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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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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.↗
NASA NTRS1978

On the relationship of radar backscatter to wind speed and fetch

The physics of the interaction of electromagnetic waves with the ocean surface has been an active area of research for a number of years. This paper contains the results of satellite and aircraft experiments to investigate the ability of active microwave radars to infer surface wind speeds remotely. Data obtained from the recent National Aeronautics and Space Administration (NASA) Skylab experiment are compared with surface wind speeds measured by low-flying aircraft and ships-of-opportunity and found to give useful estimates of the ocean wind field. Also investigated was the influence of varying wave height on radar measurements of wind speed by measuring the backscattering cross-section for constant wind speed but variable wave conditions. It is found that this effect is of little importance.

Ross, D.↗
NASA NTRS1992

Retrieval of a wind profile from the Galileo Probe telemetry signal

The zonal wind speed profile within Jupiter's upper troposphere is to be estimated on the basis of its influence on the frequency of the Galileo Probe's telemetry signal; this is achieved by linearizing the relativistic Doppler shift equation about a state of zero wind speed, expanding the zonal wind series in a Legendre polynomial series, and reducing the resulting equations to a linear, least-squares problem. If the error sources have magnitudes not greater than those presently assumed, the retrieved wind speed profiles can place a key constraint on the basic drive for the atmospheric circulation, as well as anchoring winds derived from Galileo Orbiter images to well-defined vertical positions in the atmosphere.

Pollack, James B.↗
NASA NTRS2002

Sensitivity of Global Sea-Air CO2 Flux to Gas Transfer Algorithms, Climatological Wind Speeds, and Variability of Sea Surface Temperature and Salinity

Sensitivity analyses of sea-air CO2 flux to gas transfer algorithms, climatological wind speeds, sea surface temperatures (SST) and salinity (SSS) were conducted for the global oceans and selected regional domains. Large uncertainties in the global sea-air flux estimates are identified due to different gas transfer algorithms, global climatological wind speeds, and seasonal SST and SSS data. The global sea-air flux ranges from -0.57 to -2.27 Gt/yr, depending on the combination of gas transfer algorithms and global climatological wind speeds used. Different combinations of SST and SSS global fields resulted in changes as large as 35% on the oceans global sea-air flux. An error as small as plus or minus 0.2 in SSS translates into a plus or minus 43% deviation on the mean global CO2 flux. This result emphasizes the need for highly accurate satellite SSS observations for the development of remote sensing sea-air flux algorithms.

McClain, Charles R.↗
NASA NTRS1976

A comparison of low-cloud satellite wind estimates with analyses based on aircraft observations in a disturbed tropical regime

Low-level, ATS-3 satellite wind estimates are compared with values of wind direction and speed interpolated from analyses based on research aircraft observations of a synoptic tropical wave of moderate intensity on 26 July 1969 during BOMEX. The data were stratified according to whether a satellite estimate was positioned in one of three regions; namely, east or west of the wave trough or north of the disturbance center. When cloud and analysis vector magnitude deviations were computed, regional differences became apparent. These differences are attributed to the physical behavior of the cloud targets tracked under the influence of the surrounding large-scale environment.

Smith, C. L.↗
NASA NTRS1986

The influence of velocity variability on the determination of wind profiles

High sensitivity radars allow the determination of velocity estimates at time resolutions down to one minute or better. Because of the variability introduced to the mean wind due to turbulence and waves, the high resolution profiles may not be too useful for forecasting applications, although they yield the most realistic estimate of the instantaneous wind profile. Profiles of wind speed and direction, vertical velocity and echo power, which were deduced in real-time on 23 August 1981 with the spaced antenna drift mode of the SOUSY-VHF-Radar are shown. Whereas these profiles were measured within 1 minute, the operating routine allowed the selection of variable (longer) measuring periods, and one has to search for the optimum duration of the data averaging period. A high time resolution wind vector diagram is given which gives an idea of the temporal variability. The data were obtained with the spaced antenna technique, which allows a good estimate of the horizontal wind without having to correct for the vertical velocity component. The wind vectors specifically indicate a quasi-periodic variation in direction. This is assumed to be due to gravity waves since the vertical velocity also shows periodical variations with the same period. The consistency of these spaced-antenna VHF radar results along with the radiosonde data convinced researchers that the method is quite suitable for wind profiling applications.

