92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Wednesday, 25 January 2012: 11:45 AM
Identifying Dust Aerosols Using Combined Active CALIOP and Passive IIR Measurements
Room 256 (New Orleans Convention Center )
Bin Chen, Lanzhou Univ., Lanzhou, China; and J. Huang, P. Minnis, and J. J. Liu

Abstract. Mineral dust emitted from arid and semi-arid regions plays an important role in climate and biogeochemical cycling. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) dust layer detection method, frequently misclassifies dust layers (mainly dense dust layers) as cloud layers over desert regions. A new method was developed by combining the active Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and passive Infrared Imaging Radiometer (IIR) measurements to conquer this problem. This combined lidar and IR measurement (hereafter, CLIM) method uses the IIR tri-spectral IR brightness temperatures difference to discriminate between ice cloud and dense dust layers, and lidar measurements to detect thin dust and water cloud layers. The brightness temperature difference between 10.60 and 12.05 μm (BTD11-12) is typically negative for dense dust and generally positive for ice cloud, but it varies from negative to positive for thin dust layers, which the CALIPSO lidar correctly identifies. The results show that the CLIM method could significantly reduce misclassification rates for the active dust season over the Taklamakan and Saharan Deserts. As Chen, B. et al. (2010) showed, the CALIOP dust detection method misclassified about 43% dust layers as cloud layers over Taklamakan Desert. However, the CLIM method could reduce the misclassification rates to as low as 7%.

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