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At least 433 records · Page 24

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↗

Coherent Doppler Wind Lidar Technology for Space Based Wind Measurements Including SPARCLE

It has been over 30 years since coherent lidar systems first measured wind velocity, and over 20 years since the "ultimate application" of measuring Earth's winds from space was conceived. Coherent or heterodyne optical detection involves the combination (or mixing) of the returned optical field with a local oscillator (LO) laser's optical field on the optical detector. This detection technique yields the benefits of dramatically improved signal-to-noise ratios; insensitivity to detector noise, background light and multiply scattered light; reduction of the returned signal's dynamic range; and preservation of the optical signal spectrum for electronic and computer processing. (Note that lidar systems are also referred to as optical radar, laser radar, and LADAR systems.) Many individuals, agencies, and countries have pursued the goal of space-based wind measurements through technology development, experiments, field campaigns and studies.

Kavaya, Michael J.↗

Simulating Wake Vortex Detection with the Sensivu Doppler Wind Lidar Simulator

In support of NASA's Atmospheric Environment Safety Technologies NRA research topic on Wake Vortex Hazard Investigation, Aerospace Innovations (AI) investigated a set of techniques for detecting wake vortex hazards from arbitrary viewing angles, including axial perspectives. This technical report describes an approach to this problem and presents results from its implementation in a virtual lidar simulator developed at AI. Threedimensional data volumes from NASA's Terminal Area Simulation System (TASS) containing strong turbulent vortices were used as the atmospheric domain for these studies, in addition to an analytical vortex model in 3-D space. By incorporating a third-party radiative transfer code (BACKSCAT 4), user-defined aerosol layers can be incorporated into atmospheric models, simulating attenuation and backscatter in different environmental conditions and altitudes. A hazard detection algorithm is described that uses a twocomponent spectral model to identify vortex signatures observable from arbitrary angles.

Ramsey, Dan↗

Silicon Photonic Transceiver for Spacecraft Navigational Lidar

NASA is developing an entry, descent, and landing (EDL) lidar system, the Navigation Doppler Lidar (NDL), for high-precision landing on the Moon, Mars, and beyond. The current flight NDL systems use 1550 nm fiber-optic components for frequency-modulated continuous wave (FMCW) ranging beyond 5 km, but have reduced performance under vibrational and thermal stresses during EDL. Here we describe recent efforts to develop a breadboard silicon photonic optical transceiver for integration into NDL to reduce instrument size and improve robustness to environment and demonstrate the optical balanced receiver performance during testing with the breadboard NDL unit. Initial testing shows improved suppression of common mode noise by 25 dB over the current receiver, but a 10 dB reduction in signal to noise ratio (SNR) resulting from coupling losses from fiber to the on-chip waveguides. Future work will target reduced coupling loss, hermetic packaging, and co-integration of a single sideband suppressed carrier modulator into the same chip.

Photonic Integrated Circuits↗

Using the GEOS 5 Nature Run to Simulate 2053 nm Coherent Doppler Wind Lidar Observations

Wind observations are a critical part of the current global observation system used for Numerical Weather Prediction (NWP). Wind lidars have been cited as precise instruments that can provide 3-dimensional wind measurements. Several studies have conducted observing system experiments (OSEs) with existing lidar observations or observing system simulation experiments (OSSEs) with simulated lidar observations highlighting the benefits of wind lidar measurements to NWP. Previous studies using simulated lidar observations have typically tied aerosol optical properties to functions of relative humidity instead of to aerosol properties. A methodology is presented for simulating wind measurements from a novel 2053 nm lidar using aerosol properties derived using the GEOS-5 Nature Run, along with estimating winds derived from cloud information. Some assumptions regarding aerosol scattering and the distribution of clouds are explored, along with the role of observation weighting, and implications for representativeness error. Results from a preliminary OSSE are presented highlighting the importance of assumptions used to derive data from cloud returns and aerosol scattering. While a longer duration study is required, results show a general reduction in analysis error when lidar measurements are ingested.

Bryan M. Karpowicz↗

Using the GEOS 5 Nature Run to Simulate 2053 nm Coherent Doppler Wind Lidar Observations

Wind observations are a critical part of the current global observation system used for Numerical Weather Prediction (NWP). Wind lidars have been cited as precise instruments that can provide 3-dimensional wind measurements. Several studies have conducted observing system experiments (OSEs) with existing lidar observations or observing system simulation experiments (OSSEs) with simulated lidar observations highlighting the benefits of wind lidar measurements to NWP. Previous studies using simulated lidar observations have typically tied aerosol optical properties to functions of relative humidity instead of to aerosol properties. A methodology is presented for simulating wind measurements from a novel 2053 nm lidar using aerosol properties derived using the GEOS-5 Nature Run, along with estimating winds derived from cloud information. Some assumptions regarding aerosol scattering and the distribution of clouds are explored, along with the role of observation weighting, and implications for representativeness error. Results from a preliminary OSSE are presented highlighting the importance of assumptions used to derive data from cloud returns and aerosol scattering. While a longer duration study is required, results show a general reduction in analysis error when lidar measurements are ingested.

