A21F-3098:
Global aerosol typing from a combination of A-Train satellite observations in clear-sky and above clouds
Tuesday, 16 December 2014
Meloe S Kacenelenbogen1, Philip B Russell2, Mark Vaughan3, Jens Redemann4, Yohei Shinozuka1, John M Livingston5 and Qin Zhang1, (1)Bay Area Environmental Research Institute Sonoma, Sonoma, CA, United States, (2)NASA-Ames Research Center, Moffett Field, CA, United States, (3)NASA, Hampton, VA, United States, (4)NASA Ames Research Center, Moffett Field, CA, United States, (5)SRI International Palo Alto, Palo Alto, CA, United States
Abstract:
According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the model estimates of Radiative Forcing due to aerosol-radiation interactions (RFari) for individual aerosol types are less certain than the total RFari [Boucher et al., 2013]. For example, the RFari specific to Black Carbon (BC) is uncertain due to an underestimation of its mass concentration near source regions [Koch et al., 2009]. Several recent studies have evaluated chemical transport model (CTM) predictions using observations of aerosol optical properties such as Aerosol Optical Depth (AOD) or Single Scattering Albedo (SSA) from satellite or ground-based instruments (e.g., Huneeus et al., [2010]). However, most passive remote sensing instruments fail to provide a comprehensive assessment of the particle type without further analysis and combination of measurements. To improve the predictions of aerosol composition in CTMs, we have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground based passive remote sensing instruments [Russell et al., 2014]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke and pure marine. First, we apply the SCMC method to five years of clear-sky space-borne POLDER observations over Greece. We then use the aerosol extinction and SSA spectra retrieved from a combination of MODIS, OMI and CALIOP clear-sky observations to infer the aerosol type over the globe in 2007. Finally, we will extend the spaceborne aerosol classification from clear-sky to above low opaque water clouds using a combination of CALIOP AOD and backscatter observations and OMI absorption AOD values from near-by clear-sky pixels.
