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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluation of Monin‐Obukhov Similarity Theory Wind Profiles in Convective Storm Environments and Cold Pools at the ARM Southern Great Plains Atmospheric Observatory

Monin-Obukhov similarity theory (MOST) is widely used in numerical weather prediction to model surface fluxes of momentum, heat, and water vapor. However, MOST is based on assumptions of steady state and horizontally homogeneous turbulence that can lead to prediction errors in and around convective storms. To understand the nature of these errors, we used wind and eddy covariance flux measurements from the Atmospheric Radiation Measurement Southern Great Plains Atmospheric Observatory to evaluate MOST wind profiles in fair-weather and convective storm environments, specifically those of mesoscale convective systems and ordinary thunderstorms. MOST wind profiles agreed well with observations in fair-weather cases, while in convective storm cases the theory systematically overestimated shear in cold pools after gust front passage. Surface layer stability was found to be important in assessing MOST within convective storm environments. The overestimation of wind shear in cold pools suggests the role of non-local fluxes in transferring momentum downward. We discuss reasons for differences and agreement with past studies, and conclude with recommendations to improve prediction of surface winds and fluxes in convective storm simulations.

58 GEOSCIENCES↗
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 to include NASA's Launch Services Program and NASA's Ground Systems Development and Operations Program. They currently do not have the capability to display and overlay profiles of upper-level observations and numerical weather prediction model forecasts. The LWOs requested the Applied Meteorology Unit (AMU) develop a tool in the form of a graphical user interface (GUI) that will allow them to plot upper-level wind speed and direction observations from the Kennedy Space Center (KSC) 50 MHz tropospheric wind profiling radar, KSC Shuttle Landing Facility 915 MHz boundary layer wind profiling radar and Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Processing System (AMPS) radiosondes, and then overlay forecast wind profiles from the model point data including the North American Mesoscale (NAM) model, Rapid Refresh (RAP) model and Global Forecast System (GFS) model to assess the performance of these models. The AMU developed an Excel-based tool that provides an objective method for the LWOs to compare the model-forecast upper-level winds to the KSC wind profiling radars and CCAFS AMPS observations to assess the model potential to accurately forecast changes in the upperlevel profile through the launch count. The AMU wrote Excel Visual Basic for Applications (VBA) scripts to automatically retrieve model point data for CCAFS (XMR) from the Iowa State University Archive Data Server (http://mtarchive.qeol.iastate.edu) and the 50 MHz, 915 MHz and AMPS observations from the NASA/KSC Spaceport Weather Data Archive web site (http://trmm.ksc.nasa.gov). The AMU then developed code in Excel VBA to automatically ingest and format the observations and model point data in Excel to ready the data for generating Excel charts for the LWO's. The resulting charts allow the LWOs to independently initialize the three models 0-hour forecasts against the observations to determine which is the best performing model and then overlay the model forecasts on time-matched observations during the launch countdown to further assess the model performance and forecasts. This paper will demonstrate integration of observed and predicted atmospheric conditions into a decision support tool and demonstrate how the GUI is implemented in operations.

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, California) and the Naval Post Graduate School Center for Interdisciplinary Remotely-Piloted Aircraft Studies (Marina, California) was conducted to show the advantages of an airborne wind profiling light detection and ranging (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 each ascending weather balloon launched from the Marina Municipal Airport (Marina, California). The airborne lidar used was a 5-mJ, 2-micron infrared laser with a 10-cm telescope and a two-axis scanner. Each lidar wind profile contains data for an altitude range between the surface and flight altitude of 2.7 km, processed on board every 20 s. In comparison, a typical weather balloon would traverse that same altitude range with a similar data set available in approximately 15 to 20 min. These tests were conducted on November 15 and 16, 2007. Results show a best-case absolute difference of 0.18 m/s (0.35 knots) in speed and 1 degree in direct

Houtas, Franzeska F.↗
NASA NTRS1994

Application of 50 MHz doppler radar wind profiler to launch operations at Kennedy Space Center and Cape Canaveral Air Station

