Jeffry Rothermel (jeff.rothermel@msfc.nasa.gov), MACAWS Principal Investigator, Global Hydrology and Climate Center, Marshall Space Flight Center
The Multi-Center Airborne Coherent Atmospheric Wind Sensor (MACAWS) is a scanning pulsed coherent Doppler laser radar (lidar), developed by the lidar remote sensing groups of Marshall Space Flight Center (MSFC), NOAA Environmental Technology Laboratory (R. Michael Hardesty, lead), and Jet Propulsion Laboratory (Robert T. Menzies, lead). Because of the extensive experience of each organization with laser remote sensing, development costs have been minimized through shared use of field-proven hardware and software subsystems wherever possible. Laboratory integration and testing were completed in July, and first flights are scheduled for September 1995 on the NASA DC-8 research aircraft. The concept of two-dimensional wind measurements with scanning Doppler lidar was demonstrated in 1981. Substantial improvements to scanner control and pointing accuracy were subsequently made, and the modified system was reflown in 1984 (Bilbro et al. 1986). Since then, developments in the technology of high-energy-per-pulse, frequency-stable lasers led to significant improvements in lidar remote sensing capabilities for winds and aerosols. These developments were implemented in MACAWS.
The motivation for MACAWS is three-fold. First, fine-scale, distributed measurements of sub-grid-scale processes are necessary to improve parameterizations in large-scale atmospheric/hydrologic models, e.g., WMO 1992. Second, similar measurements are necessary to increase understanding and improve predictive capabilities on the mesoscale. Finally, airborne Doppler lidar permits evaluation of various concepts for global tropospheric wind measurement with satellite Doppler wind lidar.
Principle of Operation
The table summarizes MACAWS performance specifications.
The anticipated improvement in performance over the lidar flown in the 1980's is due chiefly to a factor of 60 increase in energy-per-pulse. During operation, a pulsed lidar beam is generated and precisely directed into the atmosphere using a refractive scanning device mounted on the interior left side of the aircraft. A portion of the radiation is scattered back to the lidar from natural or anthropogenic aerosols, which act as passive wind tracers. Clouds are also a significant scattering target, and, depending on opacity and distribution, may inhibit or extend the measurement coverage. The frequency of the backscattered radiation is Doppler-shifted in proportion to the component of wind velocity along the lidar line-of-sight. By scanning the lidar beam forward and aft of the aircraft heading such that the radial velocity vectors fall within a common plane, a field of two-dimensional, ground-relative wind estimates is obtained (Figure 1).
The contribution to the Doppler shift due to scan angle and aircraft attitude and speed are removed using rapidly-updated inertial measurements from a dedicated inertial navigation system. Multiple scan planes can be generated to reveal velocity and aerosol (or cloud) distribution over a three-dimensional region (Figure 2). Research Applications
Previous experience indicates that airborne Doppler lidar can successfully measure atmospheric dynamical processes in the planetary boundary layer and free troposphere, in geographic locations and over scales of motion, for which other research, or operational, sensors may not be well-suited. As such, a variety of research activities are planned with MACAWS in 1995 and beyond, including participation during enhanced observational periods of the GEWEX Continental-scale International Program (GCIP) (IGPO 1994). Measurements will be used concurrently to address concepts in prospective satellite-borne, lidar-based Doppler wind sensors, as ground-based lidar measurements alone are insufficient to address all performance-related issues. Plans are also underway for validation of the NASA Scatterometer (NSCAT) on the Japanese Advanced Earth Observing Satellite (ADEOS).
Atmospheric Dynamics Studies
Airborne Doppler lidar measures velocity and aerosol properties in optically clear air, from cloud boundaries, and within optically-thin clouds. Despite similarities to conventional radar, differences between radar and lidar are significant (see, for example, Rothermel et al. 1985 for a comparison and discussion). Lidar is attenuated by optically thick cloud and heavy precipitation, and typically has shorter range. However, lidar does not require hydrometeors for sufficient scattering, to first order the motion of the aerosol scatterers is unbiased, lidar beam divergence is orders of magnitude smaller compared to radar, and marginal lidar return signals are not susceptible to ground clutter contamination compared to radar. In consideration of these characteristics, anticipated contributions from MACAWS are based on: measurement resolution at critical scales (down to 1 km); measurement synergisms with radar and satellites, e.g., lidar measurements in the optically clear free troposphere in the vicinity of deep convection; unique measurement capability over complex terrain; and the ability to monitor evolving processes and features that drift in and out of ground-based measurement networks. A few examples of planned research applications are described below.
Sub-grid-scale measurements of winds are highly desirable to improve parameterizations in climate and general circulation models. For example, mesoscale coherent structures in the planetary boundary layer (PBL), sometimes referred to as organized large eddies (OLE), can affect the accuracy of PBL flux parameterizations (Foster and Brown 1991). Examples are quasi-steady two- and three-dimensional circulations, often manifested, respectively, as cloud streets and mesoscale cellular convection (Rothermel and Agee 1980). These features may occupy the entire PBL and possess horizontal length scales of order 10-100 km. MACAWS will be capable of providing unprecedented measurements of these and other examples of OLEs. Airborne Doppler wind lidar can map flows over complex terrain, providing data sets against which to validate existing regional-scale numerical models or develop new models, e.g., Carroll 1989. Characteristics of low-level jets, which can play a significant role in lower troposphere moisture transport, and which are difficult to resolve with operational sensors, are also amenable to study. Under circumstances where attenuation by optically-thick clouds can be avoided, airborne Doppler wind lidar can potentially provide much-needed measurements of high-altitude circulations in and around hurricanes, as well as planetary boundary layer processes.
