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Results for “Doppler lidar”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Analysis of airborne Doppler lidar, Doppler radar and tall tower measurements of atmospheric flows in quiescent and stormy weather

The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments.

Bluestein, H. B.↗
DOE OSTI2020

Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar

Doppler lidars provide two measured parameters, radial velocity and signal-to-noise ratio, from which winds and turbulent properties are routinely derived. Attenuated backscatter, which gives quantitative information on aerosols, clouds, and precipitation in the atmosphere, can be used in conjunction with the winds and turbulent properties to create a sophisticated classification of the state of the atmospheric boundary layer. Calculating attenuated backscatter from the signal-to-noise ratio requires accurate knowledge of the telescope focus function, which is usually unavailable. Inaccurate assumptions of the telescope focus function can significantly deform attenuated backscatter profiles, even if the instrument is focused at infinity. Here, we present a methodology for deriving the telescope focus function using a co-located ceilometer for pulsed heterodyne Doppler lidars. The method was tested with Halo Photonics StreamLine and StreamLine XR Doppler lidars but should also be applicable to other pulsed heterodyne Doppler lidar systems. The method derives two parameters of the telescope focus function, the effective beam diameter and the effective focal length of the telescope. Additionally, the method provides uncertainty estimates for the retrieved attenuated backscatter profile arising from uncertainties in deriving the telescope function, together with standard measurement uncertainties from the signal-to-noise ratio. The method is best suited for locations where the absolute difference in aerosol extinction at the ceilometer and Doppler lidar wavelengths is small.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ARM SGP PBLH and MLH datasets from Raman lidar and Doppler lidar

The planetary boundary layer (PBL) plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including the daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary for studying PBL characterization and processes. Here, new approaches are developed to provide reliable PBLH and MLH estimates to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) User Facility. Compared to widely used lidar aerosol measurements for PBLH, WVMR is a better tracer for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to reconstruct 2D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm-season RL and ML measurements at the SGP site for five years to study warm-season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in a warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable data set of PBLH and MLH values will be valuable for studying PBL processes, model evolution, and PBL parameterization improvements. The MLH dataset includes the MLH in values of km above ground level. The PBLH dataset includes the PBLH in values of km above ground level, along with a flag ("situation_PBLH") to determine the state of the PBL (1 = Cloudy Condition, 2 = Stable Layer, 3 = Multi-layer WVMR structure, 4 = Well-Mixed PBL, 5 = A de-coupled layer, 6 = Other).

mixing layer height↗
NASA NTRSDate not supplied

Navigation Doppler Lidar

A Doppler lidar has been developed by NASA as an alternative to radars for providing velocity and altitude data to landing vehicles. Future robotic and manned missions to planetary bodies demand precise ground-relative velocity vector and altitude data to execute complex descent maneuvers for safe, soft and pinpoint landing at a pre-designated site. This lidar sensor, referred to as Navigation Doppler Lidar (NDL), provides velocity and altitude data from over five kilometers altitude to within a few cm/sec and tens of centimeters precision, respectively. NDL technology will be demonstrated on two lunar landing missions this year that will serve as precursors for large robotic and manned landing missions to the Moon, Mars, and other solar system destinations. NDL can also benefit terrestrial aerial vehicles that cannot rely on the GPS for position and velocity data or require precision data relative to local ground.

Doppler Lidar↗
DOE OSTI2016

Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations

Since turbulence measurements from Doppler lidars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several different ways, the simplest and most frequently used statistic is vertical velocity variance ( w ' 2 ) from zenith stares. But, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease w ' 2 , reduce the accuracy of these measurements. Herein, an established method that utilises the autocovariance of the signal to remove noise is evaluated and its skill in correcting for volume-averaging effects in the calculation of w ' 2 is also assessed. In addition, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of w ' 2 . And through comparison of observations from two Doppler lidars and sonic anemometers on a 300 m tower, the autocovariance technique is shown to generally improve estimates of w ' 2 . After the autocovariance technique is applied, values of w ' 2 from the Doppler lidars are generally in close agreement ( R 2 ≈ 0.95 -0.98) with those calculated from sonic anemometer measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Doppler lidar atmospheric wind sensor - Reevaluation of a 355-nm incoherent Doppler lidar

Reliable Nd:YAG laser technology and currently available optical sensors are presently used to reevaluate the performance of an incoherent Doppler lidar system operating at 354.7 nm. This system makes a more efficient use of output laser power than heretofore possible through a matching of the usable and detectable field of view of the Fabry-Perot interferometer receiver with that of the transmitter. Major advantages accrue to this system from the lower output power requirement, which is a primary cost driver for the prospective Spaceborne Doppler Wind Lidar.

