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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Data Quality Assessment Methods for the Eastern Range 915 MHz Wind Profiler Network

The Eastern Range installed a network of five 915 MHz Doppler Radar Wind Profilers with Radio Acoustic Sounding Systems in the Cape Canaveral Air Station/Kennedy Space Center area to provide three-dimensional wind speed and direction and virtual temperature estimates in the boundary layer. The Applied Meteorology Unit, staffed by ENSCO, Inc., was tasked by the 45th Weather Squadron, the Spaceflight Meteorology Group, and the National Weather Service in Melbourne, Florida to investigate methods which will help forecasters assess profiler network data quality when developing forecasts and warnings for critical ground, launch and landing operations. Four routines were evaluated in this study: a consensus time period check a precipitation contamination check, a median filter, and the Weber-Wuertz (WW) algorithm. No routine was able to effectively flag suspect data when used by itself. Therefore, the routines were used in different combinations. An evaluation of all possible combinations revealed two that provided the best results. The precipitation contamination and consensus time routines were used in both combinations. The median filter or WW was used as the final routine in the combinations to flag all other suspect data points.

Lambert, Winifred C.↗
DOE OSTI2026

NLML: A Deep Neural Network Emulator for the Exact Nonlinear Interactions in a Wind Wave Model

Nonlinear wave interactions describe the resonant energy transfer between wave components, playing a fundamental role in the evolution of ocean wave spectra. Nonlinear wave interactions significantly influence wave growth and development, making them essential for accurate wave modeling. However, resolving the full six-dimensional Boltzmann integral of the exact nonlinear wave interactions (Webb-Resio-Tracy method, WRT) is computationally expensive, limiting its application in real-time operational wave forecasting and for research purposes. Current approximations, such as the Discrete Interaction Approximation (DIA), prioritize computational speed over accuracy, resulting in significant errors in wave mean parameters. Here, we introduce NLML, a machine learning (ML) emulator designed to approximate the exact nonlinear wave interactions within WAVEWATCH III (WW3), with the goal of achieving the accuracy of WRT while maintaining the stability and computational speed of DIA. By leveraging GPU capabilities such as half precision inference, we achieved substantial speedups, up to 136x mathematical equation faster than the WRT and only a modest 1.04x mathematical equation slowdown relative to DIA, while achieving 2x mathematical equation the accuracy of DIA in global wave spectral energy and mean wave parameters, with up to 7x mathematical equation higher accuracy in some regions. Unlike previous ML approaches, NLML maintained inherent stability throughout model integration in a standalone, year-long WW3 simulation, without requiring additional constraints. Our new ML parameterization bridges the gap between accuracy and efficiency, offering a promising alternative for improving wave modeling in operational settings and research purposes.

16 TIDAL AND WAVE POWER↗
NASA NTRS2003

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗
DOE OSTI2019

Investigation of observational error sources in multi-Doppler-radar three-dimensional variational vertical air motion retrievals

Abstract. Multi-Doppler-radar network observations have been used in different configurations over the last several decades to conduct three-dimensional wind retrievals in mesoscale convective systems. Here, the impacts of the selected radar volume coverage pattern (VCP), the sampling time for the VCP, the number of radars used, and the added value of advection correction on the retrieval of the vertical air motion in the upper part of convective clouds are examined using the Weather Research and Forecasting (WRF) model simulation, the Cloud Resolving Model Radar SIMulator (CR-SIM), and a three-dimensional variational multi-Doppler-radar retrieval technique. Comparisons between the model truth (i.e., WRF kinematic fields) and updraft properties (updraft fraction, updraft magnitude, and mass flux) retrieved from the CR-SIM-generated multi-Doppler-radar field are used to investigate these impacts. The findings are that (1) the VCP elevation strategy and sampling time have a significant effect on the retrieved updraft properties above 6  km in altitude; (2) 2  min or shorter VCPs have small impacts on the retrievals, and the errors are comparable to retrievals using a snapshot cloud field; (3) increasing the density of elevation angles in the VCP appears to be more effective to reduce the uncertainty than an addition of data from one more radar, if the VCP is performed in 2  min ; and (4) the use of dense elevation angles combined with an advection correction applied to the 2  min VCPs can effectively improve the updraft retrievals, but for longer VCP sampling periods (5  min ) the value of advection correction is challenging. This study highlights several limiting factors in the retrieval of upper-level vertical velocity from multi-Doppler-radar networks and suggests that the use of rapid-scan radars can substantially improve the quality of wind retrievals if conducted in a limited spatial domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

