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NASA NTRS1992

Sodium Doppler Temperature Lidar Observations of the Mesopause Region Temperature and Wind Structure

Measurements of the mesopause region temperature structure are being routinely conducted at Urbana, Illinois with the University of Illinois (UIUC) Sodium Doppler Temperature Lidar. The first measurements were taken with this system in Jan. 1991 and are now being made, and will soon be done routinely in conjunction with the temperature measurements. The results obtained with the UIUC Sodium Doppler Temperature Lidar (SDTL) are presented. A description of the system is given in accompanying articles.

Senft, Daniel C.↗

NASA NTRS1993

Coherent lidar design and performance verification

The verification of LAWS beam alignment in space can be achieved by a measurement of heterodyne efficiency using the surface return. The crucial element is a direct detection signal that can be identified for each surface return. This should be satisfied for LAWS but will not be satisfied for descoped LAWS. The performance of algorithms for velocity estimation can be described with two basic parameters: the number of coherently detected photo-electrons per estimate and the number of independent signal samples per estimate. The average error of spectral domain velocity estimation algorithms are bounded by a new periodogram Cramer-Rao Bound. Comparison of the periodogram CRB with the exact CRB indicates a factor of two improvement in velocity accuracy is possible using non-spectral domain estimators. This improvement has been demonstrated with a maximum-likelihood estimator. The comparison of velocity estimation algorithms for 2 and 10 micron coherent lidar was performed by assuming all the system design parameters are fixed and the signal statistics are dominated by a 1 m/s rms wind fluctuation over the range gate. The beam alignment requirements for 2 micron are much more severe than for a 10 micron lidar. The effects of the random backscattered field on estimating the alignment error is a major problem for space based lidar operation, especially if the heterodyne efficiency cannot be estimated. For LAWS, the biggest science payoff would result from a short transmitted pulse, on the order of 0.5 microseconds instead of 3 microseconds. The numerically errors for simulation of laser propagation in the atmosphere have been determined as a joint project with the University of California, San Diego. Useful scaling laws were obtained for Kolmogorov atmospheric refractive turbulence and an atmospheric refractive turbulence characterized with an inner scale. This permits verification of the simulation procedure which is essential for the evaluation of the effects of refractive turbulence on coherent Doppler lidar systems. The analysis of 2 micron Doppler lidar data from Coherent Technologies, Inc. (CTI) has demonstrated many of the advantages of doppler lidar measurements of boundary layer winds. The effects of wind shear and wind turbulence over the pulse volume are probably the dominant source of the reduced performance. The effects of wind shear and wind turbulence on the statistical description of doppler lidar data has been derived and calculated.

Frehlich, Rod↗

NASA NTRS1992

Wind Measurements from 15 to 50 Km with a Doppler Rayleigh Lidar

The possibility to measure the mean wind in the high stratosphere using a Doppler Rayleigh lidar was demonstrated in 1989, and the Observatory of Haute Province (44 deg N, 6 deg E). It was originally developed to cover the height range 25-60 km, a region where the radars cannot operate; therefore, the system was designed to cover altitudes where the signal is only due to the Rayleigh backscattering. The instrument is currently set up at the Center d'Essais des Landes (44 deg N, 1 deg W) where it operated during the Dynamic Adapted Network for the Atmosphere Campaign in 1990. As the contribution of the Mie scattering was very low during this period above southern France, we have obtained vertical wind profiles in the stratosphere down to 15 km. Since the eruption of the Pinatubo volcano in Jun. 1991, the contribution of Mie scattering has increased between 15 and 30 km and it was very difficult with the original system to obtain wind measurements below 30 km. We will show that by using the same method with slightly different characteristics of the system, it is possible to measure the wind in the presence of Mie scattering. The first experimental results are presented.