This paper presents a case study where a significant wind shift, not detected by jimspheres, was detected by the 50 MHz DRWP (Doppler Radar Wind Profiler) and evaluated to be acceptable prior to the launch of a Shuttle. This case study illustrates the importance of frequent upper air wind measurements for detecting significant rapidly changing features as well as for providing confidence that the features really exist and are not due to instrumentation error. Had the release of the jimsphere been timed such that it would have detected the entire wind shift, there would not have been sufficient time to release another jimsphere to confirm the existence of the feature prior to the scheduled launch. We found that using a temporal median filter on the one minute spectral estimates coupled with a constraining window about a first guess velocity effectively removes nearly all spurious signals from the velocity profile generated by NASA's 50 MHz DRWP while boosting the temporal resolution to as high as one profile every 3 minutes. The higher temporal resolution of the 50 MHz DRWP using the signal processing algorithm described in this paper ensures the detection of rapidly changing features as well as provides the confidence that the features are genuine. Further benefit is gained when the profiles generated by the DRWP are examined in relation to the profiles measured by jimspheres and/or rawinsondes. The redundancy offered by using two independent measurements can dispel or confirm any suspicion regarding instrumentation error or malfunction and wind profiles can be examined in light of their respective instruments' strengths and weaknesses.

Schumann, Robin S.↗
DOE OSTI2026

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

WINDPROF provides 10-minute wind and turbulence profiles that integrate a scanning Doppler lidar, a profiling lidar, a 915 MHz radar wind profiler, and a surface met station 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 10 m surface-wind height, 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 Block Island dataset covers 1 February 2024 – 8 September 2025.

17 WIND ENERGY↗
NASA NTRS1986

Assessment of measurement error due to sampling perspective in the space-based Doppler lidar wind profiler

A Multipair Algorithm (MPA) has been developed to minimize the contribution of the sampling error in the simulated Doppler lidar wind profiler measurements (due to angular and spatial separation between shots in a shot pair) to the total measurement uncertainty. Idealized wind fields are used as input to the profiling model, and radial wind estimates are passed through the MPA to yield a wind measurement for 300 x 300 sq km areas. The derived divergence fields illustrate the gradient patterns that are particular to the Doppler lidar sampling strategy and perspective.

Houston, S. H.↗
DOE OSTI2024

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Investigating the Use of Machine Learning (ML) to Assess Tropospheric Doppler Radar Wind Profiler (TDRWP) Data Quality

Manual Quality Control (MQC) of Tropospheric Doppler Radar Wind Profiler (TDRWP) data is essential for defining an accurate climatology for downstream aerospace vehicle assessments. MQC traditionally takes around 30.5 hours per year of radar data. The Marshall Space Flight Center Natural Environments Branch (MSFC NE) used machine learning (ML) to test the feasibility of automating the MQC process, showing a potential to reduce labor by 300%. However, analysis of the model showed some false positives. We compared a neural network to the model to validate it and develop a process for assessing comparable solutions in the future.

Corey Walker↗
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 NTRS2016

Results of the NASA Kennedy Space Center 50-MHz Doppler Radar Wind Profiler Operational Acceptance Test

This paper presents results of the new Kennedy Space Center (KSC) 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). The goal of the OAT was to verify the data quality of the new DRWP against the performance of the previous DRWP in order to use wind data derived by the new DRWP for space launch vehicle operations support at the Eastern Range. The previous DRWP was used as a situational awareness asset for mission operations to identify rapid changes in the wind environment that weather balloons cannot depict. The Marshall Space Flight Center's Natural Environments Branch assessed data from the new DRWP collected during Jan-Feb 2015 against a specified set of test criteria. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 49 concurrent DRWP and balloon profiles presented root mean square wind component differences around 2.0 m/s. Evaluation of the DRWP's coherence between five-minute wind pairs found the effective vertical resolution to be Nyquist-limited at 300 m for both wind components. In addition, the sensitivity to rejecting data that do not have adequate signal was quantified. This paper documents the data, quality control procedures, methodology, and results of each analysis.

Barbre', Robert E., Jr.↗