Bryan M. Karpowicz↗

TRACER-Coastal Urban Boundary-Layer Interactions with Convection (TRACER-CUBIC) Field Campaign Report

To better understand the complicated web of processes governing convective cloud life cycle and aerosol-convection interactions, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility supported deployment of a variety of advanced atmospheric measurement systems to the greater Houston, Texas, area from 1 October 2021 to 30 September 2022 as part of the Tracking Aerosol Convection Interactions Experiment (TRACER). Houston was selected as a study area because isolated convection and a variety of aerosol conditions are common in this region. This one-year ARM Mobile Facility (AMF) deployment featured a four-month intensive operational period (IOP) during summer 2022 (1 June–30 September). The ARM instrumentation was deployed at three sites along an east-west transect from La Porte, Texas to an ancillary site in a less-polluted rural region southwest of downtown Houston (Figure 1). At the La Porte Site, which is located near the Houston ship channel in an area that experiences significant pollution, the first ARM Mobile Facility (AMF1) was deployed. During the IOP, the ARM tethered balloon system (TBS) operated at the ancillary site. The second-generation C-Band Scanning ARM Precipitation Radar (CSAPR) operated near Pearland, Texas, roughly halfway between the Laporte and ancillary sites. As part of the TRACER- Coastal Urban Boundary-Layer Interactions with Convection (CUBIC) project, three boundary-layer profiling systems) were deployed along a north-south transect spanning from the University of Houston Coastal Center to the Aldine site north of downtown Houston (also blue dot in Figure 1) during the TRACER IOP. These systems included the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory CLAMPS2 (C2), which was deployed at the UHCC, the University of Wisconsin SPARC, which was deployed at the ARM CSAPR site near Pearland (orange diamond in middle of map in Figure 1), and the University of Oklahoma CLAMPS1 (C1), which was deployed at Aldine. These three systems have been successfully operated in various field campaigns, providing data sets that collectively offer new insights into atmospheric-boundary-layer (ABL) processes, sea-breeze (SB) circulations, and convection initiation (CI). For the TRACER IOP window, these systems ran continuously between 1 June and 26 September, 2022. Due to commitments to NOAA projects, the Doppler lidar at the UHCC site was not available until 24 June 2022. The CLAMPS and SPARC profiling systems are self-contained platforms that have benefited from several years of development and deployment. Instruments and data processing were maintained remotely, which made the 4-month deployment for the TRACER-CUBIC IOP period possible. The same basic instrument configuration comprises each system: a scanning Doppler wind lidar for flow characterization and passive profiler(s) for characterizing planetary-boundary-layer (PBL) thermodynamic properties. Each platform includes a Halo Streamline Doppler wind lidar, an Atmospheric Emitted Radiance Interferometer (AERI), and a surface meteorology station. CLAMPS1 and CLAMPS2 each also include a microwave radiometer (MWR, Figure 1d). The TRACER-CUBIC hypotheses included (i) Interactions of SB and urban circulations and how they affect the PBL structure in the Houston environment, causing spatially (horizontally and vertically) and temporally highly variable flow patterns, (ii) heat, moisture, and aerosol transport and mixing depend on these flow dynamics, and (iii) an improved understanding of the flow patterns and PBL structure are critical for investigating the processes leading to CI. To test these hypotheses, the project aimed at (i) characterizing SB circulations and their impacts on the diurnal evolution of the structure of the ABL, (ii) studying the evolution of Houston’s complex urban boundary layer, and (iii) identifying effects of urban-induced circulations on pre-convective environments. TRACER-CUBIC observations generally provide good coverage during the summer IOP. Initial screening of the data indicates a good number of cases with bay-breeze (BB) and/or SB signatures, local CI, and interesting boundary-layer features such as strong nocturnal low-level jets (LLJs, Table 1). The numbers listed in rows 3-5 in this table will be further updated as part of ongoing in-depth analyses and systematic identification of local circulations and CI events. More detailed information about the data availability and quality for each instrument is provided in the “readme” files that were submitted to the ARM Data Center along with each archived data sets. These “readme” files also provide instrument descriptions, information about the data collection and processing procedures, data formats, and any additional information relevant for further data analysis.

