High-resolution Doppler Lidar Research Articles

Comparison of turbulence measurements by a CSAT3B sonic anemometer and a high-resolution bistatic Doppler lidar

Abstract. Accurate measurements of turbulence statistics in the atmosphere are important for eddy-covariance measurements, wind energy research, and the validation of atmospheric numerical models. Sonic anemometers are widely used for these applications. However, these instruments are prone to probe-induced flow distortion effects, and the magnitude of the resulting errors has been debated due to the lack of an absolute reference instrument under field conditions. Here, we present the results of an intercomparison experiment between a CSAT3B sonic anemometer and a high-resolution bistatic Doppler lidar, which is inherently free of any flow distortion. This novel remote sensing instrument has otherwise very similar spatial and temporal sampling characteristics to the sonic anemometer and hence served as a reference for this comparison. The presented measurements were carried out over flat homogeneous terrain at a measurement height of 30 m. We provide a comparative statistical analysis of the resulting mean wind velocities, the standard deviations of the vertical wind speed and the friction velocity and investigate the reasons for the observed deviations based on the turbulence spectra and co-spectra. Our results show an agreement of the mean wind velocity measurements and the standard deviations of the vertical wind speed with a comparability of 0.082 and 0.020 m s−1, respectively. Biases for these two quantities were 0.003 and 0.012 m s−1, respectively. Slightly larger differences were observed for friction velocity. Analysis of the corresponding co-spectra showed that the CSAT3B underestimates this quantity systematically by about 3 % on average as a result of co-spectral losses in the frequency range between 0.1 and 5 s−1. We also found that an angle-of-attack-dependent transducer-shadowing correction does not improve the agreement between the CSAT3B and the Physikalisch-Technische Bundesanstalt (PTB) lidar effectively.

Sensitivity of urban boundary layer simulation to urban canopy models and PBL schemes in Beijing

Mesoscale models with urban canopy models (UCM) have been increasingly used to study urban boundary layer processes. Using the data from a high-resolution Doppler lidar, automatic weather stations (AWS), and a flux tower located in the urban site, we assessed the performance of the urbanized Weather Research and Forecasting (WRF) model through three urban canopy models (the single-layer UCM, and the multi-layer BEP and BEM models) and four planetary boundary layer (PBL) schemes (the non-local first-order YSU, SH and ACM2 schemes, as well as the local TKE-based BouLac scheme) for one cloudy and one clear sky days. Results show that the WRF-Urban generally overestimates the sensible heat flux and underestimates the latent heat flux. The simulated 2-m temperature and 10-m wind speed are more sensitive to UCMs than to PBL schemes. Using the BouLac PBL scheme and the multi-layer BEP generates the best agreement with AWS observations. Simulations with the multi-layer BEM produce the highest mixing-layer heights. The convective boundary layer (CBL) from the single-layer UCM experiment develops at the slowest pace when compared with other two multi-layer UCMs. When the single-layer UCM is used, simulations with the non-local mixing YSU, SH and ACM2 schemes perform better than the TKE-based scheme (BouLac) for representing the CBL structure. Additionally, the scale-aware SH scheme considering the effect of grid resolution on the vertical dimension, simulates the potential temperature profiles that are closest to observations.

Evaluating and Improving NWP Forecast Models for the Future: How the Needs of Offshore Wind Energy Can Point the Way

AbstractTo advance the understanding of meteorological processes in offshore coastal regions, the spatial variability of wind profiles must be characterized and uncertainties (errors) in NWP model wind forecasts quantified. These gaps are especially critical for the new offshore wind energy industry, where wind profile measurements in the marine atmospheric layer spanned by wind turbine rotor blades, generally 50–200 m above mean sea level (MSL), have been largely unavailable. Here, high-quality wind profile measurements were available every 15 min from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL)’s high-resolution Doppler lidar (HRDL) during a monthlong research cruise in the Gulf of Maine for the 2004 New England Air Quality Study. These measurements were compared with retrospective NWP model wind forecasts over the area using two NOAA forecast-modeling systems [North American Mesoscale Forecast System (NAM) and Rapid Refresh (RAP)]. HRDL profile measurements quantified model errors, including their dependence on height above sea level, diurnal cycle, and forecast lead time. Typical model wind speed errors were ∼2.5 m s−1, and vector-wind errors were ∼4 m s−1. Short-term forecast errors were larger near the surface—30% larger below 100 m than above and largest for several hours after local midnight (biased low). Longer-term, 12-h forecasts had the largest errors after local sunset (biased high). At more than 3-h lead times, predictions from finer-resolution models exhibited larger errors. Horizontal variability of winds, measured as the ship traversed the Gulf of Maine, was significant and raised questions about whether modeled fields, which appeared smooth in comparison, were capturing this variability. If not, horizontal arrays of high-quality, vertical-profiling devices will be required for wind energy resource assessment offshore. Such measurement arrays are also needed to improve NWP models.

