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At least 1,153 records · Page 64
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NASA NTRS2024

Anisotropy of Density Fluctuations in the Solar Wind at 1 au

A well-known property of solar wind plasma turbulence is the observed anisotropy of the autocorrelations, or equivalently the spectra, of velocity and magnetic field fluctuations. Here we explore the related but apparently not well-studied issue of the anisotropy of plasma density fluctuations in the energy-containing and inertial ranges of solar wind turbulence. Using 10 yr (1998–2008) of in situ data from the Advanced Composition Explorer mission, we find that for all but the fastest wind category, the density correlation scale is slightly larger in directions quasi-parallel to the large-scale mean magnetic field as compared to quasi-perpendicular directions. The correlation scale in fast wind is consistent with isotropic. The anisotropy as a function of the level of correlation is also explored. We find at small correlation levels, i.e., at energy-containing scales and larger, the density fluctuations are close to isotropy for fast wind, and slightly favor more rapid decorrelation in perpendicular directions for slow and medium winds. At relatively smaller (inertial range) scales where the correlation values are larger, the sense of anisotropy is reversed in all speed ranges, implying a more "slablike" structure, especially prominent in the fast wind samples. We contrast this finding with published results on velocity and magnetic field correlations.

Interplanetary turbulence↗
NASA NTRS2007

X-Band Radar for Studies of Tropical Storms from High Altitude UAV Platform

The increased role of unmanned aerial vehicles (UAV) in NASA's suborbital program has created a strong interest in the development of instruments with new capabilities, more compact sizes and reduced weights than the instruments currently operated on manned aircrafts. There is a strong demand and tremendous potential for using high altitude UAV (HUAV) to carry weather radars for measurements of reflectivity and wind fields from tropical storms. Tropical storm genesis frequently occurs in ocean regions that are inaccessible to piloted aircraft due to the long off shore range and the required periods of time to gather significant data. Important factors of interest for the study of hurricane genesis include surface winds, profiled winds, sea surface temperatures, precipitation, and boundary layer conditions. Current satellite precipitation and surface wind sensors have resolutions that are too large and revisit times that are too infrequent to study this problem. Furthermore, none of the spaceborne sensors measure winds within the storm itself. A dual beam X-band Doppler radar, UAV Radar (URAD), is under development at the NASA Goddard Space Flight Center for the study of tropical storms from HUAV platforms, such as a Global Hawk. X-band is the most desirable frequency for airborne weather radars since these can be built in a relatively compact size using off-the-shelf components which cost significantly less than other higher frequency radars. Furthermore, X-band radars provide good sensitivity with tolerable attenuation in storms. The low-cost and light-weight URAD will provide new capabilities for studying hurricane genesis by analyzing the vertical structure of tropical cyclones as well as 3D reflectivity and wind fields in clouds. It will enable us to measure both the 3D precipitation structure and surface winds by using two antenna beams: fixed nadir and conical scanning each produced by its associated subsystem. The nadir subsystem is a magnetron based radar modified from a marine radar transceiver. It is capable of measuring vertical reflectivity and velocity profile while being a lower-cost, smaller size, and lighter weight version of the NASA ER-2 Doppler Radar (EDOP), which has flown during many NASA field campaigns and has provided valuable scientific information on hurricanes and weather phenomena. Unfortunately, EDOP is too large and heavy for most UAV platforms, but the experience gained with this instrument provided us with the heritage to build a new low-cost, light-weight, smaller system that will be capable of flying on UAVs. The scanning subsystem uses a TWT transmitter and provides measurements of 3D reflectivity/wind fields in-clouds. Conical scanning of the radar beam at a 35 deg. incidence angle will also provide information of surface wind speed and direction derived from the surface return over a single 360 deg. sweep. URAD data system will be Linux based with the capability of autonomous operation. It will utilize cutting edge digital receiver and FPGA technologies to carry out the data acquisition and processing tasks. High speed navigation data from the aircraft will also be captured and saved along with radar data for 3D measurement field reconstruction and aircraft motion correction. There is a tremendous potential for UAVs to carry down-looking weather radars for measurements of reflectivity, horizontal and vertical winds from tropical storms. With operation from HUAV platforms, the dual beam X-band radar under development promises to provide greatly needed information for tropical storm research.

Rodriquez, Shannon↗
NASA NTRS2009

Development of a Compact, Pulsed, 2-Micron, Coherent-Detection, Doppler Wind Lidar Transceiver; and Plans for Flights on NASA's DC-8 and WB-57 Aircraft

We present results of a recently completed effort to design, fabricate, and demonstrate a compact lidar transceiver for coherent-detection lidar profiling of winds. The novel high-energy, 2-micron, Ho:Tm:LuLiF laser technology developed at NASA Langley was employed to permit study of the laser technology currently envisioned by NASA for global coherent Doppler lidar measurement of winds in the future. The 250 mJ, 10 Hz compact transceiver was also designed for future aircraft flight. Ground-based wind profiles made with this transceiver will be presented. NASA Langley is currently funded to build complete Doppler lidar systems using this transceiver for the DC-8 and WB-57 aircraft. The WB-57 flights will present a more severe environment and will require autonomous operation of the lidar system. The DC-8 lidar system is a likely component of future NASA hurricane research. It will include real-time data processing and display, as well as full data archiving. We will attempt to co-fly on both aircraft with a direct-detection Doppler wind lidar system being prepared by NASA Goddard Space Flight Center.

