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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CROCUS Weather Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements.Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Chicago State University Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at Chicago State University (CSU) at a prarie site on campus in Chicago, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (CSU), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Argonne National Laboratory Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a prairie field site at Argonne National Laboratory in Lemont, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (atmos), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at University of Illinois - Chicago Tower

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the University of Illinois in Chicago, Illinois, on the meteorological tower near the greenhouse on campus. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. File naming convention includes the project (CROCUS), location (UIC), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Northwestern University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
NASA NTRS2017

Direct Numerical Simulation of Hypersonic Turbulent Boundary Layer inside an Axisymmetric Nozzle

As a first step toward a study of acoustic disturbance field within a conventional, hypersonic wind tunnel, direct numerical simulations (DNS) of a Mach 6 turbulent boundary layer on the inner wall of a straight axisymmetric nozzle are conducted and the results are compared with those for a flat plate. The DNS results for a nozzle radius to boundary-layer thickness ratio of 5:5 show that the turbulence statistics of the nozzle-wall boundary layer are nearly unaffected by the transverse curvature of the nozzle wall. Before the acoustic waves emanating from different parts of the nozzle surface can interfere with each other and undergo reflections from adjacent portions of the nozzle surface, the rms pressure fluctuation beyond the boundary layer edge increases toward the nozzle axis, apparently due to a focusing effect inside the axisymmetric configuration. Spectral analysis of pressure fluctuations at both the wall and the freestream indicates a similar distribution of energy content for both the nozzle and the flat plate, with the peak of the premultiplied frequency spectrum at a frequency of [(omega)(delta)]/U(sub infinity) approximately 6.0 inside the free stream and at [(omega)(delta)]/U(sub infinity) approximately 2.0 along the wall. The present results provide the basis for follow-on simulations involving reverberation effects inside the nozzle.

Huang, Junji↗
NASA NTRS2015

Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

Beyon, Jeffrey Y.↗
NASA NTRS1975

Ionospheric direct measurement techniques

The most important physical parameters of the ionosphere which have been studied extensively over the years are: (1) the temperature, density, chemical composition, and directed motion (wind) of the ionized and neutral gas particles; and (2) the electric and magnetic fields. This review will discuss direct in situ techniques used on sounding rockets and satellites to measure these physical parameters. The techniques reviewed are restricted to those which are applicable to altitudes above about 100 km, where the mean free path is greater than the characteristic dimension of the instruments. Direct in situ instrumentation is defined as an experiment which measures the parameters in the immediate vicinity of the vehicle carrying the instrument; remote sensing techniques will not be discussed here.

Bauer, S. J.↗
NASA NTRS1988

Direct assessment of two-dimensional wind-tunnel interference from measurements on two interfaces

A direct assessment of two-dimensional wind-tunnel wall interference using upwash component measured on two interfaces has been formulated by the Prandtl-Glauert equation of the flow field and solved by the Fourier transform technique. The analytic formulae obtained for the interference of upwash and pressure on the model are presented. The formulae have been applied successfully to the analytic models for lifting and blockage interferences induced by the general linear slotted and perforated tunnel wall boundary conditions. The formulae have been derived in terms of Fourier coefficients of the measured upwash and illustrated its merits applying to a wavy-wall model case.

Lo, Ching F.↗
NASA NTRS1987

Modeling the interactions between the ocean and the environment for microwave radar sensing

An extensive set of X-band microwave backscatter measurements has been analyzed to determine its dependence on winds near the surface, atmospheric stability, and long-wave slopes. These radar measurements, made from a tower in the Gulf of Mexico, were performed in conjunction with an extensive set of simultaneous environmental measurements. The CW microwave system operated at an incidence angle of 45 deg, with antennas directed into winds and waves. Model functions for the radar cross section (RCS) and the modulation transfer function (MTF) are developed that depend on the geophysical variables, including wind stress. Statistical analysis shows that these models functions yield a significant smaller error when fit to the RCS data than a simple wind-speed function displays. A Taylor-series expansion of the returned power from a small area provides a unified function that demonstrates the complementary roles of wave slope and atmospheric fluctuations on both the RCS, the MTF, and the coherence. The issue of linearity of the MTF is addressed with this data set, yielding evidence that this is a valid assumption. These results have direct application to the remote sensing of the mean and fluctuating winds, and the wave spectrum with coherent and incoherent active radars.

Weissman, David E.↗
NASA NTRS1990

The Windvan pulsed CO2 Doppler lidar wide-area wind sensor

Wind sensing using a Doppler lidar is achieved by sensing the Doppler content of narrow frequency laser light backscattered by the ambient atmospheric aerosols. The derived radial wind components along several directions are used to generate wind vectors, typically using the Velocity Azimuth Display (VAD) method described below. Range resolved information is obtained by range gating the continuous scattered return. For a CO2 laser (10.6 mu) the Doppler velocity scaling factor is 188 kHz/ms(exp -1). In the VAD scan method the zenith angle of the pointing direction is fixed and its azimuth is continuously varied through 2 pi. A spatially uniform wind field at a particular altitude yields a sinusoidal variation of the radial component vs. azimuth. The amplitude, phase and dc component of this sinusoid yield the horizontal wind speed, direction and vertical component of the wind respectively. In a nonuniform wind field the Fourier components of the variation yields the required information.

