Open AccessAn assessment of the radiative effects of anthropogenic sulfate
Author(s) -
Chuang Catherine C.,
Penner Joyce E.,
Taylor Karl E.,
Grossman Allen S.,
Walton John J.
Publication year - 1997
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/96jd03087
Subject(s) - radiative forcing , aerosol , sulfate , atmospheric sciences , environmental science , sulfate aerosol , radiative transfer , forcing (mathematics) , climatology , range (aeronautics) , climate model , climate change , meteorology , oceanography , chemistry , physics , geology , materials science , organic chemistry , quantum mechanics , composite material
We use a coupled climate/chemistry model with cloud nucleation processes parameterized in terms of local aerosol number, anthropogenic sulfate mass concentration, and updraft velocity to investigate both direct and indirect anthropogenic sulfate radiative forcings. We estimate that the global direct radiative forcing is about −0.4 W m −2 with a maximum over Europe where the strongest anthropogenic sulfur emissions occur. With different approaches for the formation of anthropogenic sulfate and its relation to aerosol size distribution, we estimate that the indirect forcing may range from −0.6 to −1.6 W m −2 . This range reduces to −0.4 to −1.1 W m −2 if a prescribed marine background particle number concentration is universally applied over the ocean. Contrary to the direct effect which is more significant over continents, the calculated maximum of indirect forcing is located over the Atlantic Ocean near the coastline of North America. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the warming from increased greenhouse gases. We also compare the simulated cloud drop effective radii with those retrieved from satellite data to validate the accuracy of our cloud drop parameterization.