Kavaya, Michael J.↗
NASA NTRS1985

Magnetospheric impulse response for many levels of geomagnetic activity

The temporal relationship between the solar wind and magnetospheric activity has been studied using 34 intervals of high time resolution IMP 8 solar wind data and the corresponding AL auroral activity index. The median values of the AL index for each interval were utilized to rank the intervals according to geomagnetic activity level. The linear prediction filtering technique was then applied to model magnetospheric response as measured by the AL index to the solar wind input function VB(s). The linear prediction filtering routine produces a filter of time-lagged response coefficients which estimates the most general linear relationship between the chosen input and output parameters of the magnetospheric system. It is found that the filters are composed of two response pulses speaking at time lags of 20 and 60 min. The amplitude of the 60-min pulse is the larger for moderate activity levels, while the 20-min pulse is the larger for strong activity levels. A possible interpretation is that the 20-min pulse represents magnetospheric activity driven directly by solar wind coupling and that the 60-min pulse represents magnetospheric activity driven by the release of energy previously stored in the magnetotail. If this interpretation is correct, the linear filtering results suggest that both the driven and the unloading models of magnetospheric response are important facets of a more comprehensive response model.

Bargatze, L. F.↗
NASA NTRS1972

Methods of quantitative and qualitative analysis of bird migration with a tracking radar

Methods of analyzing bird migration by using tracking radar are discussed. The procedure for assessing the rate of bird passage is described. Three topics are presented concerning the grouping of nocturnal migrants, the velocity of migratory flight, and identification of species by radar echoes. The height and volume of migration under different weather conditions are examined. The methods for studying the directions of migration and the correlation between winds and the height and direction of migrating birds are presented.

Bruderer, B.↗
NASA NTRS1994

The 630 nm MIG and the vertical neutral wind in the low latitude nighttime thermosphere

It is shown that large negative divergences (gradients) in the horizontal neutral wind in the equatorial thermosphere can support downward neutral winds in excess of 20 m/s. With attention to the meridional and vertical winds only, the pressure tendency equation is used to derive the expression U(sub z0) approximately equals (Partial derivative U(sub y)/Partial derivative y)H for the vertical wind U(sub z0) at the reference altitude for the pressure tendency equation; H is the atmospheric density scale height, and (Partial derivative U(sub y)/Partial derivative y) is the meridional wind gradient. The velocity gradient associated with the Meridional Intensity Gradient (MIG) of the O((sup 1)D) emission (630 nm) at low latitudes is used to estimate the vertical neutral wind in the MIG region. Velocity gradients derived from MIG data are about 0.5 (m/s)/km) or more, indicating that the MIG region may contain downward neutral winds in excess of 20 m/s. Though direct measurements of the vertical wind are scarce, Fabry-Perot interferometer data of the equatorial F-region above Natal, Brazil, showed downward winds of 30 m/s occurring during a strong meridional wind convergence in 1982. In-situ measurements with the WATS instrument on the DE-2 satellite also show large vertical neutral winds in the equatorial region.

Herrero, F. A.↗
NASA NTRS1983

Wind Engineering

Dr. Jack Cermak, Director of Fluid Dynamics and Diffusion Laboratory, developed the first wind tunnel to simulate the changing temperatures, directions and velocities of natural winds. In this work, Cermak benefited from NASA technology related to what is known as the atmospheric boundary layer (ABL).

Source record↗
NASA NTRS2010

Statistical Short-Range Guidance for Peak Wind Forecasts on Kennedy Space Center/Cape Canaveral Air Force Station, Phase III

This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations.The tool includes climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗
NASA NTRS2008

A Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

This conference abstract describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violatioas.The tool will include climatologies of the 5-minute mean end peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗
NASA NTRS2007

Developing a Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station

This conference presentation describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations. The tool will include climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Lambert, WInifred↗
NASA NTRS2013

A Suzaku X-ray Observation of One Orbit of the Supergiant Fast X-ray Transient IGR J16479-4514