0BGRaman: Graph Network based Simulator for Forecasting Molecular Polarizability

This report presents the work performed under the GRaman project, sponsored by the PCSD LDRD Seed program. The project aimed at accelerating ab initio molecular dynamics simulation using Graph Networks. The Graph Network framework is a ML framework that has been successfully employed to simulate the dynamics of several physical systems: including water splashing in a container and flags moving with the wind. In this effort, we performed a data collection campaign for 3 different molecules of interest. We have built tools for preprocessing the trajectories obtained by simulating Raman Spectroscopy with NWChem and translating them into a suitable format for training. We have developed a training algorithm to train the Graph Network based simulators based on our data and developed a simulator that produces trajectories in the same NWChem format. While the tool has improved with each iteration of development and subsequent experiments, the current state of the tool does not allow to directly incorporate the technology within the NWChem framework because the trajectories produced by the tool are not yet accurate enough. However, the technology has proved to have good potential and it is certainly worth further research and development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

HELIOSPHERIC PROPAGATION OF CORONAL MASS EJECTIONS: COMPARISON OF NUMERICAL WSA-ENLIL+CONE MODEL AND ANALYTICAL DRAG-BASED MODEL

Real-time forecasting of the arrival of coronal mass ejections (CMEs) at Earth, based on remote solar observations, is one of the central issues of space-weather research. In this paper, we compare arrival-time predictions calculated applying the numerical ''WSA-ENLIL+Cone model'' and the analytical ''drag-based model'' (DBM). Both models use coronagraphic observations of CMEs as input data, thus providing an early space-weather forecast two to four days before the arrival of the disturbance at the Earth, depending on the CME speed. It is shown that both methods give very similar results if the drag parameter Γ = 0.1 is used in DBM in combination with a background solar-wind speed of w = 400 km s{sup –1}. For this combination, the mean value of the difference between arrival times calculated by ENLIL and DBM is Δ-bar =0.09±9.0 hr with an average of the absolute-value differences of |Δ|-bar =7.1 hr. Comparing the observed arrivals (O) with the calculated ones (C) for ENLIL gives O – C = –0.3 ± 16.9 hr and, analogously, O – C = +1.1 ± 19.1 hr for DBM. Applying Γ = 0.2 with w = 450 km s{sup –1} in DBM, one finds O – C = –1.7 ± 18.3 hr, with an average of the absolute-value differences of 14.8 hr, which is similar to that for ENLIL, 14.1 hr. Finally, we demonstrate that the prediction accuracy significantly degrades with increasing solar activity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Convective Radio Occultations Final Campaign Summary

Deep convective systems are destructive weather phenomena that annually cause many deaths and injuries as well as much damage, thereby accounting for major economic losses in several countries. The number and intensity of such phenomena have increased over the last decades in some areas of the globe. Damage is mostly caused by strong winds and heavy rain parameters that are strongly connected to the structure of the particular storm. Convection over land is usually stronger and deeper than over the ocean and some convective systems, known as supercells, also develop tornadoes through processes that remain mostly unclear. The intensity forecast and monitoring of convective systems is one of the major challenges for meteorology because in situ measurements during extreme events are too sparse or unreliable and most ongoing satellite missions do not provide suitable time/space coverage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Improving Momentum Transport Processes in E3SM (Final Progress Report)

This proposal aims to improve the representation of subgrid-scale momentum transport processes and reduce biases in surface wind stresses and precipitation patterns in E3SM by improving the parameterization of convective momentum transport within the deep convection scheme, and (b) improving the representation of the quasi-biennial oscillation (QBO) by modifying the source spectrum parameterization of convectively generated gravity waves. Weather Research and Forecasting (WRF) model simulations will be used to verify the momentum transport parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Towards retrieving cloud top entrainment velocities from MISR cloud motion vectors

