The Constrained Ratio Aerosol Model-fit (CRAM) technique is a method for making aerosol retrievals from dual-wavelength elastic scatter lidars which attempts to constrain the retrievals so as to be consistent with a number of aerosol models thought to characterize a variety of aerosol types observed around the world. The NASA Langley Research Center Airborne HSRL is an airborne high spectral resolution lidar capable of direct measurements of aerosol extinction and backscatter at 532 nm and having the capability for elastic backscatter measurements at 1064 nm. Aerosol measurements by HSRL during the TEXas Air Quality Survey/ Gulf of Mexico Atmospheric Composition and Climate Study (TEXAQS/GoMACCS) campaign are used to validate existing aerosol models critical to the application of CRAM, in particular to data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) lidar instrument on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite.

Since its first collection of data in June of 2006, the Cloud and Aerosol LIdar with Orthogonal Polarization (CALIOP) lidar instrument aboard the CALIPSO satellite has observed numerous Saharan dust events over West Africa and the Atlantic, predominantly from late May through early September. Due to CALIOP's sensitivity to polarization at 532 nm, the depolarization arising from scattering from the nonspherical dust particles serves as an independent means of discrimination between dust and other aerosol species. In addition to being an important and frequently observed class of aerosol, the Saharan dust provides an excellent basis for the evaluation of elastic-scatter lidar retrieval techniques. The Constrained Ratio Aerosol Model-fit (CRAM) method is one such technique, which applies aerosol modeling constraints in order to limit the ambiguity inherent in aerosol retrievals from elastic-scatter lidar. This letter, in addition to investigating the overall scattering properties of Saharan dust, highlights various retrieval approaches useful in determining the scattering properties of aerosols, as observed by the CALIOP instrument. Herein, we attempt to arrive at an improvement in the dust aerosol model used within CRAM.

The limitations of single wavelength elastic scatter lidar with regard to retrieving various optical or microphysical properties of the observed aerosols are well known. Typical retrieval methodologies rely on elastic scatter information at at least two wavelengths, together with either temporally or geographically inferred estimates of the extinction-to-back-scatter ratio Sa, or aerosol model parameters which constrain the solution in such a way as to be consistent with the optical properties of commonly observed aerosol types. High spectral resolution lidars (HSRL) now facilitate unambiguous, direct measurement of aerosol extinction and backscatter profiles, greatly augmenting the level of information available for determining aerosol type or other relevant parameters. In this paper, we explore a methodology for using HSRL data at one wavelength to facilitate retrievals from traditional elastic scatter data at other wavelengths. Further, we extend the scope of the technique to improving aerosol models used to constrain retrievals from multi-wavelength elastic scatter lidars. We explore this methodology in the context of currently available HSRL technology as well as anticipated future spaceborne HSRL systems.

Since its first collection of lidar data in June of 2006, the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar instrument aboard CALIPSO has observed numerous Saharan dust events in Western Africa and the Atlantic, predominantly during the boreal summer months of late May through early September. A tremendous amount of data is currently available from which to begin analysis. With CALIOP's sensitivity to polarization at 532 nm, such dust layers are easily identified by significant amounts of depolarization relative to other aerosol types due to the non-sphericity of dust particles. Dust aerosols represent an interesting basis upon which to examine the performance of the CRAM technique, and in particular its dust model, due to the fact that dust is distinctly identifiable from depolarization. The results from this analysis aim to demonstrate the capability of aerosol modeling as a solution to the retrieval problem, where independent verification of aerosol type (i.e., from 532 nm depolarization and known dust transport paths) may be made to facilitate the investigation.

