The MACAWS program is no longer active, these pages are being maintained for informational use.
Welcome to the MACAWS homepage! If you are unfamiliar with the concept of coherent Doppler laser radar (lidar) to measure atmospheric winds and aerosols, then see our handy list of definitions to some key words and concepts. Then, come on back and enjoy the rest of this page!
The Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) is an airborne, pulsed, scanning, coherent Doppler laser radar (lidar) that remotely senses the distribution of wind velocity and aerosol backscatter within three-dimensional volumes in the troposphere and lower stratosphere. MACAWS, presently configured to fly on the NASA DC-8 research aircraft, was developed jointly by the atmospheric lidar remote sensing groups of NASA Global Hydrology and Climate Center, NASA Marshall Space Flight Center (MSFC), NOAA Environmental Technology Laboratory (ETL), and the Jet Propulsion Laboratory (JPL). Nearly all of the MACAWS hardware components were developed for previous atmospheric research programs. The re-use of these field-tested components has resulted in considerable cost savings to the Government. Interagency cooperation among the atmospheric lidar remote sensing groups also ensures that research activities are both scientifically synergistic and cost-effective. For example, the MACAWS laser transmitter is that of the highly successful mobile ground-based Doppler lidar ("Windvan") developed by NOAA ETL and deployed for a number of experiments.
The MACAWS team gratefully acknowledges the support and programmatic guidance of Dr. Ramesh Kakar, NASA Office of Mission to Planet Earth, without whom this cooperative effort would not be possible. We also acknowledge the support of the Atmospheric Lidar Division of the Environmental Technology Laboratory of NOAA/ERL.
The MACAWS team of scientists, engineers, and technicians includes: Dr. Jeffry Rothermel (Principal Investigator) and Dr. Maurice A. Jarzembski, GHCC/MSFC; Dr Dean R. Cutten (Co-Investigator), GHCC/University of Alabama in Huntsville; Dr. Vandana Srivastava, Universities Space Research Association; Diana M. Chambers, MicroCraft, Inc.; Philip A. Kromis, Computer Science Corporation, Inc.; Robert W. Lee and Scott Harper, Lassen Research, Inc.; Dr. R. Michael Hardesty (Co-PI), James N. Howell (Co-I), Lisa S. Darby, Dr. Robert M. Banta, Ann Weickmann, Alan Brewer, Scott Sandberg, Richard Marchbanks and Keith Koenig, NOAA ETL; Dr. David M. Tratt (Co-PI), Dr. Robert T. Menzies (Co-I), and Carlos Esproles, JPL. Technical and logistic support for the DC-8 is provided by the Airborne Science Branch of the NASA Dryden Flight Research Center, Edwards, California.
The scientific motivation behind MACAWS is to obtain fundamental atmospheric measurements in order to:
Airborne Doppler wind lidar is capable of measuring atmospheric dynamical
processes and features in the planetary boundary layer and free troposphere,
in geographic locations and over scales of motion, that may be beyond the
capability of conventional and other research sensors. Anticipated contributions
from MACAWS are based on: measurement resolution at critical scales (down
to 1 km); measurement synergisms with water vapor imagers and profilers,
radar, satellites and other sensors; unbiased measurement capability over
complex terrain; and the ability to monitor evolving processes and features
drifting in and out of ground-based measurement networks.
Winds and associated ocean currents are the primary response to planetary
thermal disequilibrium. Winds transport internal energy, water vapor, aerosols,
and trace gases, which interact with radiation and latent heating to produce
climate and its variability. Wind measurements for four-dimensional assimilation
of atmospheric, oceanic, and land data are critical to understanding climate
variability and improving numerical weather prediction (Baker et al. 1995).