Although important, direct retrievals of entrainment rates in cloud-topped planetary boundary layer (PBL) remain elusive. Here we present a novel technique for retrieving cloud-top entrainment velocities using only Multi-angle Imaging Spectro-Radiometer (MISR) stereoscopic retrievals of cloud-motion vectors (CMVs) and cloud-top heights (CTHs). Mesoscale vertical air velocity at CTH is diagnosed from the continuity equation and then used to derive entrainment velocities from the PBL mass-budget equation. The algorithm is demonstrated through a case of marine stratocumulus deck off the California coast, with comparisons made against data from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis (ERA5) and the data from other satellites. MISR low-cloud CTH for this case were lower than the ERA5 reported PBL depth by 189 ± 87 m. These differences in cloud top heights partly modulate the differences in the ERA5 and MISR horizontal winds, with larger differences in meridional over zonal wind components. Average difference between ERA5 and MISR derived mesoscale vertical air motion at cloud top was 0.14 ± 0.73 cm s −1 , while the same for entrainment rate was −0.09 ± 0.46 cm s −1 . The uncertainties in the utilized CTHs and CMVs are propagated to derive systematic and random retrieval uncertainties. Fractional uncertainty is lower than 25 % when the retrieved mesoscale vertical air motion is stronger than ±0.04 cm s −1 and entrainment velocities are stronger than ±0.03 cm s −1 . These results showcase the ability to derive mesoscale vertical air motion and entrainment rates from MISR observations and motivate its extension to generate a global climatology leveraging its full 23-year record (2000–2022). Nonetheless comprehensive validation of the retrievals is warranted through comparisons with estimates from an independent dataset across diverse weather conditions.

Mitra, Arka [Argonne National Laboratory (ANL), Ar↗
NASA NTRS1976

Seasat-A oceanographic data system and users

The Seasat-A system is reviewed with emphasis on data retrieval, processing and dissemination plans. Attention is paid to the sensors of the Seasat satellite including the compressed pulse radar altimeter, the coherent synthetic aperture imaging radar, the microwave wind scatterometer, and the scanning visible/infrared radiometer. Particular emphasis is placed on a particular set of experiments: the Navy's Fleet Numerical Weather Control will receive Seasat data in real time and process the data into products that will be used in weather and sea condition forecasts.

Mccandless, S. W., Jr.↗
NASA NTRS1979

Numerical prediction experiments simulating the impact of mesoscale satellite data

Recent developments in mesometeorology are summarized to place this research in perspective. Recent advances in computer analysis and forecast system development that provide the basis for the simulation tests are discussed. The impact of NIMBUS-6 humidity data on analyses off the West Coast are shown and incorporation of geopotential gradient data is discussed. Experiments to demonstrate the feasibility of incorporating satellite-derived wind fields in mesoscale severe storm models are mentioned briefly.

Kreitzberg, C. W.↗
NASA NTRS1985

The Contrasting Northern Hemisphere Winters of 1980-81 and 1981-82

Seasonal statistics calculated from daily operational analyses by the European Center for Medium Range Weather Forecasts for December 1980 to February 1981 (season 1) and December 1981 to February 1982 (season 2) were used to contrast the two seasonal mean circulation patterns present in the Northern Hemisphere and to investigate possible causes for the differences. The vertically averaged seasonal mean zonal wind and E-vector, a measure of the anisotropy of the transient eddies over the Pacific is shown for season 1 and season 2. The pattern in season 2, but not season 1, resembles that found in a modeling study of barotropic instability. One possible explanation for the differences between season 1 and 2 is a weak change in tropical heating associated with the southern oscillation, the effect of which in midlatitude was amplified by the occurrence of barotropic instability over the Pacific in season 2, but not season 1.

White, G. H.↗
NASA NTRS1986

Vertical structure of the wind field during the Special Observing Period I of the Global Weather Experiment

The vertical structure of the global atmosphere is analyzed for selected periods of the Special Observing Period I (SOP-I) for the Global Weather Experiment (GWE). The analysis consists of projection of the stream-function and velocity potential at 200 and 850 mb on spherical harmonics and of the wind and height fields on the normal modes of a linearized form of the primitive equations for a basic state at rest. The kinematic vertical structure is discussed in terms of correlation coefficients of the 200 mb and 850 mb winds and analysis of the internal and external normal modes of the primitive equations. The reliability of the results is checked by applying the same analysis methods to data sets obtained from three different institutions: Geophysical Fluid Dynamics Laboratory (GFDL), European Center for Medium Range Weather Forecasting (ECMWF), and Goddard Laboratory for the Atmospheres (GLA). It is found that, on a global basis, vertically reversing circulations are as important as the equivalent barotropic structures. For the verticaly reversing components, the gravity and mixed Rossby-gravity modes have contributions of the same order of magnitude as those of the Rossby modes in tropical latitudes.