Rottger, J.↗
DOE OSTI2022

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗
NASA NTRS1989

Basic properties of developed wind waves and their influence on microwave remote sensing signatures

Error trends in wind speed measurements by satellite scatterometer altimeter and microwave radiometer are shown to be correlated with the degree of wave development. These errors are analyzed theoretically by studying the rms wave slope which, directly or indirectly, affects all microwave signatures. For equilibrium sea state, the influence of spectrum parameters on the wave slope is reviewed. In well-developed seas, the dominant wavelength is shown to have no effect on the slope. Temporal-spatial rates of steep and breaking waves are derived and compared with field observations. The inner scale that determines a rapid falloff of spectral density function at high frequencies is estimated. The dependence of the spectral parameters on wind speed and sea maturity is studied using NOAA buoy observations. It is concluded that the removal of environmental error trends from satellite measurements can be best accomplished by a joint processing of microwave returns from several independent instruments.

Glazman, Roman E.↗
NASA NTRS1994

Validation of ERS-1 environmental data products

Evaluation of the launch-version algorithms used by the European Space Agency (ESA) to derive wind field and ocean wave estimates from measurements of sensors aboard the European Remote Sensing satellite, ERS-1, has been accomplished through comparison of the derived parameters with coincident measurements made by 24 open ocean buoys maintained by the National Oceanic and Atmospheric Administration). During the period from November 1, 1991 through February 28, 1992, data bases with 577 and 485 pairs of coincident sensor/buoy wind and wave measurements were collected for the Active Microwave Instrument (AMI) and Radar Altimeter (RA) respectively. Based on these data, algorithm retrieval accuracy is estimated to be plus or minus 4 m/s for AMI wind speed, plus or minus 3 m/s for RA wind speed and plus or minus 0.6 m for RA wave height. After removing 180 degree ambiguity errors, the AMI wind direction retrieval accuracy was estimated at plus or minus 28 degrees. All of the ERS-1 wind and wave retrievals are relatively unbiased. These results should be viewed as interim since improved algorithms are under development. As final versions are implemented, additional assessments should be conducted to complete the validation.

Goodberlet, Mark A.↗
DOE OSTI2020

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗
DOE OSTI2022

The Role of Phytoplankton Biomacromolecules in Controlling Ocean Surface Roughness

Satellite altimetric data routinely map sea surface topography by measuring the ocean return signal. One source of altimeter measurement contamination occurs when the radar ocean backscatter becomes unusually large, a situation termed a Sigma-0 bloom. Past research suggests Sigma-0 blooms are associated with weak wind and natural surface slick conditions where capillary waves at the air–sea interface are suppressed. To date, no explicit connection between these conditions and Sigma-0 bloom presence has been provided. Using a series of simplified equations, our reduced model determines capillary wave heights from estimates of planktonic carbon concentrations and regional wind speed. Our results suggest that the radar signal reflection increases as capillary wave height decreases. This relationship depends on surfactant concentration, surfactant composition, and wind speed. Model sensitivity analysis indicates that the interface reflectivity depends on biological activity and wind speed. Our proposed simplified model provides a method to identify potential Sigma-0 bloom regions. We conclude that because of the demonstrated impact of biological surfactants on ocean roughness, it is necessary to consider the biological activity, i.e., phytoplankton bloom events, when interpreting signals from radar altimetry and when developing ocean hydrology models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Urban air pollution dispersion model

Three-dimensional integrated puff model simulates smoke plume dispersion processes and estimates pollutant concentration during periods of low wind speed. Applications for model are given.

Robert, J. J.↗
NASA NTRS1972

Atmospheric density variations related to internal gravity waves

Report describes method for estimating gravity-wave density variation from wind speed profile between 60 and 100 km. Single profile is inadequate for valid determination of mean or background values and ensemble averaging over several related profiles is recommended.

Miller, E. B.↗
NASA NTRS1980

Gulf stream ground truth project - Results of the NRL airborne sensors

Results of an airborne study of the waves in the Gulf Stream are presented. These results show that the active microwave sensors (high-flight radar and wind-wave radar) provide consistent and accurate estimates of significant wave height and surface wind speed, respectively. The correlation between the wave height measurements of the high-flight radar and a laser profilometer is excellent.

