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DOI: 10.5445/IR/1000073176

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

Andersen, Hendrik; Cermak, Jan; Fuchs, Julia; Knutti, Reto; Lohmann, Ulrike

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 ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Jahr 2017
Sprache Englisch
Identifikator ISSN: 1680-7324, 1680-7316
URN: urn:nbn:de:swb:90-731768
KITopen ID: 1000073176
Erschienen in Atmospheric chemistry and physics
Band 17
Heft 15
Seiten 9535-9546
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
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