Garnier, A.↗

DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1998

Analysis of Lidar Remote Sensing Concepts

An orbiting coherent Doppler lidar for measuring winds is required to provide two basic pieces of data to the user community. The first is the line of sight wind velocity and the second is knowledge of the position at which the measurement was made. In order to obtain this data for targets of interest to the atmospheric community the instrument must also have a level of backscatter sensitivity sufficient to achieve the goal. Sensitivity analyses for the line of sight velocity and position requirements for two lidar instruments, one with a nadir angle of 30 deg. in a 300 km altitude, 58 deg. inclination orbit and the second for a 45 deg. nadir angle instrument in a 833 km altitude , 89 deg. inclination orbit are performed. The issues relating to the backscatter sensitivity of a coherent lidar have been well documented previously and are not discussed here other than to identify a space-specific issue that does not typically need to be considered for ground and aircraft based coherent lidars. Section 2 and appendices A1 and A2 document these sensitivity analyses. This contract was intended to develop requirements for a space shuttle (STS) based coherent lidar however, shortly after the award of this contract NASA MSFC won the SPARCLE program to put a coherent Doppler lidar on STS. Consequently much of the work conducted under this contract has been documented within the development of the SPARCLE project documentation. The relevant portions of the SPARCLE documentation are identified in section 3.0 and included in appendices A3 and A4. Section 4.0 briefly outlines miscellaneous other activities that occurred under this contract.

Spiers, Gray D.↗

NASA NTRS2000

Lidar Wind Measurements with the Goddard Lidar Observatory for Winds (GLOW)

We report on the development of GLOW (Goddard Lidar Observatory for Winds), a mobile Doppler lidar system which uses direct detection Doppler lidar techniques to measure wind profiles from the surface into the lower stratosphere. The system employs a Nd:YAG laser transmitter to measure winds using either aerosol backscatter at a wavelength of 1064 run or molecular backscatter at 355 nm. The system is modular in design to allow the incorporation of new technologies as they become available. GLOW is intended to be used as a deployable field system for studying atmospheric dynamics and transport and can also serve as a testbed to evaluate candidate technologies developed for use in future spaceborne systems. Finally it can be used for calibration/validation activities following launch of spaceborne wind lidar systems. A description of the mobile system is presented along with the first validated lidar wind profiles obtained with the system using a new molecular 'double edge' receiver.

Gentry, Bruce M.↗

DOE OSTI2022

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.

17 WIND ENERGY↗

NASA NTRS2013

Preliminary Observing System Simulation Experiments for Doppler Wind Lidars Deployed on the International Space Station

NASA Goddard Space Flight Center's Software Systems Support Office (SSSO) is participating in a multi-agency study of the impact of assimilating Doppler wind lidar observations on numerical weather prediction. Funded by NASA's Earth Science Technology Office, SSSO has worked with Simpson Weather Associates to produce time series of synthetic lidar observations mimicking the OAWL and WISSCR lidar instruments deployed on the International Space Station. In addition, SSSO has worked to assimilate a portion of these observations those drawn from the NASA fvGCM Nature Run into the NASA GEOS-DAS global weather prediction system in a series of Observing System Simulation Experiments (OSSEs). These OSSEs will complement parallel OSSEs prepared by the Joint Center for Satellite Data Assimilation and by NOAA's Atlantic Oceanographic and Meteorological Laboratory. In this talk, we will describe our procedure and provide available OSSE results.

Observing System Simulation↗

DOE OSTI2026

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

Coherent Doppler Wind Lidar Concepts for Global Scale Observations

Explore the source record for details and available documents.

fields weather climate↗

DOE OSTI2020

Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models

Abstract. Wake measurements of a scanning Doppler lidar mounted on the nacelle of a full-scale wind turbine during a wake-steering experiment were used for the characterization of the wake flow, the evaluation of the wake-steering set-up, and the validation of analytical wake models. Inflow-scanning Doppler lidars, a meteorological mast, and the supervisory control and data acquisition (SCADA) system of the wind turbine complemented the set-up. Results from the wake-scanning Doppler lidar showed an increase in the wake deflection with the yaw angle and that the wake deflection was not in all cases beneficial for the power output of a downstream turbine due to a bias of the inflow wind direction perceived by the yawed wind turbine and the wake-steering design implemented. Both observations could be reproduced with an analytical model that was initialized with the inflow measurements. Error propagation from the inflow measurements that were used as model input and the power coefficient of a waked wind turbine contributed significantly to the model uncertainty. Lastly, the span-wise cross section of the wake was strongly affected by wind veer, masking the effects of the yawed wind turbine on the wake cross sections.

