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At least 37 records · Page 2

Observations of Thermospheric Horizontal Winds at Watson Lake, Yukon Territory (lambda=65 Deg N)

Fabry-Perot interferometer observations of the thermospheric O I (6300 A) emission have been conducted from an airglow observatory at a dark field site in the southeastern Yukon Territory, Canada, for the period November 1991 to April 1993. The experiment operated in unattended, remote fashion, has resulted in a substantial data set from which mean neutral winds have been determined. Dependent upon geomagnetic activity, the nocturnal location of the site is either equatorward of the auroral oval or within oval boundaries. The data set is rich enough to permit hourly binning of neutral winds based upon the K(sub p) geomagnetic disturbance index as well as the season. For cases of low geomagnetic activity the averaged vector horizontal neutral wind exhibits the characteristics of a midlatitude site displaying antisunward pressure-gradient-driven winds. As the geomagnetic activity rises in the late afternoon and evening winds slowly rotate sunward in an anticlockwise direction, initially remaining near 100 m/s in speed but eventually increasing to 300 m/s for K(sub p) greater than 5. For the higher levels of activity the observed neutral wind flow pattern resembles a higher-latitude polar cap pattern characterized by ion drag forcing of thermospheric neutral gases. In addition, rotational Coriolis forcing on the dusk side enhances the ion drag forcing, resulting in dusk winds which trace out the clockwise dusk cell plasma flow. On the dawn side the neutral winds also rotate in an anticlockwise direction as the strength of geomagnetic disturbances increase. Since the site is located at a transition latitude between the midlatitude and the polar cap the data set provides a sensitive test for general circulation models which attempt to parameterize the contribution of magnetospheric processes. A comparison with the Vector Spherical Harmonic (VSH) model indicates several regions of poor correspondence for December solstice conditions but reasonable agreement for the vernal equinox.

Niciejewski, R. J.

Vertical and Horizontal Wind Structure Prior to and During the 1997/1998 ENSO Event

Analyses of ECMWF and satellite wind products are used to investigate low frequency fluctuations in the wind fields immediately preceding and during the 1997/1998 ENSO event. An extended EOF analysis of the horizontal and vertical wind structure that allows for the study of propagating features indicates that the dominant mode of variability established in the lower levels of the atmosphere is a convergence in the central tropical Pacific. At mid-levels, the westerlies increase with time over most of the equatorial Pacific, and there are closed cyclonic features on either side of the equator. At upper levels, the flow tends to become divergent across the equatorial Pacific, and there is a strong flow from the northwest Pacific across Indonesia that then turns to the west along the equator in the Indian Ocean. The addition of satellite data for improved surface wind estimates reveal that the Indian Ocean winds were anomalously strong during the winter preceding the initiation of the ENSO event. An analysis of the momentum convergence flux at the surface indicates a very strong anomaly 9 months prior to the ENSO event that begins in the western Indian Ocean and propagates to the east, arriving over the Pacific warm pool area coincident with the beginning of the El Nino. Changes in the near surface thermal and water vapor structure over the Indian Ocean during this period will also be discussed.

Adamec, David

Crossed-beam technique for measuring horizontal winds

Three ground-based single-beam detectors determine wind vectors present within a given volume. Winds approximately constant near a selected height, blowing into or out of a 90 degree arc can be calculated with reasonably small error.

Heybey, W. H.

Variation of horizontal winds with height /surface to 150 meters/

The data used in the reported analysis consist of 79 five-second intervals from the Automatic Data Acquisition System (ADAS) at the tower facility. Measurements were recorded on July 3, 1973 from 1931 through 2152 GMT during various wind conditions. Peak wind speed was determined for each 5-second interval and level and classified as low, moderate, high, or gale-force. Attention is given to peak wind speeds, wind speed differences determined from peak and associated speeds, and wind speed differences determined from the entire data record. Considering frequency and intensity of peak wind speeds, levels from 30 meters and up are significant ones. Considering frequency and magnitude of wind shears, these analyses indicate that the 60-30 layer is the significant one.

Alexander, M.

Horizontal wind estimates deterministically derived from the STS-1 entry flight date--a comparison with available meteorology data

Two wind profiles were determined from STS-1 entry flight data based on preliminary best estimate trajectory (BET). The deterministic process used in deriving the atmospheric winds requires inertial estimates of the spacecraft angle-of-attack (alpha) and side-slip angle (beta) from the BET in conjunction with some air data system measurements of the actual angles. The current orbiter air data system (OADS) provides the necessary alpha information. Two beta profiles were adopted. The first profile assumed that the spacecraft would weathervane into any prevailing wind. The second assumed a conservative side-slip history computed from measured accelerations in the spacecraft body axes. It is shown that there are no major differences between the deterministic winds computed using both methods. Further, comparisons of these winds with raw measurements from Tehachapi, California, and preliminary winds obtained from the LaRC LAIRS file and the JSC/TRW descent BET are presented.

Kelly, G. M.