In the absence of a space heritage of Doppler lidar wind measurements, performance
simulations with measured--rather than simulated--data are highly desirable
to guide design concepts, reduce lidar simulation model uncertainties, and
to begin to develop interpretive skills. Ground-based lidar measurements
alone do not address all design and performance-related issues. Measured
data are invaluable for evaluating and improving observing system simulation
experiments (OSSEs). Simulation results critically depend on instrument
design, which, at MSFC, is currently focused on economical sensors in the
small-satellite class (Kavaya and Emmitt 1998). Constraints on satellite
power, mass, volume, and heat rejection must be carefully evaluated against
performance.
Simulations of satellite Doppler wind lidar using MACAWS will address: assessment of sampling strategies, including the impact of coherent atmospheric wind structures; verification of Doppler processing algorithms; correlations between aerosol backscatter and atmospheric dynamics; mapping of cloud properties (velocity distribution, opacity, porosity); and satellite calibration and monitoring using natural targets. All of these factors must be taken into account when predicting the performance of small-satellite Doppler wind lidars, and ultimately the impact of the measurements on climate and global change studies and numerical weather prediction.
This block diagram illustrates the major components of MACAWS, their interrelationship, and the institutional responsibilities for providing and maintaining them. Most of the components were developed and used extensively for previous airborne and ground-based research programs. MACAWS consists of the following major components (many of which are shown in this laboratory photograph taken during initial laboratory integration): a frequency-stable, pulsed, transverse-excited, atmospheric pressure (TEA) CO2 laser transmitter producing 0.6-1.0 Joules per pulse between 9-11 microns (nominally 10.6 microns and 0.7 J) at a pulse repetition frequency (PRF) of 1-30 Hz (nominally 20); a coherent receiver employing a cryogenically-cooled HgCdTe infrared (IR) detector; a 0.3 m off-axis paraboloidal telescope shared by the transmitter and receiver in a monostatic configuration; a ruggedized optical table and support structure; a scanner using two counter-rotating germanium wedges to refract the transmitted beam in the desired direction; a dedicated inertial navigation system (INS) for representative measurements of aircraft attitude, speed, and position; data processing, real-time display, and storage devices; and an Operations Control System (OCS) to orchestrate the operation of all components. MACAWS is presently configured to fly on the NASA DC-8 research aircraft.
During flight, laser pulses are generated and transmitted to the atmosphere through a scanner mounted within the left side of the aircraft ahead of the wing. Aerosols, clouds, or the earth’s surface scatter a small portion of the incident radiation backward along the line-of-sight (LOS) to the receiver. INS measurements of aircraft pitch, roll, and velocity are continually input to the OCS, which in turn issues commands to the scanner to compensate for aircraft attitude and speed changes in order to maintain precise beam pointing. Using the same INS measurements, the OCS calculates and subtracts the frequency contribution to the Doppler-shifted signal due to the component of aircraft motion along the line-of-sight. The resulting LOS velocities are with respect to earth coordinates. On-board displays of LOS velocity and backscattered intensity are available for real-time assessment of lidar performance and overall data quality, and for in-flight mission guidance. Raw digitized in-phase and quadrature components of the amplified detector output (in limited quantities), processed data, aircraft housekeeping data, scanner settings, and INS measurements are stored on digital audio tape for subsequent analysis. For additional in-flight guidance, visible and infrared satellite imagery may be acquired directly from polar orbiting satellites using an aircraft facility resource. The table below summarizes nominal MACAWS performance characteristics.
MACAWS employs three methods to remotely sense the atmosphere.