Rees, David↗
DOE OSTI2019

Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations

Hight-resolved observations of vertical winds remain nearly non-existing over the Himalayas, despite of an­ticipated crucial role of vertical motions in transporting pollution across the Himalayan hms. The present study analyze the vertical wind observations from surface to 1 km above ground level over Manora Peak (29.4° N; 79.5° E; 1958 m ams!) in the Himalaya performed using a Doppler Lidar during the Ganges Valley Aerosol Experiment (GVAX). Vertical wind exhibited a pronounced diurnal variability at Manora Peak comprising of upward motions during the daytime (05-10 UT) and downward motions during nighttime typical of a mountain­valley system. Mean vertical wind speeds are observed to be varying from -0.8 to +0.8 ms- 1 during the study period with a variance of 0.1-1.5 m2s·2, which is attributed to the thermally driven turbulence. Mean vertical winds are observed to be stronger in the Doppler Lidar profiles above Manora Peak (-0_8 to 0.8 ms- 1) as compared to near surface measurements at this station using an ultrasonic anemometer ( -0.4 to 0.4 ms - 1 ), and low altitude stations in India. Daytime vertical wind speeds are observed to be higher during pre-monsoon (0.81 ms- 1), as compared to post-monsoon (0.24 ms- 1) and winter (0.33 ms- 1)_ Average Black Carbon (BC) concentrations are significantly higher during strong upward vertical winds, which indicates efficient transport of polluted air mass from low-altitude regions to the Himalaya. Weather Research and Forecasting (WRF) model reproduces the observed diurnal pattern in the vertical wind at the observation site however the model un­derestimates the variability.

Shukla, K K.↗
DOE OSTI2020

Characterizing NWP Model Errors Using Doppler-Lidar Measurements of Recurrent Regional Diurnal Flows: Marine-Air Intrusions into the Columbia-River Basin

Ground-based Doppler-lidar instrumentation provides atmospheric wind data at dramatically improved accuracies and spatial/temporal resolutions. These capabilities have provided new insights into atmospheric flow phenomena, but they also should have a strong role in NWP model improvement. Insight into the nature of model errors can be gained by studying recurrent atmospheric flows, here a regional summertime diurnal sea breeze and subsequent marine-air intrusion into the arid interior of Oregon-Washington, where these winds are an important windenergy resource. These marine intrusions were sampled by three scanning Doppler lidars in the Columbia-River Basin as part of the Second Wind Forecast Improvement Project (WFIP2), using data from summer 2016. Lidar time-height cross sections of wind speed identified eight days when the diurnal-flow cycle, (peak wind speeds at midnight, afternoon minima) was obvious and strong. Eight-day composite time-height cross sections of lidar wind speeds are used to validate those generated by the operational NCEP-HRRR model. HRRR simulated the diurnal wind cycle, but produced errors in the timing of onset and significant errors due to a premature nighttime demise of the intrusion flow, producing low-bias errors of 6 m s-1 . Day-to-day and in the composite, whenever a marine intrusion occurred, HRRR made these same errors. The errors occurred under a range of gradient wind conditions indicating that they resulted from the misrepresentation of physical processes within a limited region around the measurement locations. Because of their generation within a limited geographical area, field-measurement programs can be designed to find and address the sources of these NWP errors.

Banta, Robert M.↗
DOE OSTI2015

Finnish Meteorological Institute Doppler Lidar

This doppler lidar system provides co-polar and cross polar attenuated backscatter coefficients,signal strength, and doppler velocities in the cloud and in the boundary level, including uncertainties for all parameters. Using the doppler beam swinging DBS technique, and Vertical Azimuthal Display (VAD) this system also provides vertical profiles of horizontal winds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating wind profiles in a numerical weather prediction model with Doppler lidar