17 WIND ENERGY↗

NASA NTRS2000

GLOW: The Goddard Lidar Observatory for Winds

GLOW (Goddard Lidar Observatory for Winds) is a mobile Doppler lidar system which uses direct detection Doppler lidar techniques to measure wind profiles from the surface into the lower stratosphere. The system is contained in a modified van to allow deployment in field operations. The lidar system uses a Nd:YAG laser transmitter to measure winds using either aerosol backscatter at 1064 nm or molecular backscatter at 355 nm. The receiver telescope is a 45 cm Dall-Kirkham which is fiber coupled to separate Doppler receivers, one optimized for the aerosol backscatter wind measurement and another optimized for the molecular backscatter wind measurement. The receivers are implementations of the 'double edge' technique and use high spectral resolution Fabry-Perot etalons to measure the Doppler shift. A 45 cm aperture azimuth-over-elevation scanner is mounted on the roof of the van to allow full sky access and a variety of scanning options. GLOW is intended to be used as a deployable field system for studying atmospheric dynamics and transport and can also serve as a testbed to evaluate candidate technologies developed for use in future spaceborne systems. In addition, it can be used for calibration/validation activities following launch of spaceborne wind lidar systems. A description of the mobile system is presented along with the examples of lidar wind profiles obtained with the system.

Gentry, Bruce M.↗

NASA NTRS2000

GLOW- The Goddard Lidar Observatory for Winds

Gentry, Bruce M.↗

NASA NTRS1999

Pointing Knowledge for SPARCLE and Space-Based Doppler Wind Lidars in General

The SPAce Readiness Coherent Lidar Experiment (SPARCLE) will fly on a space shuttle to demonstrate the use of a coherent Doppler wind lidar to accurately measure global tropospheric winds. To achieve the LOS (Line of Sight) accuracy goal of approx. m/s, the lidar system must be able to account for the orbiter's velocity (approx. 7750 m/s) and the rotational component of the earth's surface motion (approx. 450 m/s). For SPARCLE this requires knowledge of the attitude (roll, pitch and yaw) of the laser beam axis within an accuracy of 80 microradians. (approx. 15 arcsec). Since SPARCLE can not use a dedicated star tracker from its earth-viewing orbiter bay location, a dedicated GPS/INS (Global Positioning System/Inertial Navigation System) will be attached to the lidar instrument rack. Since even the GPS/INS has unacceptable drifts in attitude information, the SPARCLE team has developed a way to periodically scan the instrument itself to obtain less than 10 microradian (2 arcsec) attitude knowledge accuracy that can then be used to correct the GPS/INS output on a 30 minute basis.

Emmitt, G. D.↗

NASA NTRS1999

Backscatter Modeling at 2.1 Micron Wavelength for Space-Based and Airborne Lidars Using Aerosol Physico-Chemical and Lidar Datasets