A feature unique to MACAWS is the capability to measure in real-time the two-dimensional (2-d) wind field over a broad area. The technique, referred to as side-scanning or co-planar scanning, was successfully demonstrated in 1981 with the MSFC airborne Doppler lidar system (Bilbro et al. 1984). The lidar beam is first directed through a pair of counter-rotating germanium wedges (Amirault and DiMarzio 1985) and finally through a germanium window that also serves as the pressure interface. The scanner is capable of refracting the beam anywhere within a ~64 deg solid angle. Here is a plan view of the pattern of lidar beams produced by co-planar scanning. Two-dimensional wind velocities are obtained at intersecting points by alternately directing the beam ~20 deg forward and aft of normal relative to the aircraft heading. The OCS regulates the scanner pointing to account for aircraft pitch and roll changes sensed by the INS, thus maintaining the desired beam distribution within the scan plane. Direct measurement of two-dimensional winds is limited to plus or minus ~25 deg elevation. This limitation is due to the requirement of 40 deg angular separation between forward and aft scan components and the refractive limit of the scanner wedges. Under nominal atmospheric conditions and system settings, MACAWS provides a LOS resolution of 450 m and velocity accuracy of ~1 m/s. Finer spatial resolution is possible by operating with a shorter pulse duration (1 microsecond minimum), or by reducing the receiver "window" in the signal processor (150 m minimum). Operation at the longer pulse length results in improved coverage owing to the greater laser energy output per pulse. Radial velocity accuracy may be improved by correcting the apparent Doppler velocity returns from the surface.
Three-dimensional (3-d) coverage over a limited atmospheric volume is achieved by directing the lidar beam within up to five scan planes. This technique was first demonstrated in 1984 with the improved ADLS (Bilbro et al. 1986). The OCS and scanner have the capability to control the number of scan planes and the angular spacing among scan planes, depending on the measurement requirements. For example, for studies of planetary boundary layer (PBL) processes, the aircraft may cruise within or immediately above the PBL while the scanner generates multiple scan planes with relatively small angular separation to permit detailed vertical resolution. In general, the extent of the 3-d domain over which usable signals may be obtained is a function of: aircraft altitude, which is subject to air traffic control restrictions and aircraft service ceiling; angular separation between uppermost and lowermost scan planes, which is subject to the refractive limit of the scanner; laser operating parameters (described above); aerosol backscatter distribution; attenuation by water vapor and clouds; and meteorological conditions (e.g. cloud distribution and type). Vertical resolution varies with slant range from the lidar and with angular separation between scan planes. Resolution along the flight track D x in each scan plane may be expressed by the following approximation for both 2-D and 3-D scanning:
(1) where d1 is delay in repositioning the scanner wedges to an adjacent elevation angle in the fore or aft direction (~0.1 s), d2 is scanner delay between the fore and aft pointing directions (~0.6 s), na is number of scan planes, ng is number of pulses averaged during signal processing, nb is number of pulses rejected during signal processing, P is laser pulse repetition frequency (s-1), and Vg is aircraft ground speed. Turbulence may slightly increase the time required to reposition the scanner wedges, as well as cause brief periods of laser mode degradation or frequency jitter (the on-board pulse quality discriminator rejects these pulses). Both effects degrade the along-track resolution. For the case of measurements in the planetary boundary layer (PBL) assuming Vg = 125 m s-1, P = 20 s-1, na = 5, nb = 2, and ng = 10, then D x @ 1.0 km.
It is sometimes necessary to forego 2-d wind measurements in order to obtain vertical profiles of LOS velocity or aerosols with finer spatial resolution, as well as to assess the angular dependence of backscattered signals over a broader range of incidence angles. MACAWS is capable of profiling the LOS component of the wind and aerosol backscatter above or below the flight level, at elevation angles that exceed a magnitude of 25 deg imposed by the scanner configuration for 2-d wind measurements. During profiling the lidar beam is held fixed, up to a limit of plus or minus ~30 deg elevation angle relative to the surface or feature of interest. As before, the OCS compensates for changes in aircraft attitude and speed. Angles steeper than ~30 deg may be achieved by performing a controlled roll maneuver. For example, a 57 deg incidence angle at the sea surface may be achieved by rolling the aircraft to the left at an angle of at least 27 deg. Again, the scanner is continually adjusted to take into account changes in aircraft attitude and speed in order to maintain the desired elevation angle. The ability to do vertical profiling has several important applications. For example, the horizontal wind profile may be inferred with finer resolution from the LOS velocity profile if the aircraft is flown perpendicular to the mean PBL wind velocity. Moreover, profiling of optically-thin clouds, haze layers, and boundary layers is possible with fine spatial resolution over large horizontal distances. Information on surface scattering characteristics as a function of incidence angle may be obtained by executing controlled roll maneuvers over a range of angles. By orbiting in a circular or cycloidal pattern, detailed vertical wind profiles may be derived similar to a radar VAD.
