Detection Lighe-Absorbing Aerosols And Their Properties From Satellite And AERONET Observations Over East Asia

Dust aerosol from dust source region, black carbon (BC) and organic carbon (OC) aerosols from biomass burning and fossil fuel are the three main types of light-absorbing aerosols. The radiative forcing due to light-absorbing aerosols is one of the largest sources of uncertainties in global and regional climate change. To identify the light-absorbing aerosols and estimate their optical properties have very important significance for understanding and estimating direct, semi-direct, and indirect effects by light-absorbing aerosols and climate change research. In this study, we use satellite observations to obtain the long-range transport and vertical distribution of dust aerosol, then, developed a new dust aerosol detection method. We also developed another new method to partition the light-absorbing aerosols using the AERONET observations.During the Pacific Dust Experiment (PACDEX), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and standard surface measurements are used to directly observe the long-range transport and vertical distribution of Asian dust aerosol in the free troposphere. The results show that two-layers dust aerosol structures in Pacific Ocean are often apparent, which may be associated with contributions from two major dust sources. The vertical distribution of the CALIOP backscattering/depolarization ratios indicate that non-spherically shaped dust aerosols floated from near the groud to an altitude of bellow5km in Gobi desert, which it usually takes three days to reach the Pacific Oceans and approximately9km around the Taklamakan desert, which need five or more days to arrive in the Pacific Oceans. This suggests the possible long-range transport of entrained dust aerosols via upper tropospheric westerly jets and it can be reached more distant.A new dust aerosol detection method was developed by combining the active CALIOP and passive Infrared Imaging Radiometer (IIR) measurements. This combined lidar and IR measurement (hereafter, CLIM) method uses the IIR tri-spectral IR brightness temperatures to discriminate between ice cloud and dense dust layers, and lidar measurements to detect thin dust and water cloud layers. The brightness temperature difference between10.60and12.05μm (BTD11-12) is typically negative for dense dust layer and generally positive for ice cloud layer, but it varies from negative to positive for thin dust layers, which the CALIOP correctly identifies. Results show that the CLIM method could significantly reduce misclassification rates to as low as-7%for the active dust season of spring2008over the Taklamakan Desert, which the National Aeronautics and Space Administration (NASA) version2CALIOP dust layer detection method misclassified about43%dust layers (almost dense dust layers) as cloud layers.Then, we developed a new method to partition the light-absorbing aerosols sources from AERONET observations. The aerosol spectral variations, scattering and absorption angstrom exponent from AERONET observations, are used to categorize6kinds of the absorption aerosols mixtures:Dust, Biomass Burning, Fossil Fuel, Mixed Dust with Biomass Burning, Mixed Biomass Burning with Fossil Fuel, and Mixed Pollution.For detecting the absorption aerosols from AERONET observations, another new method (three wavelengths method) was developed by using the absorption angstrom exponents (AAE) to indicate dust, black carbon, and organic carbon compositions. We found the dust AAE1(between440and675nm) and AAE2(between675and870nm) is2.24and1.29respectively, the black carbon AAE1is0.33and AAE2is0.69, and the organic carbon AAE1is4.21from the absorption aerosols mixtures data. Then we put the dust, black carbon, and organic carbon AAEs in the three wavelengths equations, to estimate their optical properties, and to compare the results with GOCART model results and field campaigns observations. The AODOC/AODBC and AAODOC/AAODBC ratios at550nm are1.33and0.26by using the three wavelengths method, and1.94and0.05from GOCART model. We found our results are more consistent with the field INDOEX and SAFARI campaigns, whose results show that the AODOC/AODBc at550nm is1.4-1.5, and AAODOC/AAODBC ratios is about0.27. These results allow a more accurate assessment of the effect of dust, black carbon, and organic carbon on climate.