Simulations of Satellite Doppler Wind Lidar
In the absence of a space heritage of global tropospheric wind measurements with Doppler lidar, assessments based on measured‹as opposed to simulated‹data are highly desirable to evaluate and refine design concepts, to reduce uncertainties in performance assessments, and to begin to develop necessary interpretive skills. Results can be used to enhance the realism of observing system simulation experiments (OSSEs) for various satellite Doppler wind lidar concepts, e.g., Baker et al. (1995). These experiments depend critically on instrument designs, which currently favor instruments in the small-satellite class, e.g., Kavaya et al. (1994). Ultimately, the reduced costs of small-sat missions will need to be carefully balanced against constraints on power, mass, volume, and heat rejection when evaluating performance.
Using appropriate scanning techniques, airborne Doppler lidar can be used to simulate a lidar perspective from space and thereby address key performance issues. For example, in the absence of optically thick cloud, spaceborne Doppler lidar will contain a frequency-distributed surface return signal with a mean and variance, absent from ground-based lidar observations. Surface returns are potentially useful for calibration and atmospheric extinction estimation, as well as identification of apparent Doppler surface velocity "ground truth" which may be used to minimize instrument biases. The properties of surface return signals depend on reflectance, which is a function of location, season, incidence angle, and sea state, for the case of ocean returns. Other issues that are addressable with airborne Doppler lidar include: velocity retrievals at marginal signal levels; the impact of spatial wind variability, including coherent structures; the effect of aerosol vertical gradients, particularly for wind measurement near sea surface; and accounting for vertical velocity contribution from cloud. Clouds will constitute a frequent scattering target for spaceborne lidar; on an annual basis, over 60 percent of the globe is covered by cloud of some type at some level (Rossow et al. 1993). Airborne scanning Doppler lidar is well-suited for high-resolution assessments of cloud-free line-of-sight, cloud dimensions (height, possibly thickness and base), and optical properties (optical depth, extinction, and speckle statistics). A number of satellite Doppler lidar scanning, or sampling, strategies may be simulated. For optimum efficiency, sampling strategies must take into account the extremes of marginal signal and abundant signal, or oversampling, conditions. Each scanning concept has major implications for system design, hence coverage and resolution.
Integration and flights are scheduled for August and September 1995, respectively. Ames Research Center, Moffett Field, California, will be the primary base of operations. The initial emphasis will be placed on verifying that MACAWS is performing properly. However, several science demonstration flights are planned for the western U.S. and eastern Pacific Ocean. Measurements will be made of boundary layer dynamics, velocity distribution in and near clouds, cloud optical properties, angular dependence of sea surface returns, and near-sea-surface velocity profiles. Correlative measurements are planned with on-board and external instrumentation, including focused Doppler lidars, microwave radiometers (near-sea-surface winds), dropsondes, ground-based Doppler radar and lidar, instrumented buoys, and polar orbiting satellites. There is also potential for one or more hurricane survey missions from either the east or west coast, in coordination with NOAA hurricane research aircraft.
A homepage has been established on the World Wide Web to provide a more thorough description of MACAWS, to give examples of previous airborne Doppler wind lidar studies, and to post late-breaking results from the 1995 MACAWS flight program (http://wwwghcc.msfc.nasa.gov:5678/macaws.html). Further inquiries from interested researchers are welcomed.
Acknowledgment: Funding for MACAWS is provided by NASA Headquarters through the support of Dr. Ramesh Kakar.
Baker, W.E., G.D. Emmitt, P. 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, T.L. Miller, and J. McElroy, 1995: Lidar measured winds from space: An essential component for weather and climate prediction. Bull. Amer. Meteor. Soc., 76, 869-888.
Bilbro, J.W., C.A. DiMarzio, D.E. Fitzjarrald, S.C. Johnson, and W.D. Jones, 1986: Airborne Doppler lidar measurements. Appl. Opt., 25, 3952-3960.
Carroll, J.J., 1989: Analysis of airborne Doppler lidar measurements of the extended California sea breeze. J. Atmos. Oceanic Tech., 6, 820-831.
Foster, R., and R.A. Brown, 1991: EOS, 72, suppl. 92-93.
International GEWEX Project Office, 1994: Major Activities Plan for 1995, 1996 and Outlook for 1997 for the GEWEX Continental-scale International Project (GCIP), IGPO Publication Series No. 12.
Kavaya, M.J., G.D. Spiers, E.S. Lobl, J. Rothermel, and V.W. Keller, 1994: Direct global measurements of tropospheric winds employing a simplified coherent laser radar using fully scalable technology and technique. Reprints, SPIE Intl. Symp. on Optical Engineering and Aerospace Sensing, April 5-8, Orlando, FL.
Rossow, W.B., A.W. Walker, and L.C. Garder, 1993: Comparison of ISCCP and other cloud amounts. J. Climate, 6, 2394-2418.
Rothermel, J., and E.M. Agee, 1980: Aircraft investigation of mesoscale cellular convection during AMTEX 75. J. Atmos. Sci., 37, 1027-1040.
Rothermel, J., C. Kessinger, and D.L. Davis, 1985: Dual-Doppler lidar measurement of winds in the JAWS experiment. J. Atmos. Oceanic Tech., 2, 138-147.
World Meteorological Organization, 1992: Scientific Plan for GEWEX Continental-Scale International Project (GCIP). WCRP-67, WMO/TD No. 461, WMO, Geneva, Switzerland.
