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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

The importance of the curvature of the wind profile in determining regions of CAT and non-CAT

An investigation is conducted regarding the relationship between CAT and the curvature of the wind profile, taking into account cases of CAT encountered by the XB-70 in the stratosphere over the mountainous terrain of the western U.S. The results of the investigation show that the curvature of the wind profile is an important tropospheric variable in the determination of stratospheric CAT regions. These CAT regions are likely to occur in cases in which the curvature increases with height in the troposphere in areas when mountain waves are expected.

Possiel, N.↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Nantucket (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Nantucket dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗
NASA NTRS1976

Curvature of the wind profile in the troposphere versus regions of CAT and non-CAT in the stratosphere

A discussion of the theoretical importance of the curvature of the wind profile to the amplitude of mountain waves is presented. Mechanisms favorable for clear air turbulence (CAT) are discussed in relation to such wave motions. It is shown that CAT encountered by the XB-70 aircraft in the stratosphere during expected mountain-wave conditions is related to the vertical gradient of curvature of the wind profile in the troposphere. Results indicate that 89% of the turbulent regions in the stratosphere occurred in expected mountain-wave areas and that 79% were located where the vertical gradient of curvature was positive in the 10-30,000 ft layer below. For the nonturbulent regions, 74% were outside expected mountain-wave areas and 98% of these occurred where the vertical gradient of curvature was negative. All the nonturbulent regions within expected mountain-wave areas occurred where the vertical gradient of curvature was negative.

Possiel, N.↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Block Island (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Block Island dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗
NASA NTRS1984

Potential advantages of the spaced antenna method for operational wind profiling, part 3.1B

The problem of very short-range forecasting is twofold. It is necessary to understand the processes that are being forecasted, and data appropriate to the scale of interest has to be generated. Coherent VHF and UHF radars are being used for operational wind profiling and are providing part of the solution to the data-acquisition problem. The Profiler system operated by the Wave Propagation Laboratory at NOAA has already shown great promise. As a result, plans are being considred for expanding the network of radars to cover a larger area of the country. The Profiler uses what is commonly referred to as the Doppler method for measuring winds. Two beams are pointed off-vertical, and the Doppler shift of the echo determines the line-of-sight velocity. The velocity components along the beams are then translated to horizontal wind components. A number of possible advantages of the spaced antennas (SA) method for operational wind profiling are discussed.

Rottger, J.↗
NASA NTRS1978

Wind profiles for Space Shuttle loads analysis

The small scale wind velocity perturbations in vertical wind profiles at Cape Kennedy, Florida were analyzed in order to derive information for simulations of space shuttle ascent through the perturbed atmosphere. The available statistical data does not permit specification of various aspects of idealized singularities and wavelike perturbations with a reasonable degree of confidence. The information developed as a result of the analysis described in Section 3 of this report is suitable for the further development of idealized models. The term perturbation is used instead of the more common term, gust. According to the conventional approach, a gust profile is calculated by applying a high pass digital filter to a Jimsphere profile; all the speeds in the filtered profile are defined as gusts. The high pass filtered profile is defined as a residual profile and the maximum residual in the vicinity of a specified reference height is defined as the gust. Gusts defined in this manner represent the perturbation peaks. A detailed discussion of the calculation of residual profiles and gusts is given. The meteorological coordinate system, the data sample, and Jimsphere profiles are also described. Recommendations and conclusions are presented.

Adelfang, S. I.↗
NASA NTRS2003

Observing System Simulation Experiments to Determine the Potential Impact of Space-Based Lidar Wind Profiles on Weather Prediction

Observing system simulation experiments (OSSE's) provide an effective means to evaluate the potential impact of a proposed observing system, as well as to determine tradeoffs in their design, and to evaluate data assimilation methodology. Great care must be taken to ensure realism of the OSSE's, and in the interpretation of OSSE results. All of the OSSE's that have been conducted to date have demonstrated tremendous potential for space-based wind profile data to improve atmospheric analyses, forecasts, and research. This has been true for differing data assimilation systems, analysis methodology, and model resolutions. OSSE's clearly show much greater potential for observations of the complete wind profile than for single-level wind data or observations of the boundary layer alone.

