Effect of water vapor on the determination of aerosol direct radiative effect based on the AERONET fluxes

• Published in: Atmospheric Chemistry and Physics
• Main Authors: J. Huttunen, A. Arola, G. Myhre, A. V. Lindfors, T. Mielonen, S. Mikkonen, J. S. Schafer, S. N. Tripathi, M. Wild, M. Komppula, K. E. J. Lehtinen
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2014
• Subjects: Physics; QC1-999; Chemistry; QD1-999; Aerosol Robotic Network
• Online Access: https://doi.org/10.5194/acp-14-6103-2014; https://doaj.org/article/666ed96feb7844fdadac14b35183c1ab

The aerosol direct radiative effect (ADRE) is defined as the change in the solar radiation flux, F , due to aerosol scattering and absorption. The difficulty in determining ADRE stems mainly from the need to estimate F without aerosols, F 0 , with either radiative transfer modeling and knowledge of the atmospheric state, or regression analysis of radiation data down to zero aerosol optical depth (AOD), if only F and AOD are observed. This paper examines the regression analysis method by using modeled surface data products provided by the Aerosol Robotic Network (AERONET). We extrapolated F 0 by two functions: a straight linear line and an exponential nonlinear decay. The exponential decay regression is expected to give a better estimation of ADRE with a few percent larger extrapolated F 0 than the linear regression. We found that, contrary to the expectation, in most cases the linear regression gives better results than the nonlinear. In such cases the extrapolated F 0 represents an unrealistically low water vapor column (WVC), resulting in underestimation of attenuation caused by the water vapor, and hence too large F 0 and overestimation of the magnitude of ADRE. The nonlinear ADRE is generally 40–50% larger in magnitude than the linear ADRE due to the extrapolated F 0 difference. Since for a majority of locations, AOD and WVC have a positive correlation, the extrapolated F 0 with the nonlinear regression fit represents an unrealistically low WVC, and hence too large F 0 . The systematic underestimation of F 0 with the linear regression is compensated by the positive correlation between AOD and water vapor, providing the better result.