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J. M. Intrieri
,
C. G. Little
,
W. J. Shaw
,
R. M. Banta
,
P. A. Durkee
, and
R. M. Hardesty

The Land/Sea Breeze Experiment (LASBEX) was conducted at Moss Landing, California, 15–30 September 1987. The experiment was designed to study the vertical structure and mesoscale variation of the land/sea breeze. A Doppler lidar, a triangular array of three sodars, two sounding systems (one deployed from land and one from a ship), and six surface weather stations (one shipborne) were sited around the Moss Landing area. Measurements obtained included ten sea-breeze and four land-breeze events. This paper describes the objectives and design of the experiment, as well as the observing systems that were used. Some preliminary results and selected observations are presented, called from the data collected, as well as the ensuing analysis plans.

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C. Kiemle
,
G. Ehret
,
A. Fix
,
M. Wirth
,
G. Poberaj
,
W. A. Brewer
,
R. M. Hardesty
,
C. Senff
, and
M. A. LeMone

Abstract

Latent heat flux profiles in the convective boundary layer (CBL) are obtained for the first time with the combination of the Deutsches Zentrum für Luft- und Raumfahrt (DLR) water vapor differential absorption lidar (DIAL) and the NOAA high resolution Doppler wind lidar (HRDL). Both instruments were integrated nadir viewing on board the DLR Falcon research aircraft during the International H2O Project (IHOP_2002) over the U.S. Southern Great Plains. Flux profiles from 300 to 2500 m AGL are computed from high spatial resolution (150 m horizontal and vertical) two-dimensional water vapor and vertical velocity lidar cross sections using the eddy covariance technique. Three flight segments on 7 June 2002 between 1000 and 1300 LT over western Oklahoma and southwestern Kansas are analyzed. On two segments with strong convection, the latent heat flux peaks at (700 ± 200) W m−2 in the entrainment zone and decreases linearly to (200 ± 100) W m−2 in the lower CBL. A water vapor budget analysis reveals that this flux divergence [(0.9 ± 0.4) g kg−1 h−1] plus the advection (0.3 g kg−1 h−1) are nearly balanced by substantial CBL drying [(1.5 ± 0.2) g kg−1 h−1] observed by airborne and surface in situ instruments, within the limits of the overall budget rms error of 0.5 g kg−1 h−1. Entrainment of dry air from aloft and net upward humidity transport caused the CBL drying and finally inhibited the initiation of deep convection. All cospectra show significant contributions to the flux between 1- and 10-km wavelength, with peaks between 2 and 6 km, originating from large eddies. The main flux uncertainty is due to low sampling (55% rmse at mid-CBL), while instrument noise (15%) and systematic errors (7%) play a minor role. The combination of a water vapor and a wind lidar on an aircraft appears as an attractive new tool that allows measuring latent heat flux profiles from a single overflight of the investigated area.

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Sara C. Tucker
,
Christoph J. Senff
,
Ann M. Weickmann
,
W. Alan Brewer
,
Robert M. Banta
,
Scott P. Sandberg
,
Daniel C. Law
, and
R. Michael Hardesty

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.

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R. J. Alvarez II
,
C. J. Senff
,
A. O. Langford
,
A. M. Weickmann
,
D. C. Law
,
J. L. Machol
,
D. A. Merritt
,
R. D. Marchbanks
,
S. P. Sandberg
,
W. A. Brewer
,
R. M. Hardesty
, and
R. M. Banta

Abstract

The National Oceanic and Atmospheric Administration/Earth System Research Laboratory/Chemical Sciences Division (NOAA/ESRL/CSD) has developed a versatile, airborne lidar system for measuring ozone and aerosols in the boundary layer and lower free troposphere. The Tunable Optical Profiler for Aerosol and Ozone (TOPAZ) lidar was deployed aboard a NOAA Twin Otter aircraft during the Texas Air Quality Study (TexAQS 2006) and the California Research at the Nexus of Air Quality and Climate Change (CalNex 2010) field campaigns. TOPAZ is capable of measuring ozone concentrations in the lower troposphere with uncertainties of several parts per billion by volume at 90-m vertical and 600-m horizontal resolution from an aircraft flying at 60 m s−1. The system also provides uncalibrated aerosol backscatter profiles at 18-m vertical and 600-m horizontal resolution. TOPAZ incorporates state-of-the-art technologies, including a cerium-doped lithium calcium aluminum fluoride (Ce:LiCAF) laser, to make it compact and lightweight with low power consumption. The tunable, three-wavelength UV laser source makes it possible to optimize the wavelengths for differing atmospheric conditions, reduce the interference from other atmospheric constituents, and implement advanced analysis techniques. This paper describes the TOPAZ lidar, its components and performance during testing and field operation, and the data analysis procedure, including a discussion of error sources. The performance characteristics are illustrated through a comparison between TOPAZ and an ozonesonde launched during the TexAQS 2006 field campaign. A more comprehensive set of comparisons with in situ measurements during TexAQS 2006 and an assessment of the TOPAZ accuracy and precision are presented in a companion paper.

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Jeffry Rothermel
,
Dean R. Cutten
,
R. Michael Hardesty
,
Robert T. Menzies
,
James N. Howell
,
Steven C. Johnson
,
David M. Tratt
,
Lisa D. Olivier
, and
Robert M. Banta

In 1992 the atmospheric lidar remote sensing groups of the National Aeronautics and Space Administration Marshall Space Flight Center, the National Oceanic and Atmospheric Administration/Environmental Technology Laboratory (NOAA/ETL), and the Jet Propulsion Laboratory began a joint collaboration to develop an airborne high-energy Doppler laser radar (lidar) system for atmospheric research and satellite validation and simulation studies. The result is the Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS), which has the capability to remotely sense the distribution of wind and absolute aerosol backscatter in three-dimensional volumes in the troposphere and lower stratosphere.