Atlas, Robert↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Nantucket (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles that integrate scanning Doppler lidars, a profiling lidar, a 915 MHz radar wind profiler, and a sonic anemometer across Northeast U.S. coastal and offshore sites during the WFIP3 campaign. Variables include wind speed, wind direction, vertical velocity, turbulence intensity, and turbulent kinetic energy, each with per-instrument quality control and inter-instrument agreement validation. Profiles are mapped to a standardized height grid – a dedicated near-surface level at the sonic measurement height (5 m AGL), 20 m spacing to 100 m, and 30 m spacing above – and carry component and derived uncertainty estimates. Heights are reported above ground level; the site's ground elevation is stored separately. The Nantucket dataset covers 1 February 2024 – 8 September 2025.

17 WIND ENERGY↗
NASA NTRS1973

Monthly and annual percentage levels of wind speed differences computed by using FPS-16 radar/Jimsphere wind profile data from Cape Kennedy, Florida

The percentage levels of wind speed differences are presented computed from sequential FPS-16 radar/Jimsphere wind profiles. The results are based on monthly profiles obtained from December 1964 to July 1970 at Cape Kennedy, Florida. The profile sequences contain a series of three to ten Jimspheres released at approximately 1.5-hour intervals. The results given are the persistence analysis of wind speed difference at 1.5-hour intervals to a maximum time interval of 12 hours. The monthly percentage of wind speed differences and the annual percentage of wind speed differences are tabulated. The percentage levels are based on the scalar wind speed changes calculated over an altitude interval of approximately 50 meters and printed out every 25 meters as a function of initial wind speed within each five-kilometer layer from near sea level to 20 km. In addition, analyses were made of the wind speed difference for the 0.2 to 1 km layer as an aid for studies associated with take-off and landing of the space shuttle.

Susko, M.↗
NASA NTRS2013

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers. During launch operations, the payload/launch team sometimes asks the LWOs if they expect the upper-level winds to change during the countdown. The LWOs used numerical weather prediction model point forecasts to provide the information, but did not have the capability to quickly retrieve or adequately display the upper-level observations and compare them directly in the same display to the model point forecasts to help them determine which model performed the best. The LWOs requested the Applied Meteorology Unit (AMU) develop a graphical user interface (GUI) that will plot upper-level wind speed and direction observations from the Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Profiling System (AMPS) rawinsondes with point forecast wind profiles from the National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM), Rapid Refresh (RAP) and Global Forecast System (GFS) models to assess the performance of these models. The AMU suggested adding observations from the NASA 50 MHz wind profiler and one of the US Air Force 915 MHz wind profilers, both located near the Kennedy Space Center (KSC) Shuttle Landing Facility, to supplement the AMPS observations with more frequent upper-level profiles. Figure 1 shows a map of KSC/CCAFS with the locations of the observation sites and the model point forecasts.

Bauman, William H., III↗
NASA NTRS2010

Lidar Wind Profiler Comparison to Weather Balloon for Support of Orion Crew Exploration Vehicle Landings

A comparison study by the National Aeronautics and Space Administration Dryden Flight Research Center, Edwards, CA and the Naval Post Graduate School Center for Interdisciplinary Remotely-Piloted Aircraft Studies, Marina, CA was conducted to show the advantages of an airborne wind profiling lidar system in reducing drift uncertainty along a reentry vehicle descent trajectory. This effort was in support of the once planned Orion Crew Exploration Vehicle ground landing. A Twin Otter Doppler Wind Lidar was flown on multiple flights along the approximate ground track of an ascending weather balloons launched from the Marina Municipal Airport. The airborne lidar used was a 5-milli-Joules, 2-micron infrared laser with a 10-centimeter telescope and a two-axis scanner. Each lidar wind profile contains data for an altitude range between the surface and flight altitude of 2,700 meters, processed on board every 20 seconds. In comparison, a typical weather balloon would traverse that same altitude range with a similar data set available in approximately 15-20 minutes. These tests were conducted on November 15 & 16, 2007. Results comparing the balloon and a 10 minute multiple lidar profile averages show a best case absolute difference of 0.18 m/s (0.35 knots) in speed and 1 degree in direction during light and variable (less than 5 knots, without constant direction) wind conditions. These limited test results indicated a standard deviation wind velocity and direction differences of 0.71 m/s (1.3 knots) and 7.17 degrees for 1800Z, and 0.70 m/s (1.3 knots) and 6.79 degrees, outside of cloud layer.

Houtas, Franzeska↗