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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparison of horizontal wind speed and direction measurements from dual-Doppler radar and profiling lidars

Dual-Doppler radar is a relatively new technology in the wind energy community and thus not yet studied vastly. This paper aims to compare horizontal wind speed and direction data retrieved from dual-Doppler radar and profiling lidars within the American WAKE experimeNt (AWAKEN) to investigate the influence of measurement height, wind direction and speed on the comparison. The 10-min averaged data show a better agreement of the measurements for higher altitudes, especially at faster wind speeds. For the wind direction, two sectors of larger differences in the measurements were detected: around 270° transient winds occur with a higher frequency than in other sectors. To explain the different measurement values in the wind direction sector around 90°, further studies, e.g. on the influence of atmospheric stability, are necessary.

17 WIND ENERGY↗
DOE OSTI2023

Performance Audit Report: Automated Meteorological Monitoring Stations, Lawrence Livermore National Laboratory

The Waste and Air Quality Offices Group at the Lawrence Livermore National Laboratory operates two main meteorological monitoring sites near Livermore, California. The primary met tower (Site 200) is located in the northwest corner of the lab and consists of a fifty-two (52) meter tower with vertical wind speed sensors, horizontal wind speed and direction sensors and air temperature sensors at fifty-two (52) meters, twenty-three (23) meters and ten (10) meters. In addition, there is a temperature and humidity probe at ten (10) meters. At two (2) meters there are upward and downward facing solar and infrared radiation sensors, an air temperature sensor, barometric pressure sensor and a temperature and relative humidity probe. At ground level there is a tipping bucket rain gauge located to the southwest of the tower. The datalogger, communication peripherals and the barometric pressure sensor are housed in a small building near the tower. The Site 300 met site is located approximately 10 miles east of Livermore within the boundary of the LLNL blast test site. This site also consists of a 52-meter tower which is configured the same as the 52-meter tower at Site 200. There is also a building at this site that houses the datalogger, communication peripherals and the barometric pressure sensor. At both Site 200 and Site 300, data are collected by Ethernet with telephone modem collection as a backup. The data collection interval for both sites is fifteen (15) minutes via workstations running Loggernet software located at the main lab facility. The audits of the Lawrence Livermore National Laboratory’s two automated meteorological stations located near Livermore, California were performed on October 24 & 25, 2023. These audits were performed under the guidelines of the Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV, Version 2 and the On-Site Meteorological Program Guidance for Regulatory Modeling Applications, U.S. EPA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2026

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2025

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
DOE OSTI2026

Wind lidar operations and observations from Tundra Pigeon

Lawrence Livermore National Laboratory brought a ZX-300 profiling lidar to the Tundra Pigeon experiment for the purpose of collecting wind measurements in the lower atmospheric boundary layer. The ZX-300 lidar is a portable Doppler lidar which uses light to track naturally occurring aerosols across a measurement cone, thereby deriving wind speed (horizontal and vertical) and wind direction. The ZX-300 is programable between the heights of 10 m and 300 m above ground level and additionally has a 1 m onboard meteorological sensor for collecting measurements of air temperature, relative humidity, air pressure and wind at 1 m height. We programmed the ZX-300 to target altitudes of most interest to the tracer experiment. These heights were 10, 15, 20, 30, 38, 50, 75, 100, 125, 150 and 200 m. Note that the 38 m level is a fixed calibration height and cannot be changed. This measurement strategy prioritized winds close to the surface while ensuring that we’d also collect information about the winds aloft. The wind measurements are collected directly over the lidar instrument and represent a vertical profile of the winds over that location. However, given that there were minimal terrain and vegetation differences in the area, we’d expect these wind conditions to be representative of a larger volume area, discussed in more detail below.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CO2 Profiling System for CO2 Storage (a1-level)

The Southern Great Plains (SGP) carbon dioxide flux (CO2FLUX) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), sensible heat, and momentum. The systems use the eddy covariance technique, which computes the fluxes from the vertical wind speed in combination with the concentrations of CO2 and H2O, temperature, and horizontal wind speed, respectively. A 3D sonic anemometer obtains the wind components and the temperature, while an infrared gas analyzer measures CO2 and H2O. A sub-system also measures half-hour averages of radiation, meteorological, and soil measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Abstract In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS Urban Canyons - Space Science and Engineering Center (SPARC) Doppler lidar data

