Atlantic Multidecadal Oscillation footprint on global high cloud cover

Due to the complexity of the physical processes responsible for cloud formation and to the relatively short satellite database of continuous data records, cloud behavior in a warming climate remains uncertain. Identifying physical links between climate modes and clouds would contribute not only to a...

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Veröffentlicht in:Theoretical and applied climatology 2018-11, Vol.134 (3-4), p.1245-1256
Hauptverfasser: Vaideanu, Petru, Dima, Mihai, Voiculescu, Mirela
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Sprache:eng
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Zusammenfassung:Due to the complexity of the physical processes responsible for cloud formation and to the relatively short satellite database of continuous data records, cloud behavior in a warming climate remains uncertain. Identifying physical links between climate modes and clouds would contribute not only to a better understanding of the physical processes governing their formation and dynamics, but also to an improved representation of the clouds in climate models. Here, we identify the global footprint of the Atlantic Multidecadal Oscillation (AMO) on high cloud cover, with focus on the tropical and North Atlantic, tropical Pacific and on the circum-Antarctic sector. In the tropical band, the sea surface temperature (SST) and high cloud cover (HCC) anomalies are positively correlated, indicating a dominant role played by convection in mediating the influence of the AMO-related SST anomalies on the HCC field. The negative SST-HCC correlation observed in North Atlantic could be explained by the reduced meridional temperature gradient induced by the AMO positive phase, which would be reflected in less storms and negative HCC anomalies. A similar negative SST-HCC correlation is observed around Antarctica. The corresponding negative correlation around Antarctica could be generated dynamically, as a response to the intensified upward motion in the Ferrel cell. Despite the inherent imperfection of the observed and reanalysis data sets, the AMO footprint on HCC is found to be robust to the choice of dataset, statistical method, and specific time period considered.
ISSN:0177-798X
1434-4483
DOI:10.1007/s00704-017-2330-3