Lidar uses laser radiation and a telescope/scanner similar to the way radar uses radio frequency emissions and a dish antenna. Lidar scatterers sensed by MACAWS are typically aerosols with diameter of order 1 micron (0.00004 inch) or less, which act as passive wind tracers. Optically thick cloud and precipitation can attenuate the lidar beam. On the other hand, radar scatterers may consist of clouds and hydrometeors (e.g., rain or frozen precipitation, which have a definite fall velocity). In optically clear air, radar return signals may be obtained from insects and birds, and from radio refractive index variations due to humidity, temperature, or pressure fluctuations. Lidar beam divergence is two to three orders of magnitude smaller compared to conventional 5 and 10 cm wavelength radars. For example, the MACAWS lidar beam diameter for a single pulse is only ~1 m at 10 km slant range. This characteristic permits unambiguous velocity measurements near clouds and surface features, without susceptibility to velocity bias due to ground clutter and side lobe contamination sometimes experienced by radar under marginal reflectivity conditions and strong reflectivity gradients.
After three years of development, a series of trial measurements was made over the western US and eastern Pacific Ocean during September 13-26, 1995. NASA Ames Research Center was used as a base of operations. Emphasis was placed on assessing MACAWS performance, although several science missions were flown. The table below summarizes details of the flight experiments. Some experiments were strongly dependent on geographic area, altitude, and diurnal cycle; other experiments were independent of these factors.
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FLIGHT DATE OBJECTIVE(S) LOCATION(S)
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950301 9-13-95 Engineering check CA Cent. Valley; E. Pacific
950302 9-15-95 Engineering check CA Cent. Valley
950303 9-18-95 Backscatter intercomp. E. Pacific
Pollution transport Between Sacramento & Lake Tahoe
into Sierra Nevadas
950304 9-20-95 Intercomp. with COPE Near northern Oregon coast
ERS-1 intercomp. of Near northern Oregon coast
near sea-surface winds
Sea surface scattering Near central Oregon coast
versus nadir angle
Near-coast sea breeze Monterey Bay & Salinas Valley
950305 9-21-95 Hurricane Juliette E. Pacific SW of Baja peninsula
950306 9-22-95 Down day for MACAWS - - -
950307 9-23-95 Intercomp. with COPE Near northern Oregon coast
ERS-1 intercomp. of near Near northern Oregon coast
sea-surface winds
Sea surface scattering Near northern Oregon coast
versus nadir angle
950308 9-24-95 Satellite Doppler wind CA Central Valley
lidar simulations
Cirrus cloud properties CA Central Valley
Pollution transport Between Sacramento & Lake Tahoe
into Sierra Nevadas
950309 9-26-95 Sea surface scattering E. Pacific
versus nadir angle
Coherent structure in E. Pacific
PBL convection
ERS-1 intercomparison of E. Pacific
near-sea-surface winds
Flow around isolated Sutter Buttes (CA Central Val.)
obstacle
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This movie loop illustrates the marine PBL wind structure as measured over five scan planes during a Flight 7 on September 23, 1995, 1826-1829 UTC. The DC-8 was on a southerly heading at ~30 km west of the coast of northern Oregon at an altitude of 909 meters ASL. These measurements were made in conjunction with the Coastal Ocean Probing Experiment (COPE).
Following the initial 1995 flight program several improvements were made to the laser and OCS in order to improve accuracy and reliability, particularly under turbulent conditions. Following is a summary of the flight experiments conducted during the 1996 flight program. "Piggyback" denotes occasions when another experiment had control of the aircraft.