Lawrence, Rhidian↗
DOE OSTI2021

A surrogate-model-based approach for estimating the first and second-order moments of offshore wind power

Power curve, the functional relationship that governs the process of converting a set of weather variables experienced by a wind turbine into electric power, is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input, thus ignoring the secondary, yet possibly significant effects of other environmental factors, (ii) they largely overlook the complex marine environment in which offshore turbines operate, potentially compromising their value in offshore wind energy applications, and (ii) they solely focus on the first-order properties of wind power, with little (or null) information about the variation around the mean behavior, which is important for ensuring reliable grid integration, asset health monitoring, and energy storage, among others. In light of that, this study investigates the impact of several wind-and wave-related factors on offshore wind power variability, with the ultimate goal of accurately predicting its first two moments. Further, our approach couples OpenFAST—a multi-physics wind turbine simulator—with Gaussian Process (GP) regression to reveal the underlying relationships governing offshore weather-to-power conversion. We first find that a multi-input power curve which captures the combined impact of wind speed, direction, and air density, can provide double-digit improvements, in terms of prediction accuracy, relative to univariate methods which rely on wind speed as the sole explanatory variable (e.g. the standard method of bins). Wave-related variables are found not important for predicting the average power output, but interestingly, appear to be extremely relevant in describing the fluctuation of the offshore power around its mean. Tested on real-world data collected at the New York/New Jersey bight, our proposed multi-input models demonstrate a high explanatory power in predicting the first two moments of offshore wind generation, testifying their potential value to the offshore wind industry.

17 WIND ENERGY↗
NASA NTRS1974

Satellite observations of type III solar radio bursts at low frequencies

Type III solar radio bursts have been observed from 10 MHz to 10 kHz by satellite experiments above the terrestrial plasmasphere. Solar radio emission in this frequency range results from excitation of the interplanetary plasma by energetic particles propagating outward along open field lines over distances from 5 earth radii to at least 1 AU from the sun. This review summarizes the morphology, characteristics, and analysis of individual as well as storms of bursts. Substantial evidence is available to show that the radio emission is observed at the second harmonic instead of the fundamental of the plasma frequency. This brings the density scale derived by radio observations into better agreement with direct solar wind density measurements at 1 AU and relaxes the requirement for type III propagation along large density-enhanced regions. This density scale with the measured direction of arrival of the radio burst allows the trajectory of the exciter path to be determined from 10 earth radii to 1 AU.

Fainberg, J.↗
NASA NTRS1975

A model of coronal holes

It has been noted that coronal holes appear to be associated with regions of diverging magnetic field in the corona. We set out to test the hypothesis that coronal holes may be caused by an increased flow of energy into the solar wind resulting directly from this diverging magnetic field pattern. Simple models were devised to approximate the energy flow down into the transition region and up into the solar wind as a function of the temperature, density, and rate of field line divergence in the corona. By assuming the rate of mechanical energy influx into the corona to be constant, it was then possible to solve numerically for the coronal temperature and density as a function of the rate of field line divergence. The results of these calculations demonstrate that a diverging field pattern can, indeed, bring about reductions in the temperature and density at the base of the corona comparable to those observed in coronal holes.

Adams, W. M.↗
NASA NTRS2016

Contributions of Solar Wind and Micrometeoroids to Molecular Hydrogen in the Lunar Exosphere

We investigate the density and spatial distribution of the H2 exosphere of the Moon assuming various source mechanisms. Owing to its low mass, escape is non-negligible for H2. For high-energy source mechanisms, a high percentage of the released molecules escape lunar gravity. Thus, the H2 spatial distribution for high-energy release processes reflects the spatial distribution of the source. For low energy release mechanisms, the escape rate decreases and the H2 redistributes itself predominantly to reflect a thermally accommodated exosphere. However, a small dependence on the spatial distribution of the source is superimposed on the thermally accommodated distribution in model simulations, where density is locally enhanced near regions of higher source rate. For an exosphere accommodated to the local surface temperature, a source rate of 2.2 g s-1 is required to produce a steady state density at high latitude of 1200 cm-3. Greater source rates are required to produce the same density for more energetic release mechanisms. Physical sputtering by solar wind and direct delivery of H2 through micrometeoroid bombardment can be ruled out as mechanisms for producing and liberating H2 into the lunar exosphere. Chemical sputtering by the solar wind is the most plausible as a source mechanism and would require 10-50 of the solar wind H+ inventory to be converted to H2 to account for the observations.

Impact↗
NASA NTRS1975

The ionosphere and upper atmosphere of Venus

A summary is presented of current understanding of the upper atmosphere and ionosphere of Venus and its interaction with the solar wind, based on data from the Mariner 5 and Mariner 10 fly-bys and on far UV spectra obtained in rocket experiments. The major constituent of the upper atmosphere is CO2. Minor constituents include H, He, O, C, and CO and probably N2, Cl, and S. Although the thermal escape rate is only about 10,000/sq cm/sec, the H content in the exosphere appears to be highly variable. A prominent peak in the ionosphere profile near 140 km, appearing both on the day and nightside, is identified as an F(1) layer. An E layer and possibly an F(2) layer are present at 125 and 170 km, respectively. The dayside ionosphere may be explained in terms of the absorption of solar radiation by CO2, O, and He. The transport of ions from day to nightside may be important in the formation of the nightside ionosphere; an additional source may be needed to explain the nightside E layer. There is observational evidence that the solar wind interacts directly with the Venusian atmosphere, resulting in the formation of a bow shock. This may in part be explained by a balance at the ionopause between the solar wind ram pressure and the planetary plasma pressure.

Kumar, S.↗