54 ENVIRONMENTAL SCIENCES↗

AWAKEN Site H HALO XR Lidar / Raw Data

These data are scanning Doppler lidar measurements from the deployment of a HALO XR at site H. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY↗

AWAKEN Site H HALO XR Lidar / Raw Data

These data are scanning Doppler lidar measurements from the deployment of a HALO XR at AWAKEN site H. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY↗

Lidar / Processed Data

These data include scanning Doppler lidar measurements from the deployment of the PNNL HALO XR+ (s/n 184) at the Nantucket site. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. The data are provided in NetCDF.

17 WIND ENERGY↗

Evaluation of airborne lidar wind measurements

The verification of the Doppler lidar wind measurement is continued. The in situ measurements on a 500 meter tall tower are used to check the lidar determined winds (flight 4), followed by other tests applied to the extensive data sets of flights 19 and 21. After checking for possible software errors in the processing programs, the inconsistency was not solved. The source of the errors appears to be the uncertainty in the calculation of the contribution of the aircraft motion to the lidar measured line of sight speed. Possible techniques for estimating the aircraft motion errors from the aircraft data are investigated.

Carroll, J. J.↗

Lidar meteorology

Current and future lidar applications to meteorological studies are presented. In water vapor, temperature, and pressure measurement applications, differential absorption lidar (DIAL) techniques are used, employing a minimum of two wavelengths. The DIAL technique has proven particularly accurate in pressure measurements. For wind measurements, lidar investigations generally use the Doppler shifting of laser light backscattered from aerosols, and a pulsed low-power CO2 Doppler lidar is being developed for airborne platform applications. At visible to near-infrared wavelengths, spatial distribution of aerosol and clouds can be obtained from lidar, and this information can help determine such atmospheric parameters as mixed layer height and cloud height distributions. A Shuttle lidar facility, being developed for the end of the 1980's, will enable laser remote sensing techniques to be applied to studies of the lower atmosphere.

Browell, E. V.↗

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

We demonstrate the combination of three Doppler lidars (DLs), a water vapor differential absorption lidar and a temperature rotational Raman lidar for the investigation of the interactions between the land-surface and the atmospheric boundary layer. This combination of scanning lidars was operated for the first time during the Land-Atmosphere Feedback Experiment at the Atmospheric Radiation Measurement program's Southern Great Plain site, Oklahoma, USA, in August 2017, and provided simultaneous surface layer profiles of horizontal wind, humidity and temperature. The horizontal wind profiles were determined using the dual-Doppler method with two DLs. The scans were performed above four towers providing atmospheric variables and fluxes. These combined lidar data allowed for the estimation of the friction velocity as well as the surface latent and sensible heat fluxes. For this purpose, profiles calculated with Monin-Obukhov similarity theory were fitted with the Levenberg-Marquardt nonlinear least squares curve-fitting method to the measured surface-layer lidar profiles. We present case studies of three 50-min periods to illustrate the new method. The measurements resulted in friction velocities of 0.31, 0.29, and 0.38 ms –1 , sensible surface heat fluxes of 312.1, 234.1, and 183.3 Wm –2 and latent surface heat fluxes of 251.8, 227.3, and 274.4 Wm –2 . These values were compared with the in-situ measurements of the towers. Considering the sampling differences and the error analyses, the results agree within 25.1%, 42.5%, and 28.8%, respectively, demonstrating that this synergy of scanning active remote sensing systems can be used to derive surface fluxes with reasonable accuracy.

54 ENVIRONMENTAL SCIENCES↗

Performance of mean-frequency estimators for Doppler radar and lidar

The performance of mean-frequency estimators for Doppler radar and lidar measurements of winds is presented in terms of two basic parameters: Phi, the ratio of the average signal energy per estimate to the spectral noise level; and Omega, which is proportional to the number of independent samples per estimate. For fixed Phi and Omega, the Cramer-Rao bound (CRB) (theoretical best performance) for unbiased estimators of mean frequency (normalized by the spectral width of the signal), signal power, and spectral width are essentially independent of the number of data samples M. For large Phi, the estimators of mean frequency are unbiased and the performance is independent of M. The spectral domain estimators and covariance based estimators are bounded by the approximate period of M. The spectral domain estimators and covariance based estimators are bounded by the approximate periodogram CRB. The standard deviation of the maximum-likelihood estimator approaches the exact CRB, which can be more than a factor of 2 better than the performance of the spectral domain estimators or covariance-based estimators for typical Omega. For small Phi, the estimators are biased due to the effects of the uncorrelated noise (white noise), which results in uniformly distributed 'bad' estimates. The fraction of bad estimates is a function of Phi and M with weak dependence on the parameter Omega. Simple empirical models describe the standard deviation of the good estimates and the fraction of bad estimates. For Doppler lidar and for large Phi, better performance is obtained by using many low-energy pulses instead of one pulse with the same total energy. For small Phi, the converse is true.

Frehlich, R. G.↗