Assessment of NWP Forecast Models in Simulating Offshore Winds through the Lower Boundary Layer by Measurements from a Ship-Based Scanning Doppler Lidar

Evaluation of model skill in predicting winds over the ocean was performed by comparing retrospective runs of numerical weather prediction (NWP) forecast models to shipborne Doppler lidar measurements in the Gulf of Maine, a potential region for U.S. coastal wind farm development. Deployed on board the NOAA R/V Ronald H. Brown during a 2004 field campaign, the high-resolution Doppler lidar (HRDL) provided accurate motion-compensated wind measurements from the water surface up through several hundred meters of the marine atmospheric boundary layer (MABL). The quality and resolution of the HRDL data allow detailed analysis of wind flow at heights within the rotor layer of modern wind turbines and data on other critical variables to be obtained, such as wind speed and direction shear, turbulence, low-level jet properties, ramp events, and many other wind-energy-relevant aspects of the flow. This study will focus on the quantitative validation of NWP models’ wind forecasts within the lower MABL by comparison with HRDL measurements. Validation of two modeling systems rerun in special configurations for these 2004 cases—the hourly updated Rapid Refresh (RAP) system and a special hourly updated version of the North American Mesoscale Forecast System [NAM Rapid Refresh (NAMRR)]—are presented. These models were run at both normal-resolution (RAP, 13 km; NAMRR, 12 km) and high-resolution versions: the NAMRR-CONUS-nest (4 km) and the High-Resolution Rapid Refresh (HRRR, 3 km). Each model was run twice: with (experimental runs) and without (control runs) assimilation of data from 11 wind profiling radars located along the U.S. East Coast. The impact of the additional assimilation of the 11 profilers was estimated by comparing HRDL data to modeled winds from both runs. The results obtained demonstrate the importance of high-resolution lidar measurements to validate NWP models and to better understand what atmospheric conditions may impact the accuracy of wind forecasts in the marine atmospheric boundary layer. Results of this research will also provide a first guess as to the uncertainties of wind resource assessment using NWP models in one of the U.S. offshore areas projected for wind plant development.

The Mean and Turbulent Properties of a Wildfire Convective Plume

AbstractThe time-mean and time-varying smoke and velocity structure of a wildfire convective plume is examined using a high-resolution scanning Doppler lidar. The mean plume is shown to exhibit the archetypal form of a bent-over plume in a crosswind, matching the well-established Briggs plume-rise equation. The plume cross section is approximately Gaussian and the plume radius increases linearly with height, consistent with plume-rise theory. The Briggs plume-rise equation is subsequently inverted to estimate the mean fire-generated sensible heat flux, which is found to be 87 kW m−2. The mean radial velocity structure of the plume indicates flow convergence into the plume base and regions of both convective overshoot and sinking flow in the upper plume. The updraft speed in the lower plume is estimated to be 13.5 m s−1 by tracking the leading edge of a convective element ascending through the plume. The lidar data also reveal aspects of entrainment processes during the plume rise. For example, the covariation of the radial velocity and smoke perturbations are shown to dilute the smoke concentration with height.

