A new statistical approach to improve the satellite-based estimation of the radiative forcing by aerosol–cloud interactions
In a previous study of Quaas et al. (2008) the radiative forcing by anthropogenic aerosol due to aerosol–cloud interactions, RF<sub>aci</sub>, was obtained by a statistical analysis of satellite retrievals using a multilinear regression. Here we employ a new statistical approach to obtai...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-03-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | http://www.atmos-chem-phys.net/17/3687/2017/acp-17-3687-2017.pdf |
| Summary: | In a previous study of Quaas et al. (2008) the radiative forcing by
anthropogenic aerosol due to aerosol–cloud interactions, RF<sub>aci</sub>, was
obtained by a statistical analysis of satellite retrievals using a
multilinear regression. Here we employ a new statistical approach to obtain
the fitting parameters, determined using a nonlinear least square
statistical approach for the relationship between planetary albedo and cloud
properties and, further, for the relationship between cloud properties and
aerosol optical depth. In order to verify the performance, the results from
both statistical approaches (previous and present) were compared to the
results from radiative transfer simulations over three regions for different
seasons. We find that the results of the new statistical approach agree well
with the simulated results both over land and ocean. The new statistical
approach increases the correlation by 21–23 % and reduces the error compared to the previous approach. |
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| ISSN: | 1680-7316 1680-7324 |