Space-based and airborne coherent Doppler lidars designed for measuring global tropospheric wind profiles in cloud-free air rely on backscatter, beta from aerosols acting as passive wind tracers. Aerosol beta distribution in the vertical can vary over as much as 5-6 orders of magnitude. Thus, the design of a wave length-specific, space-borne or airborne lidar must account for the magnitude of 8 in the region or features of interest. The SPAce Readiness Coherent Lidar Experiment under development by the National Aeronautics and Space Administration (NASA) and scheduled for launch on the Space Shuttle in 2001, will demonstrate wind measurements from space using a solid-state 2 micrometer coherent Doppler lidar. Consequently, there is a critical need to understand variability of aerosol beta at 2.1 micrometers, to evaluate signal detection under varying aerosol loading conditions. Although few direct measurements of beta at 2.1 micrometers exist, extensive datasets, including climatologies in widely-separated locations, do exist for other wavelengths based on CO2 and Nd:YAG lidars. Datasets also exist for the associated microphysical and chemical properties. An example of a multi-parametric dataset is that of the NASA GLObal Backscatter Experiment (GLOBE) in 1990 in which aerosol chemistry and size distributions were measured concurrently with multi-wavelength lidar backscatter observations. More recently, continuous-wave (CW) lidar backscatter measurements at mid-infrared wavelengths have been made during the Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) experiment in 1995. Using Lorenz-Mie theory, these datasets have been used to develop a method to convert lidar backscatter to the 2.1 micrometer wavelength. This paper presents comparison of modeled backscatter at wavelengths for which backscatter measurements exist including converted beta (sub 2.1).

Srivastava, V.↗

NASA NTRS2011

Results of the Simulation and Assimilation of Doppler Wind Lidar Observations in Preparation for European Space Agency's Aeolus Mission

With the launch of the European Space Agency's Aeolus Mission in 2013, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for such missions is the development of the proper data assimilation methodology for handling such observations. Since no heritage measurements exist in space, the Joint Observing System Simulation Experiment (Joint OSSE) framework has been utilized to generate a realistic proxy dataset as a precursor to flight. These data are being used for the development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States including the Global Modeling and Assimilation Office (GMAO) at NASA/Goddard Space Flight Center and at the National Centers for Environmental Prediction (NOAA/NWS/NCEP) as an activity through the Joint Center for Satellite Data Assimilation. An update of this ongoing effort will be presented, including the methodology of proxy data generation, the limitations of the proxy data, the handling of line-of-sight wind measurements within the GSI, and the impact on both analyses and forecasts with the addition of the new data type.

McCarty, Will↗

NASA NTRS1985

NASA/MSFC FY-85 Atmospheric Processes Research Review

The two main areas of focus for the research program are global scale processes and mesoscale processes. Geophysical fluid processes, satellite doppler lidar, satellite data analysis, atmospheric electricity, doppler lidar wind research, and mesoscale modeling are among the topics covered.

Vaughan, W. W.↗

NASA NTRS1993

Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS)

This effort involves development of a calibrated, pulsed coherent CO2 Doppler lidar, followed by a carefully-planned and -executed program of multi-dimensional wind velocity and aerosol backscatter measurements from the NASA DC-8 research aircraft. The lidar, designated as the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS), will be applicable to two research areas. First, MACAWS will enable specialized measurements of atmospheric dynamical processes in the planetary boundary layer and free troposphere in geographic locations and over scales of motion not routinely or easily accessible to conventional sensors. The proposed observations will contribute fundamentally to a greater understanding of the role of the mesoscale, helping to improve predictive capabilities for mesoscale phenomena and to provide insights into improving model parameterizations of sub-grid scale processes within large-scale circulation models. As such, it has the potential to contribute uniquely to major, multi-institutional field programs planned for the mid 1990's. Second, MACAWS measurements can be used to reduce the degree of uncertainty in performance assessments and algorithm development for NASA's prospective Laser Atmospheric Wind Sounder (LAWS), which has no space-based instrument heritage. Ground-based lidar measurements alone are insufficient to address all of the key issues. To minimize costs, MACAWS is being developed cooperatively by the lidar remote sensing groups of the Jet Propulsion Laboratory, NOAA Wave Propagation Laboratory, and MSFC using existing lidar hardware and manpower resources. Several lidar components have already been exercised in previous airborne lidar programs (for example, MSFC Airborne Doppler Lidar System (ADLS) used in 1981,4 Severe Storms Wind Measurement Program; JPL Airborne Backscatter Lidar Experiment (ABLE) used in 1989,90 Global Backscatter Experiment Survey Missions). MSFC has been given responsibility for directing the overall program of instrument development and scientific measurement. The focus of current research and plans for next year are presented.

Rhothermel, Jeffry↗