The POWER Experiment: Impact of Assimilation of a Network of Coastal Wind Profiling Radars on Simulating Offshore Winds in and above the Wind Turbine Layer

AbstractDuring the summer of 2004 a network of 11 wind profiling radars (WPRs) was deployed in New England as part of the New England Air Quality Study (NEAQS). Observations from this dataset are used to determine their impact on numerical weather prediction (NWP) model skill at simulating coastal and offshore winds through data-denial experiments. This study is a part of the Position of Offshore Wind Energy Resources (POWER) experiment, a Department of Energy (DOE) sponsored project that uses National Oceanic and Atmospheric Administration (NOAA) models for two 1-week periods to measure the impact of the assimilation of observations from 11 inland WPRs. Model simulations with and without assimilation of the WPR data are compared at the locations of the inland WPRs, as well as against observations from an additional WPR and a high-resolution Doppler lidar (HRDL) located on board the Research Vessel Ronald H. Brown (RHB), which cruised the Gulf of Maine during the NEAQS experiment. Model evaluation in the lowest 2 km above the ground shows a positive impact of the WPR data assimilation from the initialization time through the next five to six forecast hours at the WPR locations for 12 of 15 days analyzed, when offshore winds prevailed. A smaller positive impact at the RHB ship track was also confirmed. For the remaining three days, during which time there was a cyclone event with strong onshore wind flow, the assimilation of additional observations had a negative impact on model skill. Explanations for the negative impact are offered.

Evaluation of Modeled Stratocumulus-Capped Boundary Layer Turbulence with Shipborne Data

Abstract Numerically modeled turbulence simulated by the Advanced Research Weather Research and Forecasting Model (ARW) is evaluated with turbulence measurements from NOAA’s high-resolution Doppler lidar on the NOAA Research Vessel Ronald H. Brown during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study—Regional Experiment (VOCALS-Rex) field program. A nonprecipitating nocturnal marine stratocumulus case is examined, and a nudging technique is applied to allow turbulence to spin up and come into a statistically stationary state with the initial observed cloud field. This “stationary” state is then used as the initial condition for the subsequent free-running simulation. The comparison shows that the modeled turbulence is consistently weaker than that observed. For the same resolution, the turbulence becomes stronger, especially for the horizontal component, as the length of the horizontal domain increases from 6.4 to 25.6 km. Analysis of the power spectral density shows that, even for the largest domain, the horizontal component of the turbulence is limited by the upper limit of the domain size; supporting evidence from past studies is provided. Results suggest that convergence is expected for (i) energy spectra of turbulence with a sufficiently large domain and (ii) liquid water path with an adequately large domain and fine resolution. Additional tests are performed by changing momentum advection and turning off subgrid-scale diffusion. These exhibit more significant changes in turbulence characteristics compared to the sensitivity to domain size and resolution, suggesting that the model behavior is essentially established by the configuration of the model dynamics and physics and that the simulation only gradually improves when domain size and resolution are increased.

High-Resolution Doppler Lidar Observations of Transient Downslope Flows and Rotors

Abstract The authors present observations of the temporal evolution of downslope windstorms with rotors and internal hydraulic jumps of unprecedented detail and spatiotemporal coverage. The observations were carried out by means of a coherent Doppler lidar in the lee of the southern Sierra Nevada range during the sixth intensive observational period of the Terrain-induced Rotor Experiment (T-REX) in 2006. Two representative flow regimes are analyzed and juxtaposed in this paper. The first case shows pulses of high-momentum air that propagate eastward through the valley with an internal hydraulic jump on the leading edge. The region downstream of the transient internal hydraulic jump is characterized by turbulence but no coherent rotor circulation was observed. During the second case, the strongest windstorm of the field campaign T-REX occurred. The observed features of this event resemble the classical notion of a rotor. Altogether, the Doppler lidar observations of both downslope flow events reveal a complex, turbulent flow that is highly transient, intermittent, 3D, and interacts with a significant along-valley flow.

Wind Energy Meteorology: Insight into Wind Properties in the Turbine-Rotor Layer of the Atmosphere from High-Resolution Doppler Lidar

Addressing the need for high-quality wind information aloft in the layer occupied by turbine rotors (~30–150 m above ground level) is one of many significant challenges facing the wind energy industry. Without wind measurements at heights within the rotor sweep of the turbines, characteristics of the flow in this layer are unknown for wind energy and modeling purposes. Since flow in this layer is often decoupled from the surface, near-surface measurements are prone to errant extrapolation to these heights, and the behavior of the near-surface winds may not reflect that of the upper-level flow.

