HR: 0830h
AN: A11E-0030    [PDF]
TI: Aerosol Measurements on ACE-Asia and TRACE-P in Support of the Retrieval of CCN from Satellite
AU: * Kapustin, V N
EM: kapustin@soest.hawaii.edu
AF: University of Hawaii, School of Ocean and Earth Science and Technology, 1000 Pope Rd., MSB531, Honolulu, HI 96822 United States
AU: Clarke, A D
EM: tclarke@soest.hawaii.edu
AF: University of Hawaii, School of Ocean and Earth Science and Technology, 1000 Pope Rd., MSB531, Honolulu, HI 96822 United States
AU: Howell, S
EM: showell@soest.hawaii.edu
AF: University of Hawaii, School of Ocean and Earth Science and Technology, 1000 Pope Rd., MSB531, Honolulu, HI 96822 United States
AB: Aerosol size distributions measured in the size range from 0.01 to 10+ $\mu$m during TRACE-P and ACE-ASIA allow us to integrate aerosol number over any size range expected to be effective cloud condensation nuclei (CCN) and provide definition of a proxy for CCN (CCNproxy). Because of the mixed nature of the accumulation mode aerosol and the link between volatility and solubility this CCNproxy can be linked to the optical properties of the same size distributions at ambient conditions. This allows the relationships between CCNproxy and aerosol optical properties expected to be seen by satellites to be examined. Relative increases in coarse aerosol (e.g. dust) generally add little particle number to effective CCN but significantly increase scattering seen by satellite and drive the Angstrom exponent to approach zero. This has prompted the use of a so-called aerosol index (AI) based upon the product of the scattering and the non-dimensional Angstrom exponent, both capable of being inferred from satellite observations. The AI represents scattering weighting by the Angstrom exponent that is near zero for coarse particle contributions. This biases the AI to be closer to scattering values generated by particles in the accumulation mode (Angstrom exponent about 1 to 2) that dominate particle number. Hence, the CCNproxy range over an order of magnitude for a given scattering value but are tightly clustered for a given AI value. The observation made on TRACE and ACE-Asia demonstrates that under many conditions AI relates well to our measured CCNproxy and suggests it serves as a meaningful tool for satellite estimates of CCN.
DE: 0305 Aerosols and particles (0345, 4801)
DE: 0345 Pollution--urban and regional (0305)
SC: Atmospheric Sciences [A]
MN: 2003 Fall Meeting