We report on a 250 ks long X-ray observation of the supergiant fast X-ray transient (SFXT) IGR J16479-4514 performed with Suzaku in 2012 February. During this observation, about 80% of the short orbital period (P(sub orb) approximates 3.32 days) was covered as continuously as possible for the first time. The source light curve displays variability of more than two orders of magnitude, starting with a very low emission state (10(exp −13) erg / sq cm/s; 1-10 keV) lasting the first 46 ks, consistent with being due to the X-ray eclipse by the supergiant companion. The transition to the uneclipsed X-ray emission is energy dependent. Outside the eclipse, the source spends most of the time at a level of 6-7X10)(exp−12) erg/sq. cm/s) punctuated by two structured faint flares with a duration of about 10 and 15 ks, respectively, reaching a peak flux of 3-4X10(exp −11) erg/sq. cm./S, separated by about 0.2 in orbital phase. Remarkably, the first faint flare occurs at a similar orbital phase of the bright flares previously observed in the system. This indicates the presence of a phase-locked large scale structure in the supergiant wind, driving a higher accretion rate onto the compact object. The average X-ray spectrum is hard and highly absorbed, with a column density, NH, of 10*exp 23)/sq cm, clearly in excess of the interstellar absorption. There is no evidence for variability of the absorbing column density, except that during the eclipse, where a less absorbed X-ray spectrum is observed. A narrow Fe K-alpha emission line at 6.4 keV is viewed along the whole orbit, with an intensity which correlates with the continuum emission above 7 keV. The scattered component visible during the X-ray eclipse allowed us to directly probe the wind density at the orbital separation, resulting in rho(sub w)=7X10(exp −14) g/cubic cm. Assuming a spherical geometry for the supergiant wind, the derived wind density translates into a ratio M(sub w)/v(sub infinity) = 7X10(exp −17) Solar M/km which, assuming terminal velocities in a large range 500-3000 km/s, implies an accretion luminosity two orders of magnitude higher than that observed. As a consequence, a mechanism should be at work reducing the mass accretion rate. Different possibilities are discussed.

J164794514↗
DOE OSTI2025

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1975

Direct observations of a flare related coronal and solar wind disturbance

Numerous mass ejections from the sun have been detected with orbiting coronagraphs. Here for the first time we document and discuss the direct association of a coronagraph observed mass ejection, which followed a 2B flare, with a large interplanetary shock wave disturbance observed at 1 AU. Estimates of the mass and energy content of the coronal disturbance are in reasonably good agreement with estimates of the mass and energy content of the solar wind disturbance at 1 AU. The energy estimates as well as the transit time of the disturbance are also in good agreement with numerical models of shock wave propagation in the solar wind.

Gosling, J. T.↗
NASA NTRS2000

SeaWinds on QuikSCAT Mission and Early Science Results

SeaWinds on QuikSCAT (QSCAT) is a dedicated satellite remote sensing mission for measuring ocean surface wind speed and direction, using a spinning, pencil-beam Ku-band scatterometer. It is a replacement mission for NASA Scatterometer (NSCAT), which was launched on board of the Japan's Advanced Earth Observation System (ADEOS-1) in August 1996 and returned 10 months of high quality data before the mission was terminated in June, 1997 due to the failure of the ADEOS-1 spacecraft. Since the next NASA scatterometer mission, SeaWinds on ADEOS-2 (SeaWinds), will not be launched until November 2000, NASA decided to fill the data gap by launching the QSCAT mission. Furthermore, after year 2000. the potential exists for using both the QSCAT and SeaWinds to provide approximately 6 hours global coverage of the marine winds. QSCAT is currently scheduled for launch in April, 1999 from Vandenberg Air Force Base, using Titan-II launch vehicle. The purpose of this paper is to first present the mission objectives, the spacecraft and instrument design, ground receiving systems, the science data processing system, and the data products. We will then present the post-launch calibration and verification results of the QSCAT end-to-end sensor system. Finally, we present some of the key results obtained from the first two months of the mission, which include ocean surface wind measurements, ice detection and classification, global snow cover detection, and flood detection.

Tsai, Wu-Yang↗
NASA NTRS2008

MESSENGER: Exploring Mercury's Magnetosphere

The MESSENGER mission to Mercury offers our first opportunity to explore this planet's miniature magnetosphere since Mariner 10's brief fly-bys in 1974-5. Mercury's magnetosphere is unique in many respects. The magnetosphere of Mercury is the smallest in the solar system with its magnetic field typically standing off the solar wind only - 1000 to 2000 km above the surface. For this reason there are no closed dri-fi paths for energetic particles and, hence, no radiation belts; the characteristic time scales for wave propagation and convective transport are short possibly coupling kinetic and fluid modes; magnetic reconnection at the dayside magnetopause may erode the subsolar magnetosphere allowing solar wind ions to directly impact the dayside regolith; inductive currents in Mercury's interior should act to modify the solar In addition, Mercury's magnetosphere is the only one with its defining magnetic flux tubes rooted in a planetary regolith as opposed to an atmosphere with a conductive ionosphere. This lack of an ionosphere is thought to be the underlying reason for the brevity of the very intense, but short lived, approx. 1-2 min, substorm-like energetic particle events observed by Mariner 10 in Mercury's magnetic tail. In this seminar, we review what we think we know about Mercury's magnetosphere and describe the MESSENGER science team's strategy for obtaining answers to the outstanding science questions surrounding the interaction of the solar wind with Mercury and its small, but dynamic magnetosphere.

Slavin, James A.↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
DOE OSTI2025

NREL - GE 1.5MW SLE Wind Turbine / Reviewed Data

This dataset is intended to be a public resource for anyone conducting wind turbine noise research. It contains noise spectra and equivalent sound pressure levels at 11 measurement stations. The dataset also contains wind turbine operational data and meteorological data from a met mast directly upstream of the wind turbine.

17 WIND ENERGY↗