Wind energy meteorology: Insight into wind properties in the turbine-rotor layer of the atmosphere from high-resolution Doppler lidar

Wind energy meteorology: Insight into wind properties in the turbine-rotor layer of the atmosphere from high-resolution Doppler lidar

Doppler Lidar–Based Wind-Profile Measurement System for Offshore Wind-Energy and Other Marine Boundary Layer Applications

AbstractAccurate measurement of wind speed profiles aloft in the marine boundary layer is a difficult challenge. The development of offshore wind energy requires accurate information on wind speeds above the surface at least at the levels occupied by turbine blades. Few measured data are available at these heights, and the temporal and spatial behavior of near-surface winds is often unrepresentative of that at the required heights. As a consequence, numerical model data, another potential source of information, are essentially unverified at these levels of the atmosphere. In this paper, a motion-compensated, high-resolution Doppler lidar–based wind measurement system that is capable of providing needed information on offshore winds at several heights is described. The system has been evaluated and verified in several ways. A sampling of data from the 2004 New England Air Quality Study shows the kind of analyses and information available. Examples include time–height cross sections, time series, profiles, and distributions of quantities such as winds and shear. These analyses show that there is strong spatial and temporal variability associated with the wind field in the marine boundary layer. Winds near the coast show diurnal variations, and frequent occurrences of low-level jets are evident, especially during nocturnal periods. Persistent patterns of spatial variability in the flow field that are due to coastal irregularities should be of particular concern for wind-energy planning, because they affect the representativeness of fixed-location measurements and imply that some areas would be favored for wind-energy production whereas others would not.

A Comparison of Higher-Order Vertical Velocity Moments in the Convective Boundary Layer from Lidar with In Situ Measurements and Large-Eddy Simulation

We have analyzed measurements of vertical velocity w statistics with the NOAA high resolution Doppler lidar (HRDL) from about 390 m above the surface to the top of the convective boundary layer (CBL) over a relatively flat and uniform agricultural surface during the Lidars-in-Flat-Terrain (LIFT) experiment in 1996. The temporal resolution of the zenith-pointing lidar was about 1 s, and the range-gate resolution about 30 m. Vertical cross-sections of w were used to calculate second- to fourth-moment statistics of w as a function of height throughout most of the CBL. We compare the results with large-eddy simulations (LES) of the CBL and with in situ aircraft measurements. A major cause of the observed case-to-case variability in the vertical profiles of the higher moments is differences in stability. For example, for the most convective cases, the skewness from both LES and observations changes more with height than for cases with more shear, with the observations changing more with stability than the LES. We also found a decrease in skewness, particularly in the upper part of the CBL, with an increase in LES grid resolution.

Stable Boundary Layer Depth from High-Resolution Measurements of the Mean Wind Profile

Abstract The depth h of the stable boundary layer (SBL) has long been an elusive measurement. In this diagnostic study the use of high-quality, high-resolution (Δz = 10 m) vertical profile data of the mean wind U(z) and streamwise variance σu2(z) is investigated to see whether mean-profile features alone can be equated with h. Three mean-profile diagnostics are identified: hJ, the height of maximum low-level-jet (LLJ) wind speed U in the SBL; h1, the height of the first zero crossing or minimum absolute value of the magnitude of the shear ∂U/∂z profile above the surface; and h2, the minimum in the curvature ∂2U/∂z2 profile. Boundary layer BL here is defined as the surface-based layer of significant turbulence, so the top of the BL was determined as the first significant minimum in the σu2(z) profile, designated as hσ. The height hσ was taken as a reference against which the three mean-profile diagnostics were tested. Mean-wind profiles smooth enough to calculate second derivatives were obtained by averaging high-resolution Doppler lidar profile data, taken during two nighttime field programs in the Great Plains, over 10-min intervals. Nights are chosen for study when the maximum wind speed in the lowest 200 m exceeded 5 m s−1 (i.e., weak-wind, very stable BLs were excluded). To evaluate the three diagnostics, data from the 14-night sample were divided into three profile shapes: Type I, a traditional LLJ structure with a distinct maximum or “nose,” Type II, a “flat” structure with constant wind speed over a significant depth, and Type III, having a layered structure to the shear and turbulence in the lower levels. For Type I profiles, the height of the jet nose hJ, which coincided with h1 and h2 in this case, agreed with the reference SBL depth to within 5%. The study had two major results: 1) among the mean-profile diagnostics for h, the curvature depth h2 gave the best results; for the entire sample, h2 agreed with hσ to within 12%; 2) considering the profile shapes, the layered Type III profiles gave the most problems. When these profiles could be identified and eliminated from the sample, regression and error statistics improved significantly: mean relative errors of 8% for hJ and h1, and errors of <5% for h2, were found for the sample of only Type I and II profiles.