The widely employed Fernald lidar equation solution relation retrieves aerosol backscatter versus height for an assumed aerosol extinction-to-backscatter ratio, Sa, and known system calibration factor, C, at a given wavelength, subject to the constraint/assumption that Sais spatially constant over the solution layer (height range). At 532 nm, the calibration factor may be estimated fairly accurately by Rayleigh (molecular) normalization in high-altitude, clean-air regions. For elevated aerosol layers embedded in clean air, the direct transmittance approach may be used to estimate the optical depth of the layer, thereby giving an auxiliary input that permits Sato be determined as a part of the solution. Otherwise, Samust be specified based on models or determined through use of some other constraining information. The retrieval at 1064 nm is more problematic because the molecular scatter contribution is much weaker, typically making it difficult to either calibrate by molecular normalization or to accurately estimate the transmittance of an elevated aerosol layer, particularly for the weak signals from satellite lidar or eye-safe airborne lidar. As such, aerosol retrievals from dual-wavelength satellite lidars such as those onboard ICESat and CALIPSO have largely been limited to 532 nm retrievals using a table look-up approach to select assumed Savalues based on climatological/geographically determined models. Dual-wavelength retrievals using a Constrained Ratio Aerosol Model-fit (CRAM) retrieval method, employing AERONET based model ratio parameters, have also been obtained with some success for a few satellite lidar data sets.

Case studies from the first three months of the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) measurements of lofted aerosol layers are analyzed using transmittance [Young, 1995] and two-wavelength algorithms [Vaughan et ah, 2004] to determine the aerosol extinction-to-backscatter ratios at 532 and 1064 nm. The transmittance method requires clear air below the layer so that the transmittance through the layer can be determined. Suitable scenes are selected from the browse images and clear air below features is identified by low 532 nm backscatter signal and confirmed by low depolarization and color ratios. The transmittance and two-wavelength techniques are applied to a number of lofted layers and the extinction-to-backscatter ratios are compared with values obtained from the CALIPSO aerosol models [Omar et ah, 2004]. The results obtained from these studies are used to adjust the aerosol models and develop observations based extinction-to-backscatter ratio look-up tables and phase functions. Values obtained by these techniques are compared to Sadeterminations using other independent methods with a goal of developing probability distribution functions of aerosol type-specific extinction to backscatter ratios.

The successful launch of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloud-Satellite (CloudSAT) satellites on April 28, 2006, placing two new active remote sensing systems (lidar and radar) in space, heralded a new era in spaceborne earth observations. Not only will they provide new information unique to active sensing satellites, but by positioning them in orbit with the A-Train constellation of satellites, joining the passive sensing satellites AURA, PARASOL and AQUA, this will enable myriad synergistic active-passive sensing opportunities. CALIPSO and CloudSAT have both successfully completed their payload checkouts and initial validations; some six months of data have already been collected and data are now beginning to be distributed to the scientific community (e.g., CALIPSO Level 1 and 2a data released on Dec. 8, 2006). Thus there are sufficient data, with more arriving daily, to fuel years of scientific studies addressing questions critical to more fully understanding the earth-atmosphere system and assessing weather-climate change issues. The Constrained Ratio Aerosol Model-fit (CRAM) technique for aerosol retrieval is examined in the context of CALIPSO data, and temporally/spatially coincident High Spectral Resolution Lidar (HSRL) data is studied with respect to its potential to provide external context to the retrievals and to verify aerosol models upon which the CRAM technique relies.

In the absence of auxiliary optical depth or transmittance information, or self-determination of same for specialized observing situations, aerosol backscatter and extinction profiles cannot be retrieved from lidar observations along a single direction without an assumption linking aerosol extinction and backscatter (i.e., the aerosol extinction-to-backscatter ratio, or aerosol lidar ratio, Sa). Aerosol retrievals at 532 nm for the current GLAS and upcoming CALIPSO satellite lidar missions employ/can employ a look-up table approach to select climatologically based Samodel values for these retrievals when alternate, less uncertain methods for either defining Saor providing the needed auxiliary information are unavailable. This paper addresses a revised table look-up approach that incorporates two notable revisions for improved Saselection which, as a consequence, enable more bounded aerosol retrievals. One is a refined, more bounded set of Savalues, both for 532 nm and 1064 nm, representative of a definitive set of aerosol types/models determined from an extensive analysis of the global aerosol solar radiometer network, AERONET, data base. The other is an accompanying set of key spectral ratio parameters (i.e., dual wavelength, 532 nm to 1064 nm, ratios of backscatter, extinction and Sa) also derived from the AERONET data which offer additional ways to bound the lidar aerosol retrievals. Thus, aerosol retrievals can be obtained subject to the constraints that the lidar data yield retrievals with spectral ratio parameters consistent with a given aerosol model (or models), to confirm the model choice and better bound the retrievals. Examples of retrievals make subject to these constraints are included as a part of the paper