We use Doppler lidar wind profiles from six locations around the globe to evaluate the wind profile forecasts in the boundary layer generated by the operational global Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts (ECMWF). The six locations selected cover a variety of surfaces with different characteristics (rural, marine, mountainous urban, and coastal urban). We first validated the Doppler lidar observations at four locations by comparison with co-located radiosonde profiles to ensure that the Doppler lidar observations were of sufficient quality. The two observation types agree well, with the mean absolute error (MAE) in wind speed almost always less than 1 m s –1 . Large deviations in the wind direction were usually only seen for low wind speeds and are due to the wind direction uncertainty increasing rapidly as the wind speed tends to zero. Time–height composites of the wind evaluation with 1 h resolution were generated, and evaluation of the model winds showed that the IFS model performs best over marine and coastal locations, where the mean absolute wind vector error was usually less than 3 m s –1 at all heights within the boundary layer. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. For example, in Granada, which is near a high mountain range, the IFS model failed to capture a commonly occurring mountain breeze, which is highly dependent on the sub-grid-size terrain features that are not resolved by the model. The uncertainty in the wind forecasts increased with forecast lead time, but no increase in the bias was seen. At one location, we conditionally performed the wind evaluation based on the presence or absence of a low-level jet diagnosed from the Doppler lidar observations. The model was able to reproduce the presence of the low-level jet, but the wind speed maximum was about 2 m s –1 lower than observed. This is attributed to the effective vertical resolution of the model being too coarse to create the strong gradients in wind speed observed. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Wind Measurements with a 355 nm Molecular Doppler Lidar

A Doppler lidar system based on the molecular double edge technique is described. The system is mounted in a modified van to allow deployment in field operations. The lidar operates with a tripled Nd:YAG laser at 355 nm, a 45cm aperture telescope and a matching azimuth-over-elevation scanner to allow full sky access. Validated atmospheric wind profiles have been measured from 1.8 km to 35 km with a 178 m vertical resolution. The range dependent rms deviation of the horizontal wind speed is 0.4 - 6 m/s. The results of wind speed and direction are in good agreement with balloon sonde wind measurements made simultaneously at the same location.

Gentry, Bruce M.↗
DOE OSTI2020

Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

17 WIND ENERGY↗
NASA NTRS1985

Analysis of Doppler lidar data

Dual Doppler lidar analyses of data taken by pulsed lidars demonstrated feasibility of deriving wind fields from coordinated lidar scans. Limited case histories of thunderstorm outflows were obtained. Co-located comparison between Marshall Space Flight Center lidar and NCAR 5.5 cm radar demonstrated desirability of lidar in cases of marginal radar reflectivity in clear air and low-elevation scans. Analysis continued on backscattered intensity and velocity measurements made from April 1983 to February 1984. A slant path method was used to calculate vertical profiles of volumetric backscatter and adsorption in the lower troposphere. High-quality VAD scans were identified as candidates for investigating feasibility of calculating horizontal motion fields using single Doppler lidar. Activities during FY-85 also included participation in Fall 1984 airborne Doppler lidar flight experiments. Preliminary data review was begun using McIdas system. Analysis of backscatter and absorpiton profiles continues. Focus is on understanding spatial and temporal variations, as well as frequency distribution, of backscatter at several tropospheric levels. Results from this study provide input to evaluation of clean/dirty airmass hypothesis of aerosol distribution. Assistance is being given to preparation of a comprehensive, global backscatter measurement plan. Analysis of data from Fall 1984 flight experiments is just beginning. Work has begun on preprocessing data to minimize errors due to electro-optic modulator malfunction during flights.

Rothermel, J.↗
DOE OSTI2015

3D Volumetric Analysis of Wind Turbine Wake Properties in the Atmosphere Using High-Resolution Doppler Lidar

Wind turbine wakes in the atmosphere are three-dimensional (3D) and time dependent. An important question is how best to measure atmospheric wake properties, both for characterizing these properties observationally and for verification of numerical, conceptual, and physical (e.g., wind tunnel) models of wakes. Here a scanning, pulsed, coherent Doppler lidar is used to sample a turbine wake using 3D volume scan patterns that envelop the wake and simultaneously measure the inflow profile. The volume data are analyzed for quantities of interest, such as peak velocity deficit, downwind variability of the deficit, and downwind extent of the wake, in a manner that preserves the measured data. For the case study presented here, in which the wake was well defined in the lidar data, peak deficits of up to 80% were measured 0.6-2 rotor diameters (D) downwind of the turbine, and the wakes extended more than 11D downwind. Temporal wake variability over periods of minutes and the effects of atmospheric gusts and lulls in the inflow are demonstrated in the analysis. Lidar scanning trade-offs important to ensuring that the wake quantities of interest are adequately sampled by the scan pattern, including scan coverage, number of scans per volume, data resolution, and scan-cycle repeat interval, are discussed.

17 WIND ENERGY↗