Doppler Lidar Estimation of Mixing Height Using Turbulence, Shear, and Aerosol Profiles

Abstract The concept of boundary layer mixing height for meteorology and air quality applications using lidar data is reviewed, and new algorithms for estimation of mixing heights from various types of lower-tropospheric coherent Doppler lidar measurements are presented. Velocity variance profiles derived from Doppler lidar data demonstrate direct application to mixing height estimation, while other types of lidar profiles demonstrate relationships to the variance profiles and thus may also be used in the mixing height estimate. The algorithms are applied to ship-based, high-resolution Doppler lidar (HRDL) velocity and backscattered-signal measurements acquired on the R/V Ronald H. Brown during Texas Air Quality Study (TexAQS) 2006 to demonstrate the method and to produce mixing height estimates for that experiment. These combinations of Doppler lidar–derived velocity measurements have not previously been applied to analysis of boundary layer mixing height—over the water or elsewhere. A comparison of the results to those derived from ship-launched, balloon-radiosonde potential temperature and relative humidity profiles is presented.

Nocturnal boundary layer characteristics and land breeze development in Houston, Texas during TexAQS II

The nocturnal boundary layer in Houston, Texas was studied using a high temporal and vertical resolution tethersonde system on four nights during the Texas Air Quality Study II (TexAQS II) in August and September 2006. The launch site was on the University of Houston campus located approximately 4 km from downtown Houston. Of particular interest was the evolution of the nocturnal surface inversion and the wind flows within the boundary layer. The land–sea breeze oscillation in Houston has important implications for air quality as the cycle can impact ozone concentrations through pollutant advection and recirculation. The results showed that a weakly stable surface inversion averaging in depth between 145 and 200 m AGL formed on each of the experiment nights, typically within 2–3 h after sunset. Tethersonde vertical winds were compared with two other Houston data sets (High Resolution Doppler Lidar and radar wind profiler) from locations near the coastline and good agreement was found, albeit with a temporal lag at the tethersonde site. This comparison revealed development of a land breeze on three nights which began near the coastline and propagated inland both horizontally and vertically with time. The vertical temperature structure was significantly modified on one night at the tethersonde site after the land breeze wind shift, exhibiting near-adiabatic profiles below 100 m AGL.

Mesoscale Moisture Transport by the Low-Level Jet during the IHOP Field Experiment

Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.

Horizontal-Velocity and Variance Measurements in the Stable Boundary Layer Using Doppler Lidar: Sensitivity to Averaging Procedures

AbstractQuantitative data on turbulence variables aloft—above the region of the atmosphere conveniently measured from towers—have been an important but difficult measurement need for advancing understanding and modeling of the stable boundary layer (SBL). Vertical profiles of streamwise velocity variances obtained from NOAA’s high-resolution Doppler lidar (HRDL), which have been shown to be approximately equal to turbulence kinetic energy (TKE) for stable conditions, are a measure of the turbulence in the SBL. In the present study, the mean horizontal wind component U and variance σ2u were computed from HRDL measurements of the line-of-sight (LOS) velocity using a method described by Banta et al., which uses an elevation (vertical slice) scanning technique. The method was tested on datasets obtained during the Lamar Low-Level Jet Project (LLLJP) carried out in early September 2003, near the town of Lamar in southeastern Colorado.This paper compares U with mean wind speed obtained from sodar and sonic anemometer measurements. The results for the mean U and mean wind speed measured by sodar and in situ instruments for all nights of LLLJP show high correlation (0.71–0.97), independent of sampling strategies and averaging procedures, and correlation coefficients consistently >0.9 for four high-wind nights, when the low-level jet speeds exceeded 15 m s−1 at some time during the night. Comparison of estimates of variance, on the other hand, proved sensitive to both the spatial and temporal averaging parameters. Several series of averaging tests are described, to find the best correlation between TKE calculated from sonic anemometer data at several tower levels and lidar measurements of horizontal-velocity variance σ2u. Because of the nonstationarity of the SBL data, the best results were obtained when the velocity data were first averaged over intervals of 1 min, and then further averaged over 3–15 consecutive 1-min intervals, with best results for the 10- and 15-min averaging periods. For these cases, correlation coefficients exceeded 0.9. As a part of the analysis, Eulerian integral time scales (τ) were estimated for the four high-wind nights. Time series of τ through each night indicated erratic behavior consistent with the nonstationarity. Histograms of τ showed a mode at 4–5 s, but frequent occurrences of larger τ values, mostly between 10 and 100 s.

