HR: 09:45h
AN: A21E-08    [Abstracts]
TI: GLAS Dual-Wavelength Lidar Aerosol Retrievals via CRAM
AU: * Reagan, J A
EM: reagan@ece.arizona.edu
AF: University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ 85721 United States
AU: Wang, Z
EM: xzwang@ece.arizona.edu
AF: University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ 85721 United States
AU: Palm, S
EM: spp@agnes.gsfc.nasa.gov
AF: Science Systems, and Applications, Inc., Lanham, MD 20706 United States
AU: Spinhirne, J
EM: jspin@virl.gsfc.nasa.gov
AF: NASA Goddard Spaceflight Center, Code 912, Greenbelt, MD 20771 United States
AB: Profiles of aerosol backscatter and extinction and layer averaged aerosol extinction-to-backscatter ratio, Sa, values have been retrieved from selected dual-wavelength lidar measurements made with the Geoscience Laser Altimeter System (GLAS) on the ICESat mission during the fall of 2003 (the period when both the 532 and 1064 nm lidar channels were operating close to expected performance levels). As is well know, aerosol backscatter and extinction profiles cannot be retrieved unambiguously from lidar observations without an assumption linking aerosol extinction and backscatter (e.g., Sa is reasonably spatially constant through a solution layer) as well as requiring additional boundary value or parameter specification information (e.g., a layer optical depth or specified value of Sa). The approach employed for spaceborne lidar aerosol retrievals (e.g., LITE, GLAS ICESat and upcoming CALIPSO missions) has been/will be to employ a look-up table approach to select climatological/geographically based model Sa values when alternate, less uncertain methods for either defining Sa or providing the needed auxiliary optical depth information are unavailable. Simply selecting the mean of Sa values cited in the literature is subject to too much uncertainty (Sa standard deviation ~ 30%) to yield retrievals sufficiently accurate to be really useful. A recent in-depth analysis of the global aerosol solar radiometer network, AERONET, data base has defined a relatively few, well defined aerosol types/models that predominately characterize aerosols observed around the world (Cattrall et al., JGR, 110, D10511, 2005). These model aerosols have well bounded Sa standard deviations of ~ 15% or less. However, assuming a specific model/Sa value for a given retrieval, even using climatological/geographic considerations in the model selection, does not assure that the model really applies/that the retrieval is really correct. This is where the Constrained Ratio Aerosol Model-fit (CRAM) approach (Reagan et al., Proc. IGARSS 2004, IEEE, pp. 1940-1943, 2004) can be applied to further bound/reduce uncertainty in the retrievals. Specifically, the aerosol models are characterized by spectral ratios (i.e., dual-wavelength, 532 to 1064 nm, ratios of backscatter extinction and Sa), with uncertainty windows, that permit aerosol retrievals to be obtained subject to the constraint that the lidar data yield retrievals with spectral ratio parameters consistent with a given assumed model (or models). CRAM has been successfully applied to both smoke and dust layers revealed in GLAS image data collected in October 2003. As these layers were elevated with clean regions below them, this permitted an independent determination of Sa via the self-transmittance retrieval approach, which further substantiated that the layers were well characterized by the assumed dust and smoke models. Presentation and discussion of the results obtained from these CRAM based aerosol retrievals, plus an overview of the CRAM approach and associated aerosol models, will constitute the major portion of this paper presentation.
DE: 0305 Aerosols and particles (0345, 4801, 4906)
SC: Atmospheric Sciences [A]
MN: Fall Meeting 2005