Paegle, J. N.↗
NASA NTRS2009

Spinoff 2009

Topics covered include: Image-Capture Devices Extend Medicine's Reach; Medical Devices Assess, Treat Balance Disorders; NASA Bioreactors Advance Disease Treatments; Robotics Algorithms Provide Nutritional Guidelines; "Anti-Gravity" Treadmills Speed Rehabilitation; Crew Management Processes Revitalize Patient Care; Hubble Systems Optimize Hospital Schedules; Web-based Programs Assess Cognitive Fitness; Electrolyte Concentrates Treat Dehydration; Tools Lighten Designs, Maintain Structural Integrity; Insulating Foams Save Money, Increase Safety; Polyimide Resins Resist Extreme Temperatures; Sensors Locate Radio Interference; Surface Operations Systems Improve Airport Efficiency; Nontoxic Resins Advance Aerospace Manufacturing; Sensors Provide Early Warning of Biological Threats; Robot Saves Soldier's Lives Overseas (MarcBot); Apollo-Era Life Raft Saves Hundreds of Sailors; Circuits Enhance Scientific Instruments and Safety Devices; Tough Textiles Protect Payloads and Public Safety Officers; Forecasting Tools Point to Fishing Hotspots; Air Purifiers Eliminate Pathogens, Preserve Food; Fabrics Protect Sensitive Skin from UV Rays; Phase Change Fabrics Control Temperature; Tiny Devices Project Sharp, Colorful Images; Star-Mapping Tools Enable Tracking of Endangered Animals; Nanofiber Filters Eliminate Contaminants; Modeling Innovations Advance Wind Energy Industry; Thermal Insulation Strips Conserve Energy; Satellite Respondent Buoys Identify Ocean Debris; Mobile Instruments Measure Atmospheric Pollutants; Cloud Imagers Offer New Details on Earth's Health; Antennas Lower Cost of Satellite Access; Feature Detection Systems Enhance Satellite Imagery; Chlorophyll Meters Aid Plant Nutrient Management; Telemetry Boards Interpret Rocket, Airplane Engine Data; Programs Automate Complex Operations Monitoring; Software Tools Streamline Project Management; Modeling Languages Refine Vehicle Design; Radio Relays Improve Wireless Products; Advanced Sensors Boost Optical Communication, Imaging; Tensile Fabrics Enhance Architecture Around the World; Robust Light Filters Support Powerful Imaging Devices; Thermoelectric Devices Cool, Power Electronics; Innovative Tools Advance Revolutionary Weld Technique; Methods Reduce Cost, Enhance Quality of Nanotubes; Gauging Systems Monitor Cryogenic Liquids; Voltage Sensors Monitor Harmful Static; and Compact Instruments Measure Heat Potential.

Source record↗
NASA NTRS2014

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-14

Ms. Crawford completed the final report for the dual-Doppler wind field task. Dr. Bauman completed transitioning the 915-MHz and 50-MHz Doppler Radar Wind Profiler (DRWP) splicing algorithm developed at Marshall Space Flight Center (MSFC) into the AMU Upper Winds Tool. Dr. Watson completed work to assimilate data into model configurations for Wallops Flight Facility (WFF) and Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Ms. Shafer began evaluating the a local high-resolution model she had set up previously for its ability to forecast weather elements that affect launches at KSC/CCAFS. Dr. Watson began a task to optimize the data-assimilated model she just developed to run in real time.

Applied Meteorology Unit↗
NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗
DOE OSTI2025

Hybrid Power Plants for Energy Resilience: A Case Study

As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.

17 WIND ENERGY↗
DOE OSTI2019

Investigating land surface effects on the moisture transport over South America with a moisture tagging model

Land-atmosphere interactions are a critical component of precipitation processes within the Amazon and the La Plata river basins (LPRB) in South America. The possible pathways through which the land surface can affect precipitation are: 1) by changing the amount of moisture available for precipitation (moisture recycling) and 2) by changing the atmospheric thermal structure and consequently affecting circulation patterns. In this study, the Weather Research and Forecasting (WRF) model with embedded water vapor tracers (WVT) is used to disentangle these relative contributions. Using WRF-WVT we track the moisture that originates from the Amazon basin over a 10-year period. It is estimated that Amazon evapotranspiration (ET) contributes to around 30% of the total precipitation over the Amazon and around 20% over the LPRB. Analyzing moisture transport from the Amazon to the LPRB, it is found that warm (cool) surface air temperature over the northwestern Argentine is linked to low level winds and likely to induce northerly (southerly) winds that intensify (weaken) moisture transport by changing continental-scale circulation patterns.

Yang, Zhao↗