Remote sensing of the nocturnal boundary layer for wind energy applications.

The fine temporal and spatial resolution of Doppler lidar observations has been highly effective in the study of wind and turbulence dynamic in the nocturnal boundary layer during Lamar Low-Level Project in 2003. The High-Resolution Doppler Lidar (HRDL), designed and developed at the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), measures range-resolved profiles of line-of sight (LOS) Doppler velocity and aerosol backscatter with a pulse repetition frequency of 200 Hz, velocity precision about 10 cm s-1, and a very narrow beam width. The majority of the lidar-measured wind speed and variance profiles were derived using a vertical-scan mode and the application of a vertical binning technique. The profile data were used to calculate quantities important for wind energy applications, including turbulence intensity, wind and directional shear through the layer of the turbine rotor. Profiles of all quantities show a strong variation with height. The mean wind fields, the turbulence, and turbulence intensities show a good agreement with sonic anemometer sodar high confidence (high SNR) measurements. The ability of HRDL to provide continuous information about wind and turbulence conditions at the turbine height and above the range of the tower measurements made HRDL as a powerful instrument for studies of the nighttime boundary layer features. Such information is needed as turbine rotors continue to rise higher into the boundary layer.

Doppler lidar measurements of the great plains low-level jet: applications to wind energy

The southerly low-level jet (LLJ) of the Great Plains of the United States is a recurrent flow feature of the nighttime boundary layer of the region, which has been identified as a region of high potential for wind energy. The acceleration of the LLJ after sunset produces an enhancement of the wind speed over daytime values, and provides a dependable resource for wind energy. On the negative side, occasional bursts of strong turbulence may be generated that can be of just the right frequency to excite strong oscillatory response in the turbine rotors, thereby accelerating the fatigue of the rotor parts. High resolution Doppler lidar has been used in two studies of the LLJ over the U.S. Great Plains. In this paper we show the usefulness of this remote sensing tool in documenting the mean and turbulent vertical structure, and the evolution of these vertical structures through entire nights. This leads to implications about potential usefulness of Doppler lidar in monitoring mean winds and turbulence in real time to aid in turbine operations.

Stable-boundary-layer regimes from the perspective of the low-level jet

This paper reviews results from two field studies of the nocturnal stable atmospheric boundary layer (SBL) over the Great Plains of the United States. Data from a scanning remote-sensing system, a High-Resolution Doppler Lidar (HRDL), provided measurements of mean and turbulent wind components at high spatial and temporal resolution through the lowest 500–1000 m of the atmosphere. This data set has allowed the characteristics of the low-level jet (LLJ) maximum (speed, height, direction) to be documented through entire nights. LLJs form after sunset and produce strong shear in the layer below the LLJ maximum or nose, which is a source of turbulence and mixing in the SBL. Simultaneous HRDL measurements of turbulence quantities related to turbulence kinetic energy (TKE) has allowed the turbulence in the subjet layer to be related to LLJ properties. Turbulence structure was found to be a function of the bulk stability of the subjet layer. For the strong-LLJ (> 15 m s−1), weakly stable cases the strength of the turbulence is proportional to the strength of the LLJ. For these cases with nearly continuous turbulence in the subjet layer, low-level jet scaling, in which lengths are scaled by the LLJ height and velocity variables are scaled by the LLJ speed, was found to be appropriate. For the weak-wind (< 5 m s−1 in the lowest 200 m), very stable boundary layer (vSBL), the boundary layer was found to be very shallow (sometimes < 10 m deep), and turbulent fluxes between the earth’s surface and the atmosphere were found to be essentially shut down. For more intermediate wind speeds and stabilities, the SBL shows varying degrees of intermittency due to various mechanisms, including shearinstability and other gravity waves, density currents, and other mesoscale disturbances.