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FLIGHT DATE OBJECTIVE(S) LOCATION(S)
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960301 5-31-96 Engineering check CA Central Valley; Southern CA
960302 6-02-96 Engineering check CA Central Valley; Southern CA
960303 6-05-96 (piggyback) Central, Southern CA
960304 6-06-96 Southerly surge Monterey Bay
(piggyback) San Francisco Bay
960305 6-07-96 (piggyback) Central, Southern CA
960306 6-10-96 Hydraulic fan Near Point Arena, CA
Ang. dep. sea sfc scat. E. Pacific near No. CA
Jet stream transects Washington state
960307 6-12-96 Jet stream transects Washington state
(piggyback) Washington, Alaska
960308 6-13-96 Flow over complex terrain Aleutian Islands, AK
960309 6-14-96 (piggyback) Alaska
960310 6-15-96 (piggyback) Transit AK to TX
960311 6-22-96 (stand-down) - - -
960312 6-24-96 Sea breeze (aborted due Near Galveston, TX
to intense convection)
(piggyback) AR, OK, TX
960313 6-25-97 Dryline West Texas
(piggyback) Texas coast
960314 6-26-96 (piggyback) OK, TX
960315 6-27-96 [power supply failure] - - -
960316 6-30-96 Hydraulic fan Near Point Arena, CA
ERS-2 intercomparison E. Pacific
960317 7-01-96 (piggyback) SW of SF Bay, CA
960318 7-02-96 (piggyback) Central, southern CA
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In addition, ongoing experiments using targets of opportunity were conducted to investigate aerosol backscatter distribution, cloud velocity distributions and optical properties, lidar and OCS performance, and satellite Doppler wind lidar simulations.
MACAWS was integrated into the DC-8 by May 24, 1996. The first checkout flight was made on May 30 over southern and central California. Lidar winds measured at flight level were found to be in good agreement with wind velocities derived from the DC-8 inertial navigation system. Also, scanner pointing errors were calculated to be ~0.1 deg rms based on ground calibration. Analysis of the spatial distribution of ground returns over the flat terrain in the California Central Valley are consistent with this calculation. These results confirmed that MACAWS could be dismantled and re-integrated with no degradation in performance.
On 7 June 1996 (flight. no. 960305) during 1630 - 1813 UTC, the DC-8 flew a series of parallel lines over Napa Valley, California in conjunction with an unrelated mission. During this time flight-level conditions were dominated by weak southwesterly flow due to a ridge of high pressure located over Utah-Arizona and by a low pressure area located to the west of British Columbia, Canada. Surface conditions were influenced by a weak inverted trough of low pressure extending through southern California, and a stationary front located along the California-Oregon border. This figure shows a quasi-vertical cross-section of aerosol backscatter coefficient (top) and line-of-sight velocity measured at a lidar beam elevation angle of -30 deg from an altitude of 8.3 km ASL during 1717 - 1720 UTC. Note the well-defined scattering layers, that are highly correlated with the vertical shear in velocity. The lidar beam intersected the western slopes of the Mayacmas Mountains north of Santa Rosa, California, evident on the right-hand side. Note that the surface returns have nearly zero Doppler shift, indicating that MACAWS was performing optimally. Datasets such as this are valuable for atmospheric research as well as to simulate aspects of the performance of prospective satellite Doppler lidar wind sounders.
Surface winds off the California coast are northwesterly to northerly in summer, resulting from flow around the east side of the subtropical high-pressure system over the Pacific Ocean. This high is accompanied by subsidence and a strong marine inversion usually a few hundred meters deep. The coastal mountain-range topography interacts with the northerly flow in this marine-inversion layer to produce a variety of interesting flow phenomena. For example, when this flow passes one of the many capes and points that jut into the winds along the California coast, structures referred to as "hydraulic expansion fans" have been found. Such features are marked by strong variation along the vertical and cross-shore directions. To study this variability the DC-8 flew sets of parallel line segments just offshore past Point Arena, California on 30 June 1996 during 1950 - 2110 UTC at an altitude of 0.49 km. This movie loop shows wind fields at five elevation angles in the original, fine resolution. These data, including adjacent lidar wind fields not shown, have been interpolated to three levels in a Cartesian grid volume and are displayed as a movie loop.
