity of the katabatic winds produced by MM4 is sensitive to parameterizations of boundary layer fluxes. Two simulations performed with MM4 using analyses from the European Center for Medium-Range Weather Forecasts (ECMWF) for June 1988 as initial and boundary conditions. A simulation of the period from 000 UTC 2 June to 0000 UTC 8 June produces realistic synoptic phenomena including ridge development over East Antarctica, frontogenesis over the Amundsen Sea, and a katabatic surge over the Ross Ice Shelf. The simulated time-averaged fields for June 1988, particularly that of a 500-hPa height, are in good agreement with time-averaged fields analyzed by the ECMWF. The results of the simulations provide detailed features of the Antarctic winter boundary layer along the steeply sloping terrain. Highest boundary layer wind speeds averaged over the month-long simulation are approximately 20 m/s. The lack of latent heating in the simulations apparently results in some bias in the results. In particular, the cloud-free version of MM4 underpredicts the intensity of lows in the sea level pressure field.

Hines, K. M.↗
NASA NTRS1982

Cloud/climate sensitivity experiments

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Roads, J. O.↗
DOE OSTI2023

QES-Plume v1.0: a Lagrangian dispersion model

Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

58 GEOSCIENCES↗
NASA NTRS1989

Interactions among radiation, convection, and large-scale dynamics in a general circulation model

The effects of radiatively active clouds on the climate simulated by a GCM are studied, focusing on the effects of upper tropospheric stratiform clouds associated with deep cumulus convection and the interactions of these clouds with convection and the large-scale circulation. The isolated effects of atmospheric cloud radiative forcing are analyzed using a model climate of an ocean-covered earth. It is found that the upper tropospheric cloudiness associated with cumulus convection has a powerful influence on both the convection and the large-scale circulation. Consideration is given to the importance of developing a GCM which includes a direct representation of the radiative, thermodynamical, and dynamical couplings between the convection parameterization and the large-scale saturation parameterization.

Randall, David A.↗
DOE OSTI2020

Statistically Steady State Large-Eddy Simulations Forced by an Idealized GCM: 1. Forcing Framework and Simulation Characteristics

Using large-eddy simulations (LES) systematically has the potential to inform parameterizations of subgrid-scale (SGS) processes in general circulation models (GCMs), such as turbulence, convection, and clouds. Here we show how LES can be run to emulate grid columns of GCMs to generate a library of LES across a cross-section of dynamical regimes. The LES setup replicates the thermodynamic and water budgets in GCM grid columns. Resolved horizontal and vertical transports of heat and water and large-scale pressure gradients from the GCM are prescribed as forcing in the LES. The LES satisfies the same (slab-ocean) surface boundary conditions as the GCM, leaving the LES temperatures free to adjust. Radiative transfer is treated in a unied but highly idealized manner (a semi-gray atmosphere without cloud radiative effects) in both the GCM and LES. We show that the LES with these forcing and boundary conditions reaches statistically steady states without nudging to reference profiles. These steady states provide a training dataset for developing GCM parameterizations. The same LES setup also provides a good basis for studying the cloud response to global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Slow Wake Recovery and Low Turbulence Behind Wind Farms Parameterized in Mesoscale Simulations

Numerical weather prediction (NWP) and climate models equipped with wind-farm parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates wake recovery behind a wind farm represented by the NWP-WFP approach in the Weather Research and Forecasting (WRF) model using either the Fitch et al. (2012) or Ma et al. (2022a, b) WFPs. Results are benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm with aligned and staggered layouts under neutral atmospheric stability. Near-farm wake recovery is underestimated in NWP-WFP simulations due to its representation on a coarse mesoscale grid. This limitation leads to slow wake recovery through two interconnected mechanisms: (i) spatial gradients in the wind velocity field are weaker compared to LES and (ii) turbulence kinetic energy (TKE) remains low not because of excessive dissipation but due to insufficient shear production caused by these weakened gradients. For the scenario considered here, a wind-speed bias develops in the near-farm wake and persists into the far wake. Differences between the NWP-WFP simulations and LES emerge within a short distance downstream of the farm exit, where the mesoscale simulations recover too slowly. This reduced recovery contributes approximately 0.15-0.50 m s-1 to the near-farm wind-speed bias. The bias established in this region is not subsequently compensated for downstream but instead propagates into the far wake, where wind-speed differences of approximately 0.4-0.6 m s-1 remain up to 50 km downstream. Higher-resolution mesoscale simulations partially reduce this bias. Increasing turbine-added TKE or including subgrid wake effects provides additional improvement, but neither fully addresses the underlying cause. The slow wake recovery is not caused by limitations of the WFPs themselves, as it also occurs outside their region of influence, and adding subgrid wake effects does not significantly impact recovery. Rather, the slow wake recovery is a consequence of mesoscale flow representation. This behavior is not limited to regions downstream of the wind farm but is less visible within the farm, where wake recovery occurs simultaneously with turbine-induced momentum extraction. These results highlight the need for improved representations of wake recovery both within and downstream of wind farms. While enhanced subgrid modeling, shear-driven TKE production, and refined WFP formulations may improve intra-farm dynamics, accurately capturing near-farm wake recovery downstream remains challenging, as WFPs do not act in this region.