A key aspect to the recently-launched GLAS instrument is understanding its radiometric performance using on-orbit verification approaches. One of these approaches compares the reported backscattered signal from a surface to a predicted signal from that same surface. This returned signal depends on both the atmospheric transmittance and the surface reflectance in the backscatter direction. This work describes three methods that have been used to derive the backscatter surface reflectance for the prediction of the hard-target signal at the GLAS sensor. The first relies on a portable field spectrometer carried over a representative area of the surface and the reflected solar irradiance is measured with reference to a known field standard of reflectance. The difficulty with this approach is that it does not measure the backscatter reflectance. Thus, a second method using a laser-based system operating on the ground has been used to determine the surface reflectance. Both of these cases require that ground personnel be present near in time to the GLAS overpass. A third method, relying on reflectances derived from the MODIS sensor increases the available number of data sets for comparison to GLAS. Early results from all three approaches indicate agreement at better than 10% with the GLAS sensor.

The extinction-to-backscatter ratio (Sa) is an important parameter used in the determination of the aerosol extinction and subsequently the optical depth from lidar backscatter measurements. We outline the algorithm used to determine Sa for the Cloud and Aerosol Lidar and Infrared imager Pathfinder Spaceborne Observations (CALIPSO) lidar. Sa of the CALIPSO lidar will either be selected from a look-up table or calculated using the lidar measurements depending on the characteristics of aerosol layer. When lofted layers are encountered, Sa is computed directly from the integrated backscatter and transmittance. In all other cases, the CALIPSO observables: the depolarization ratio δ, the layer integrated attenuated backscatter γ', and the mean layer total attenuated color ratio χ, together with the surface type, are used to aid in aerosol typing. Once the type is identified, a look-up-table developed primarily from worldwide observations, is used to determine the Sa value. For aerosols in non-polar regions, CALIPSO aerosol models include desert dust, biomass burning, background, polluted continental, polluted dust, and marine aerosols. The polar aerosols are classified into three groups: arctic, polluted arctic, and antarctic aerosols.

In order to make optimal quantitative use of multi-wavelength spaceborne lidar data in the upcoming satellite lidar mission CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), it is essential that the lidar be well calibrated. In view of the use of a narrow bandwidth receiver filter in CALIPSO, it is necessary to quantitatively distinguish Cabannes scattering from the full bandwidth Rayleigh scattering for correct calibration of the 532 nm channel based on Rayleigh normalization. This also affects the 1064 nm calibration when it is implemented by the 532/1064 calibration ratio approach. Secondly, the calibration obtained by normalizing to a nearly Rayleigh background signal depends on the backscatter ratio R, defined as the ratio of the total backscattering coefficient [aerosol backscattering coefficient, /spl beta//sub a/(z), plus molecular backscattering coefficient, /spl beta//sub m/(z)] to the molecular backscattering coefficient, /spl beta//sub m/(z). How well this backscatter ratio, R, can be estimated in clean air regions will play an important role in lidar measurements of aerosol and cloud by CALIPSO. The LITE (Lidar In-space Technology Experiment) mission, the first lidar designed for atmospheric studies to fly in Earth orbit, provided an important database for doing the analysis and simulations for future lidar systems on free-flying satellite platforms. This paper presents calculations of Rayleigh/Cabannes scattering cross sections that should apply for CALIPSO by incorporating different depolarization factors appropriate for different spectral bandwidths. LITE data are analyzed to recover estimates of R characteristic of clean air regions. Errors in recovering R resulting from uncertainties in the calibration constant and two-way transmission from the calibration reference height are simulated and assessed.

A cost effective, miniature, Doppler wind lidar system based on atmospheric scattering from aerosols is presented. The initial design and theory of this instrument will be discussed. A method for minimizing the systematic error resulting from the component of the return signal that is backscattered by the atmospheric molecular constituents is also briefly described.