Temperature and horizontal wind measurements on the ER-2 aircraft during the 1987 airborne Antarctic ozone experiment

The NASA ER-2 aircraft is equipped with special instrumentation to provide accurate in situ measurement of the atmospheric state variables during flight. The Meteorological Measurement System (MMS) on the ER-2 aircraft is described. Since the meteorological parameters (temperature, pressure, and wind vector) are extensively used by other ER-2 experimenters for data processing and interpretation, the accuracy and resolution of each of these parameters are assessed and discussed. During the 1987 Airborne Antarctic Ozone Experiment (AAOE) mission, the ER-2 aircraft was stationed at Punta Arenas, Chile (53 S, 72 W), and successfully flew over Antarctica on 12 occasions between August 17 and September 22, 1987. On each of the 12 flights, the ER-2 aircraft flight plan was to take off at approximately the same local time, fly southward at a near constant potential temperature surface, descend and ascend at the southernmost terminus at about 72 S over Antarctica and return northward at either the same or a different constant potential temperature surface. The measurements of the MMS experiment during the AAOE mission are presented. MMS data are organized to provide a composite view of the polar atmosphere, which is characterized by frigid temperatures and high zonal winds. Altitudinal variations of the temperature measurement (during takeoff/landing at Punta Arenas and during descent/ascent at the southern terminus) and latitudinal variations of the zonal wind (on near constant potential temperature surfaces) are emphasized and discussed.

Chan, K. Roland

Vertical Mass, Momentum, Moisture, and Heat Fluxes in Hurricanes above 10 km during CAMEX-3 and CAMEX-4

The third and fourth NASA Convection and Moisture Experiments (CAMEX-3 and CAMEX-4) during the Atlantic hurricane seasons of 1998 and 2001, respectively, have yielded comprehensive multi-aircraft datasets using, both remote and in-situ instrumentation. Among these are high-frequency in-situ measurements of vertical wind, horizontal wind, temperature, and water vapor, made from NASA's DC-8 aircraft in the upper portions of the hurricane (typically above 10 km). Wind and temperature measurements were made at 20 hz by the NASA/Ames Meteorological Measurement System, while water vapor was measured at 1 hz by the NASA/JPL Laser Hygrometer. Fluxes of heat, momentum, and moisture at these levels are important, since modeling studies have shown that ice processes, which are dominant at temperatures below -40C (where the DC-8 flies) are important for hurricane intensification. Also, there are indications from satellite studies that latent heat release at DC-8 levels is significant, perhaps a third of those in the mid-troposphere. Preliminary results show that typical updrafts in the eyewall region are comparable to or higher than previous observations of tropical convection, with several instances of updraft magnitudes of 15 meters per second (the maximum observed was 21 meters per second). They also show significant supersaturations (10-20% or more) in the updrafts, which would enhance the latent heat release at the upper levels of the hurricane. This paper will examine the magnitude and distribution of small and mesoscale vertical fluxes of mass, momentum, moisture, and heat. The goal is to examine the role of these fluxes in the overall budgets of the respective quantities in the upper portions of the hurricane.

Pfister, Leonhard

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

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

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

Wind response characteristics of horizontal axis wind turbines

It was the objective of the work reported here, and in the companion paper 1 . A broader examination of wind turbine dynamic response to turbulence, and attempts to ascertain the features of turbulence that wind turbines are most sensitive to were made. A statistical description of the wind input including all three wind components and allowing linear wind gradients across the rotor disk, was used together with quasi-static aerodynamic theory and an elementary structural model involving only a few degrees of freedom. The idea was to keep the turbine model simple and show the benefits of this type of statistical wind representation before attempting to use a more complex turbine model. As far as possible, the analysis was kept in the simplest form, while still preserving key physical responses.

Thresher, R. W.

Wind turbulence inputs for horizontal axis wind turbines

Wind turbine response characteristics in the presence of atmospheric turbulence was predicted using two major modeling steps. First, the important atmospheric sources for the force excitations felt by the wind turbine system were identified and characterized. Second, a dynamic model was developed which describes how these excitations are transmitted through the structure and power train. The first modeling step, that of quantifying the important excitations due to the atmospheric turbulence was established. The dynamic modeling of the second step was undertaken separately.

Holley, W. E.

Development of methodology for horizontal axis wind turbine dynamic analysis

Horizontal axis wind turbine dynamics were studied. The following findings are summarized: (1) review of the MOSTAS computer programs for dynamic analysis of horizontal axis wind turbines; (2) review of various analysis methods for rotating systems with periodic coefficients; (3) review of structural dynamics analysis tools for large wind turbine; (4) experiments for yaw characteristics of a rotating rotor; (5) development of a finite element model for rotors; (6) development of simple models for aeroelastics; and (7) development of simple models for stability and response of wind turbines on flexible towers.

Dugundji, J.

A simple, analytical, axisymmetric microburst model for downdraft estimation

A simple analytical microburst model was developed for use in estimating vertical winds from horizontal wind measurements. It is an axisymmetric, steady state model that uses shaping functions to satisfy the mass continuity equation and simulate boundary layer effects. The model is defined through four model variables: the radius and altitude of the maximum horizontal wind, a shaping function variable, and a scale factor. The model closely agrees with a high fidelity analytical model and measured data, particularily in the radial direction and at lower altitudes. At higher altitudes, the model tends to overestimate the wind magnitude relative to the measured data.

Vicroy, Dan D.