Session 7.1 Derivation of Component Aerosol Direct Radiative Forcing for the Clear Sky by Combining Satellite Measurement and Model Simulations

Wednesday, 12 July 2006: 8:30 AM
Ballroom AD (Monona Terrace Community and Convention Center)
Tom X.-P. Zhao, CICS/ESSIC/UMCP & STAR/NESDIS/NOAA, Camp Springs, MD; and H. Yu, I. Laszlo, and M. Chin

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Satellite observations have been actively used for the estimation of global aerosol direct radiative effect (DRE) and observed size information has also been utilized to discriminate ensemble anthropogenic aerosol from natural aerosol in order to determine the global radiative effect of anthropogenic aerosols, termed as the aerosol direct radiative forcing (DRF). However, it is still difficult to use satellite observations alone to further discriminate aerosols into more detailed components (such as sea salt, dust, sulfate, black and organic carbons) over the globe as well as to derive their DRE/DRF. Since the aerosol DRE/DRF from different aerosol components can be very different, an accurate estimation of component aerosol DRE/DRF becomes important and deserves to be explored. Here, we explore a new approach that combines satellite measured aerosol DRE from the CERES instrument with the optical thickness fractions of major aerosol components from the NASA GOCART model to derive the component aerosol DRE/DRF over global oceans. Specifically, Terra/CERES-SSF shortwave (SW) flux data in 2001 will be combined with the GOCART model output and a SSF/MODIS-GOCART merged total aerosol optical thickness (AOT) product to derive top-of-atmosphere (TOA) component aerosol DRE/DRF over the global oceans for clear-sky conditions through a two-step approach. The first step is to drive the total aerosol DRE from the SSF SW fluxes and the second step is to partition the total aerosol DRE into the contributions of the five major aerosol components (black carbon, organic matter, sulfate, dust, and sea salt) by using the AOT fractions of the five component aerosols derived from the GOCART model simulations. The major uncertainties associated with the estimates will be analyzed and discussed.
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