The Lidar In-space Technology Experiment (LITE) shuttle mission demonstrated that spaceborne lidar offers an effective means for detecting the spatial features of significant regional aerosol concentrations resulting, for example, from Saharan dust, African and South American biomass burning, urban plumes and the like. Quantitative retrievals of aerosol backscatter and extinction profiles have also been obtained from the LITE 532 nm data using initial LITE calibrations and preliminary assumptions/modeling constraints regarding the aerosol extinction-to-backscatter ratio, S/sub a/, or auxiliary transmittance information. Two upcoming satellite lidar missions, GLAS (Geoscience Laser Altimeter System) and CALIPSO(Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) have provided impetus for continued analysis of LITE data as a testbed for developing and validating improved aerosol retrieval approaches for these satellite missions. This paper presents updated LITE aerosol retrievals, including uncertainty assessments, enabled by revised calibration approaches (including the 1064 nm channel) and techniques/models for reducing the range in S/sub a/ values assumed for the retrievals.

Current multi-channel solar radiometers now allow for near-simultaneous collection of transmitted solar radiation in multiple spectral bands. Such simultaneous measurements are necessary for understanding the spectral nature of highly temporal phenomena such as cirrus clouds. Measurements of spectral optical depth from several locations in the desert southwest have been made by the University of Arizona for more than 10 years under both clear and cloudy conditions. Studies of the data collected under cirrus conditions indicate, as expected, that the transmittance through cirrus is nearly spectrally flat over a range of optical thicknesses. A recent data set collected at Ivanpah Playa, Nevada included measurements through a layer of cirrus clouds of varying thickness for a period of nearly three hours. These data were preceded by a two hour period of cloudless conditions with relatively stable atmospheric aerosol loading. Results from this data set indicate that the cirrus optical depth is spectrally flat to better than 6% over a range of optical depths from 0.10 to 0.30. Because of the spectrally flat nature of the cloud radiative properties, it is possible to use these clouds as hand-to-hand radiometric calibration targets for multichannel radiometers and two-channel lidar systems. The possible accuracy of such calibrations is presented based on the historical measurements of cirrus cloud transmittance.

In order to make optimal quantitative use of multiwavelength spaceborne lidar data, it is essential that the lidar be well calibrated. Due to system gain/efficiency changes that can be expected to occur during the course of a shuttle or satellite mission, it is essential to employ a calibration approach that can be implemented on-orbit, preferably repeatable at least a few times per orbit. For wavelengths less than about 550 nm, in situ calibration can be accomplished via normalization to high-altitude nearly molecular scattering regions. However, for longer wavelengths beyond about 800 nm, particularly the popular Nd: YAG fundamental wavelength at 1064 nm, the Rayleigh normalization approach becomes questionable due to both an inherently weaker signal and a stronger, variable, and somewhat unknown aerosol scattering contribution. For lidars operating at both longer and shorter wavelengths, a viable approach is to retrieve the longer wavelength calibrations ratioed to the shorter wavelength calibrations via comparisons of spectral backscatter from known/quantifiable scatterers. Cirrus clouds are good for this purpose because they occur at high altitudes with significant frequency and provide strong nearly spectrally flat backscatter. This paper presents both the molecular normalization and cirrus spectral backscatter ratio calibration approaches, including results obtained from case studies of lidar data collected during the LITE shuttle mission. Attention is focused on developing a simple autonomous approach applicable to satellite lidar missions such as Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) and the Geoscience Laser Altimeter System (GLAS).

A simple two-channel solar radiometer and data retrieval technique is described for sensing the columnar content of atmospheric water vapor via differential solar transmission measurements in and adjacent to the 940-nm water vapor absorption band. The instrument features two parallel channels for simultaneous measurements in and out of the absorption band to eliminate temporal variability effects in the differential comparison of the data from the two channels. The water vapor transmittance is determined by a modified Langley plot analysis of the ratio of the two channel signals. A statistical band model which closely follows the square-root law is then used to extract the columnar water vapor amount from the water vapor band transmittance. Error analyses and experimental results indicate that the instrument/technique can be reasonably employed to retrieve water vapor amounts with an error of 10% or less.>

Advances in the development and application of lidar as a tool for the remote sensing of atmospheric aerosols and clouds are reviewed. The lidar sensing technique is described, and various approaches for solving the lidar equation to retrieve aerosol properties are summarized. Examples are presented of lidar applications of aerosol and cloud sensing in both the troposphere and stratosphere. These include environmental monitoring, atmospheric boundary layer studies, retrieval of aerosol optical and physical properties, sensing of clouds, and investigation of volcanic effects in the stratosphere. Comments are offered regarding the future outlook for aerosol and cloud sensing by both ground-based and spaceborne lidar.>