Mcclain, C. R.↗
NASA NTRS1981

Studies of Jupiter's lower ionospheric layers

Fluxes of heavy ions necessary to form layers of enhanced ionization observed in the lower ionosphere of Jupiter are theoretically calculated, and possible formation mechanisms of the layers are investigated. Estimates of ion drift velocities and neutral wind speeds are made from the shape of the ionization layers, and are found to range from a few centimeters per second to meters per second. Zonal wind shear ranges from 50 m/s westward to 200 m/s eastward over a 70 km altitude range, while small meridional winds are sufficient to form the layer. Results indicate that if the layers are formed from sodium or sulfur ions from the Galilean satellite which are injected into the Jovian atmosphere, then the Na(+) flux must be 30,000 sq cm/s, and the S(+) flux must be 4000 sq cm/s in order to correlate with Pioneer 10 observations of the L(6) layer. At low altitudes of the L(6) and L(7) layers, the denser atmosphere makes diffusion very slow, and the vertical drift velocity of 1 cm/s requires a zonal wind of only several centimeters per second to drive it.

Chen, R. H.↗
NASA NTRS1999

Estimating the Effects of Sensor Spacing on Peak Wind Measurements at Launch Complex 39

This paper presents results of an empirical study to estimate the measurement error in the peak wind speed at Shuttle Launch Complex 39 (LC-39) which results from the measurement being made by sensors 1,300 feet away. Quality controlled data taken at a height of 30 feet from an array of sensors at the Shuttle Landing Facility (SLF) were used to model differences of peak winds as a function of separation distance and time interval. The SLF data covered wind speeds from less than ten to more than 25 knots. Winds measured at the standard LC-39 site at the normal height of 60 feet were used to verify the applicability of the model to the LC-39 situation. The error in the peak wind speed resulting from separation of the sensor from the target site obeys a power law as a function of separation distance and varies linearly with mean wind speed. At large separation distances, the error becomes a constant fraction of the mean wind speed as the separation function reaches an asymptotic value. The asymptotic average of the mean of the absolute difference in the peak wind speed between the two locations is about twelve percent of the mean wind speed. The distribution of the normalized absolute differences is half-Gaussian.

Merceret, Francis J.↗
NASA NTRS2019

Characterization of the land surface freeze/thaw state with SMAP-Reflectometry (SMAP-R)

The use of the Soil Moisture Active Passive (SMAP) radar in received mode has allowed for a new dataset of Global Navigation Satellite System – Reflectometry (GNSS-R) measurements. GNSS-R techniques have been used for more than two decades and have proven successful perform altimetry studies and to retrieve ocean wind speed and soil moisture, monitor wetland dynamics, estimate snow depth, detect sea ice and determine sea ice types. In this paper, the SMAP-Reflectometry measurements are used to classify freeze/thaw (F/T) state over Alaska, studying the differences in the SNR signal at both V and H polarizations.

Podest, Erika↗
DOE OSTI2023

Reducing Uncertainty in Offshore Wind Energy Yield Estimates via a Metocean Reference Site

The offshore wind industry is burgeoning in the coastal waters of the United States, specifically along the Atlantic. For wind energy to be successful, reliable observations and model simulations are needed for resource assessment and forecasting. While many of these activities have already begun, there is currently an absence of observations at hub-height in these waters, with the closest available hub-height measurements usually taken onshore. Deployment of floating lidars has occurred through various federally funded projects, but only encapsulates time periods of a couple of years at best. Private industry is also beginning to leverage floating lidars, but this data is often proprietary, and not shared with the general public. In this work, we make the case for a metocean reference site for long-term offshore wind energy. Specifically, we quantify the impact of having a metocean reference site compared to other methods of determining hub-height winds and energy production. We use an offshore floating lidar to directly measure the wind resource, and compare these measurements to predictions derived from other widely-available surface meteorological variables. These prediction methods (vertical extrapolation, machine learning, and NWP output) produce a variety of vertical wind speed profiles, of which produce different energy yield estimates for a reference offshore turbine (Figure 1). While some methods perform reasonably well against the lidar, the uncertainty in these energy yield estimates has financial implications, further illustrating the need for long-term measurements in coastal waters.

machine learning↗