MACAWS was reflown during August 3 - October 1, 1998 on the NASA DC-8 in essentially the same configuration as part of the NASA-sponsored Convection and Moisture Experiment (CAMEX III) and Texas-Florida Underflights (TEFLUN) field programs sponsored by the NASA Office of Earth Science. Flight listings may be found at the CAMEX III website.
With the feasibility of Doppler lidar wind coverage having been confirmed in 1995 during a science demonstration flight through tropical cyclone Juliette (Rothermel et al. 1997), MACAWS was included in CAMEX III. The objectives of CAMEX III were to study hurricane intensification and track using "state-of-the-art" active, passive, optical, and microwave remote sensing technology sponsored by the NASA research and analysis program. Coordinated flights were conducted with the NASA DC-8 (containing MACAWS) and ER-2 during 10 August – 22 September 1998 using Patrick Air Force Base, Florida, as the operations base. Flights were made into hurricanes Bonnie (twice), Danielle (twice), Earl (once), and Georges (twice). Correlative measurements were obtained with other on-board sensors, including a water vapor profiler, as well as among the NASA aircraft, NOAA Hurricane Research Division WP-3D’s and Gulfstream-IV, University of North Dakota Citation and US Air Force 53rd Weather Reconnaissance Squadron C-130’s. Additionally, GPS dropwindsondes were released into the hurricane routinely for the first time. The NASA instruments provided information on upper levels of the tropical cyclone heretofore unstudied by NOAA research and USAF reconnaissance aircraft. Mission objectives (for all aircraft but the NOAA Gulfstream-IV) included numerous eyewall transects and mapping of low-level inflow. MACAWS observations fell into three general categories: storm environment, eyewall transects, and low-level inflow. This figure shows a portion of eyewall winds mapped by MACAWS in the northwest quadrant during an eyewall transect of hurricane Bonnie during landfall in the Carolinas on 26 August 1998. The approximate location of the analysis is indicated on a visible satellite image obtained ~20 minutes earlier. Gridded two-dimensional wind velocities were calculated using the publicly-available NCAR Doppler radar analysis package ‘CEDRIC’ (Mohr and Miller 1983). Owing to the vertical distribution of the five scan planes (-20, -10, 0, 10, and 20 deg), horizontal wind fields were calculated from 10.1 – 10.4 km in 100 m vertical intervals. Results show an extremely tight velocity gradient and curvature along the inner edge of the eyewall, in good agreement with flight-level winds derived from the aircraft INS (Rothermel et al. 1999). These results represent the first Doppler lidar wind field measurements within a hurricane.
The following references provide additional information on MACAWS and on the airborne Doppler lidar system that was flown in the 1980's. Selected papers based on the latter have been included as additional examples of research applications; those results are based on a much lower-energy system with less coverage compared to MACAWS.
Amirault, C.T. and C.A. DiMarzio, "Precision pointing using a dual-wedge scanner," Appl. Opt., 24, 1302-1308 (1985).
Baker, W.E., G.D. Emmitt, F. Robertson, R.M. Atlas, J.E. Molinari, D.A. Bowdle, J. Paegle, R.M. Hardesty, R.T. Menzies, T.N. Krishnamurti, R.A. Brown, M.J. Post, J.R. Anderson, A.C. Lorenc, and James McElroy, "Lidar-measured winds from space: a key component for weather and climate prediction," Bull. Amer. Meteor. Soc., 76, 869-888 (1995).
Bilbro, J.W., G.H. Fichtl, D.E. Fitzjarrald and M. Krause, "Airborne Doppler lidar wind field measurements," Bull. Amer. Meteor. Soc., 65, 348-359 (1984).