17 WIND ENERGY↗
DOE OSTI2022

High-Resolution Wind Resource Data Set of the Greater Puerto Rico Region

In February 2022, the U.S. Department of Energy and six national laboratories launched the Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100). PR100 aims to provide a comprehensive analysis of possible pathways for Puerto Rico's energy future, with a goal of 100% renewable energy by 2050. As a part of the renewable energy potential assessment in this project, we developed 20 years (2001-2020) of data using a numerical weather prediction (NWP) model for onshore and offshore wind resource assessment for the Puerto Rico. The research steps in developing the long-term wind resource data sets based on the NWP model were: 1. Model wind resource based on the Weather Research and Forecasting (WRF) model. 2. Develop WRF model configurations for Puerto Rico. 3. Test WRF with 11 different physics parameterizations for planetary boundary layer (PBL). 4. Assess WRF output from the different PBL schemes against observations. 5. Select a final model configuration which can produce the modeled wind speed with sufficient accuracy. 6. Produce 20 years wind resource data sets for Puerto Rico region. In the first stage of our framework for developing wind resource data, we developed a WRF model configuration using two nested domains (9 km and 3 km) to cover Puerto Rico and U.S. Virgin Islands and downscale the ERA5 reanalysis data (0.25 degrees x 0.25 degrees; hourly interval) to a 3-km domain. For the second stage, we implemented one-year simulations focused on using 11 different PBL physics parameterizations to find a combination of WRF physics parameterizations that could provide accurately modeled wind speed for Puerto Rico. We also analyzed the sensitivity of the modeled wind speed to PBL schemes for onshore and offshore locations. The WRF output resulting from the 11 WRF experiments using different PBL parameterizations were evaluated against observations obtained from the National Data Buoy Center (NDBC) as well as at hub height for a location for which measurements were available. A final model setup selected through the validation with observational data was used to produce 20 years of data with 3-km spatial and 5-minute temporal resolution. The WRF model output was post-processed to include wind profiles and basic atmospheric variables in a format that can be easily used for downstream modeling. The 20 years of wind resource data will be made available through NREL and support the estimation of wind energy development costs for the PR100 study.

17 WIND ENERGY↗
NASA NTRS1998

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical "cores" of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. The two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical "simple physics" parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Hollingsworth, Jeffery L.↗
NASA NTRS1998

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical 'cores' of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. The two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical 'simple physics' parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Hollingsworth, Jeffery L.↗
NASA NTRS1998

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Cen- ter and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical "cores" of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. ne two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical "simple physics" parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Hollingsworth, Jeffery L.↗
DOE OSTI2021

INSIGHTS INTO MARINE UNICELLULAR CYANOBACTERIAL AND NON-CYANOBACTERIAL DIAZOTROPHS THROUGH SINGLE-CELL ANALYSES

Nutrient availability affects primary productivity, and nitrogen (N) is the limiting nutrient over large regions of the ocean. Biological N fixation (BNF) is the conversion of atmospheric dinitrogen (N2) to bioavailable forms of N (ammonium and amino acids). A select group of Bacteria and Archaea, known as diazotrophs, are the only organisms capable of this conversion. BNF is a critical source of N in nutrient-depleted (oligotrophic) marine waters. As such, BNF studies are a fundamental component for better understanding primary productivity and carbon cycling, as well as parameterizing predictive future global ocean models. Unicellular diazotrophs are widespread in marine systems and, in some cases, important contributors of BNF. This dissertation investigates unicellular diazotrophs at the single-cell level, including: UCYN-A, a cyanobacterial diazotroph that lives in symbiosis with an algal host, non-cyanobacterial diazotrophs (NCDs), which are putative heterotrophs, as well as a specific NCD known as Gamma A, a commonly occurring organism throughout the tropics and subtropics that belongs to the class Gammaproteobacteria. The single-cell investigations used in these studies can provide high-resolution insights that are not possible from community-level analyses of BNF, such as the N2 fixation rate of individual cells and cell morphology. Singlecell nanoscale secondary ion mass spectrometry (nanoSIMS) analyses were used in chapter 2 and 3 to investigate the cell-specific N2 fixation rates of (2) UCYN-A in the viii cold waters of the Bering and Arctic Seas where N2 fixation was not previously believed to be possible, and (3) NCDs in the North Pacific Subtropical Gyre where we demonstrated the first direct evidence of NCD N2 fixation on open ocean particles. Chapter 4 focused on the uncultivated NCD, Gamma A, using geneFISH to visualize single cells in natural seawater samples. We successfully identified Gamma A by developing a fluorescent in situ hybridization (FISH) probe targeting the diazotrophic functional marker gene nifH, revealing Gamma A cells are most often attached to particles. Together these studies provide new insights into the distributions, activities, and physiologies of geographically widespread, unicellular diazotrophs, thus improving our understanding of their roles as sources of fixed N in the surface ocean.

Harding, K.↗