Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

Open access
Date
2017Type
- Journal Article
Abstract
The role of aerosols, clouds and their interactions with radiation remain among the largest unknowns in the climate system. Even though the processes involved are complex, aerosol–cloud interactions are often analyzed by means of bivariate relationships. In this study, 15 years (2001–2015) of monthly satellite-retrieved near-global aerosol products are combined with reanalysis data of various meteorological parameters to predict satellite-derived marine liquid-water cloud occurrence and properties by means of region-specific artificial neural networks. The statistical models used are shown to be capable of predicting clouds, especially in regions of high cloud variability. On this monthly scale, lower-tropospheric stability is shown to be the main determinant of cloud fraction and droplet size, especially in stratocumulus regions, while boundary layer height controls the liquid-water amount and thus the optical thickness of clouds. While aerosols show the expected impact on clouds, at this scale they are less relevant than some meteorological factors. Global patterns of the derived sensitivities point to regional characteristics of aerosol and cloud processes. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000192420Publication status
publishedExternal links
Journal / series
Atmospheric Chemistry and PhysicsVolume
Pages / Article No.
Publisher
European Geophysical SocietyOrganisational unit
03690 - Lohmann, Ulrike / Lohmann, Ulrike
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