Bilbro, J.W., C.A. Dimarzio, D.E. Fitzjarrald, S.C. Johnson and W.D. Jones, "Airborne Doppler lidar measurements," Appl. Opt., 25, 3952-3960 (1986).
Blumen, W. and J.E. Hart, "Airborne Doppler lidar wind field measurements of waves in the lee of Mount Shasta," J. Atmos. Sci., 45, 1571-1583 (1988).
Carroll, J.J., "Analysis of airborne Doppler lidar measurements of the extended California sea breeze," J. Atmos. Oceanic Tech., 6, 820-831 (1989).
Emmitt, G.D., "Convective storm downdraft outflows detected by NASA/MSFC's 10.6 micron pulsed Doppler lidar system," NASA CR-3898, Marshall Space Flight Center, Huntsville, AL, 46 pp. (1985).
Howell, J.N., R.M. Hardesty, J. Rothermel, and R.T. Menzies, 1996: Overview of the first Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) experiment: Conversion of ground-based lidar for airborne applications. Proc. Soc. Photo. Instrum. Eng., 2833, 116-127.
McCaul, E.W., Jr., H.B. Bluestein and R.J. Doviak, "Airborne Doppler lidar observations of convective phenomena in Oklahoma," J. Atmos. Oceanic Tech., 4, 479-497 (1987).
Mohr, C.G. and L.J. Miller, 1983: CEDRIC - A software package for Cartesian space editing, synthesis, and display of radar fields under interactive control. Preprints, 21st Conf. Radar Meteor., Edmonton, Alta., Canada, Amer. Meteor. Soc., 569-574.
Rothermel, J., C. Kessinger, and D.L. Davis, "Dual-Doppler lidar measurement of winds in the JAWS experiment," J. Atmos. Oceanic Tech., 2, 138-147 (1985).
Rothermel, J., R.M. Hardesty, and R.T. Menzies, "Characterizing sub-grid scale processes and assessing satellite Doppler wind lidar with MACAWS," Preprints, Sixth Symp. Global Change Studies, Jan. 15-20, Dallas, Amer. Meteor. Soc., 118-121 (1995).
Rothermel, J., D.R. Cutten, R.M. Hardesty, J.N. Howell, R.T. Menzies, D.M. Tratt, and S.C. Johnson, "Application of airborne Doppler laser radar to hurricane research," Preprints, 22nd Conf. Hurricanes and Tropical Meteorology, May 18-23, Ft. Collins, CO, Amer. Meteor. Soc., 57-58 (1997).
Rothermel, J., D.R. Cutten, R.M. Hardesty, R.T. Menzies, J.N. Howell, S.C. Johnson, D.M. Tratt, L.D. Olivier and R.M. Banta, 1998: "The Multi-center Airborne Coherent Atmospheric Wind Sensor," Bull. Amer. Meteor. Soc., 79, 581-599.
Rothermel, J., L.D. Olivier, R.M. Banta, R.M. Hardesty, J.N. Howell, D.R. Cutten, S.C. Johnson, R.T. Menzies, and D.M. Tratt, 1998: "Remote sensing of multi-level wind fields with high-energy airborne scanning coherent Doppler lidar." Optics Express, 2 40-50 (1998).[Accessible at uniform resource locator http://www.opticsexpress.org/abstract.cfm?URI=OPEX-2-2-40
For more information on MACAWS and potential applications, you are welcome to contact:
Dr. Timothy Miller
Global Hydrology and Climate Center
320 Sparkman Dr
Huntsville AL 35805
tim.miller@msfc.nasa.gov
Global Hydrology and Climate Center
Responsible Official: Dr. James E. Arnold (jim.arnold@msfc.nasa.gov)
Page Curator: Diane Samuelson (diane.samuelson@msfc.nasa.gov)
Last Updated: May 9, 2000