This is the netCDF format output from the Halo Photonics Streamline XR Doppler lidar that was deployed next to the Space Science and Engineering Center (SPARC) trailer at the University of Illnois-Chicago greenhouse parking lot during CROCUS Urban Canyons. The purpose of collecting this dataset is to provide vertical and horizontal wind profiles for studying the characteristics of turbulence over the urban canyon of Chicago. This data contains the radial velocity, intensity, and backscatter from the vertical profile, range height indicator, and sector scans that were performed over both Intensive Operating Period 1 and 2 of CROCUS Urban Canyons. There are four different types of files: * The Range Height Indicator (RHI) files contain scans that are along a constant azimuth, spanning the entire hemisphere of elevation values above the surface. * The Velocity Azimuth Display (VAD) files contain the raw radial velocity data from the 6-beam, 60 degree scans. * The User1 files contain stacked Plan Position Indicator scans over a 45 degree quadrant over downtown Chicago. * The Stare files contain vertically pointing scans. These are standard netCDF files that can be opened using xarray. The VAD scans can be processed from their raw radial velocities to horizontal wind speeds with the Atmospheric data Community Toolkit (https://arm-doe.github.io/ACT/).

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS↗
DOE OSTI2024

Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation

Abstract. The Weather Research Forecasting (WRF) version 4.3 model is configured within a Lagrangian framework to quantify the impact of aerosols on evolving cloud fields. Kilometer-scale simulations utilizing meteorological boundary conditions are based on 10 case study days offering diverse meteorology during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA). Measurements from aircraft, the ground-based Atmosphere Radiation Measurement (ARM) site at Graciosa Island in the Azores, and A-Train and geostationary satellites are utilized for validation, demonstrating good agreement with the WRF-simulated cloud and aerosol properties. Higher aerosol concentration leads to suppressed drizzle and increased cloud water content in all case study days. These changes lead to larger radiative cooling rates at cloud top, enhanced vertical velocity variance, and increased vertical and horizontal wind speed near the base of the lower-tropospheric inversion. As a result, marine cloud cell area expands, narrowing the gap between shallow clouds and increasing cloud optical thickness, liquid water content, and the top-of-atmosphere outgoing shortwave flux. While similar aerosol effects are observed in lightly to non-raining clouds, they tend to be smaller by comparison. These simulations show a relationship between cloud cell area expansion and the radiative adjustments caused by liquid water path and cloud fraction changes. The adjustments are positive and scale as 74 % and 51 %, respectively, relative to the Twomey effect. While higher-resolution large-eddy simulations may provide improved representation of cloud-top mixing processes, these results emphasize the importance of addressing mesoscale cloud-state transitions in the quantification of aerosol radiative forcing that cannot be attained from traditional climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Estimating turbulent energy flux vertical profiles from uncrewed aircraft system measurements: exemplary results for the MOSAiC campaign

This study analyzes turbulent energy fluxes in the Arctic atmospheric boundary layer (ABL) using measurements with a small uncrewed aircraft system (sUAS). Turbulent fluxes constitute a major part of the atmospheric energy budget and influence the surface heat balance by distributing energy vertically in the atmosphere. However, only few in situ measurements of the vertical profile of turbulent fluxes in the Arctic ABL exist. The study presents a method to derive turbulent heat fluxes from DataHawk2 sUAS turbulence measurements, based on the flux gradient method with a parameterization of the turbulent exchange coefficient. This parameterization is derived from high-resolution horizontal wind speed measurements in combination with formulations for the turbulent Prandtl number and anisotropy depending on stability. Measurements were taken during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the Arctic sea ice during the melt season of 2020. For three example cases from this campaign, vertical profiles of turbulence parameters and turbulent heat fluxes are presented and compared to balloon-borne, radar, and near-surface measurements. The combination of all measurements draws a consistent picture of ABL conditions and demonstrates the unique potential of the presented method for studying turbulent exchange processes in the vertical ABL profile with sUAS measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER CLAMPS1 Doppler Lidar VAD Data

These files contain 24 hour periods of data collected from the CLAMPS1 Halo Streamline XR Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the TRACER project. For the TRACER campaign, the CLAMPS1 Doppler lidar collected PPI scans at 70 deg elevation every 20 minutes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER CLAMPS2 Doppler Lidar VAD Data

These files contain 24 hour periods of data collected from the CLAMPS2 Halo Streamline XR+ Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER SPARC Doppler Lidar VAD Data

These files contain 24 hour periods of data collected from the SPARC Halo Streamline XR Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AWAKEN CLAMPS1 Doppler Lidar VAD Data

These files contain 24 hour periods of data collected from the CLAMPS1 Halo Streamline XR+ Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the AWAKEN project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AWAKEN CLAMPS2 Doppler Lidar VAD Data

These files contain 24 hour periods of data collected from the CLAMPS2 Halo Streamline XR+ Doppler lidar. The Doppler lidar conducts regular conical scans at a set elevation angle. These data are then passed through a typical VAD algorithm to retrieve horizontal wind speed and direction profiles. These data were collected during the AWAKEN project.

54 ENVIRONMENTAL SCIENCES↗