A factor critical to the programmatic feasibility and technical success of this collaboration has been the utilization of existing components and expertise that were developed for previous atmospheric research by the respective institutions. For example, the laser transmitter is that of the mobile ground-based Doppler lidar system developed and used in atmospheric research for more than a decade at NOAA/ETL.

The motivation for MACAWS is threefold: 1) to obtain fundamental measurements of subsynoptic-scale processes and features to improve subgrid-scale parameterizations in large-scale models, 2) to obtain datasets in order to improve the understanding of and predictive capabilities for meteorological systems on subsynoptic scales, and 3) to validate (simulate) the performance of existing (planned) satellite-borne sensors.

Initial flight tests were made in September 1995; subsequent flights were made in June 1996 following system improvements. This paper describes the MACAWS instrument, principles of operation, examples of measurements over the eastern Pacific Ocean and western United States, and future applications.

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Paul J. Neiman
,
M. A. Shapiro
,
R. Michael Hardesty
,
B. Boba Stankov
,
Rhidian T. Lawrence
,
Robert J. Zamora
, and
Tamara Hampel

Abstract

The NOAA/WPL pulsed coherent Doppler lidar was used during the Texas Frontal Experiment in 1985 to study mesoscale preconvective atmospheric conditions. On 22 April 1985, the Doppler lidar, in conjunction with serial rawinsonde ascents and National Weather Service rawinsonde ascents, observed atmospheric features such as middle-tropospheric frontal and vertical wind shear layers and the planetary boundary layer. The lidar showed unique evidence of the downward transport of strong winds from an elevated vertical speed shear (frontal) layer into the planetary boundary layer. The lidar provided further evidence of atmospheric processes such as clear-air turbulence within frontal layers, and dry convection turbulence within the superadiabatic planetary boundary layer. As a result, high-technology remote sensing instruments such as the Doppler lidar show considerable promise for future studies of small-scale weather systems in a nonprecipitating atmosphere.

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Robert M. Banta
,
Yelena L. Pichugina
,
W. Alan Brewer
,
Julie K. Lundquist
,
Neil D. Kelley
,
Scott P. Sandberg
,
Raul J. Alvarez II
,
R. Michael Hardesty
, and
Ann M. Weickmann

Abstract

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.

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Robert M. Banta
,
Yelena L. Pichugina
,
W. Alan Brewer
,
Eric P. James
,
Joseph B. Olson
,
Stanley G. Benjamin
,
Jacob R. Carley
,
Laura Bianco
,
Irina V. Djalalova
,
James M. Wilczak
,
R. Michael Hardesty
,
Joel Cline
, and
Melinda C. Marquis

Abstract

To 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.

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Volker Wulfmeyer
,
David D. Turner
,
B. Baker
,
R. Banta
,
A. Behrendt
,
T. Bonin
,
W. A. Brewer
,
M. Buban
,
A. Choukulkar
,
E. Dumas
,
R. M. Hardesty
,
T. Heus
,
J. Ingwersen
,
D. Lange
,
T. R. Lee
,
S. Metzendorf
,
S. K. Muppa
,
T. Meyers
,
R. Newsom
,
M. Osman
,
S. Raasch
,
J. Santanello
,
C. Senff
,
F. Späth
,
T. Wagner
, and
T. Weckwerth

Abstract

Forecast errors with respect to wind, temperature, moisture, clouds, and precipitation largely correspond to the limited capability of current Earth system models to capture and simulate land–atmosphere feedback. To facilitate its realistic simulation in next-generation models, an improved process understanding of the related complex interactions is essential. To this end, accurate 3D observations of key variables in the land–atmosphere (L–A) system with high vertical and temporal resolution from the surface to the free troposphere are indispensable.

Recently, we developed a synergy of innovative ground-based, scanning active remote sensing systems for 2D to 3D measurements of wind, temperature, and water vapor from the surface to the lower troposphere that is able to provide comprehensive datasets for characterizing L–A feedback independently of any model input. Several new applications are introduced, such as the mapping of surface momentum, sensible heat, and latent heat fluxes in heterogeneous terrain; the testing of Monin–Obukhov similarity theory and turbulence parameterizations; the direct measurement of entrainment fluxes; and the development of new flux-gradient relationships. An experimental design taking advantage of the sensors’ synergy and advanced capabilities was realized for the first time during the Land Atmosphere Feedback Experiment (LAFE), conducted at the Atmospheric Radiation Measurement Program Southern Great Plains site in August 2017. The scientific goals and the strategy of achieving them with the LAFE dataset are introduced. We envision the initiation of innovative L–A feedback studies in different climate regions to improve weather forecast, climate, and Earth system models worldwide.

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Wayman E. Baker
,
George D. Emmitt
,
Franklin Robertson
,
Robert M. Atlas
,
John E. Molinari
,
David A. Bowdle
,
Jan Paegle
,
R. Michael Hardesty
,
Robert T. Menzies
,
T. N. Krishnamurti
,
Robert A. Brown
,
Madison J. Post
,
John R. Anderson
,
Andrew C. Lorenc
, and
James McElroy

The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.

This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.

Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.

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