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On the daily cycle of mesoscale cloud organization in the winter trades

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Schulz,  Hauke
Tropical Cloud Observations, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

Vial, J., Vogel, R., & Schulz, H. (2021). On the daily cycle of mesoscale cloud organization in the winter trades. Quarterly Journal of the Royal Meteorological Society, 147, 2850-2873. doi:10.1002/qj.4103.


Cite as: https://hdl.handle.net/21.11116/0000-0008-B868-4
Abstract
How spatial organization of clouds at the mesoscale contributes to the daily cycle of shallow cumulus clouds and precipitation is here explored, for the first time, using three years of high-frequency satellite- and ground-based observations. We focus on the four prominent patterns of cloud organization - Sugar, Gravel, Flowers and Fish - which were found recently to characterize well the variability of the North Atlantic winter trades. Our analysis is based on a simple framework to disentangle the parts of the daily cycle of trade-wind cloudiness that are due to changes in (a) the occurrence frequency of patterns, and (b) cloud cover for a given pattern. Our investigation reveals that the contribution of mesoscale organization to the daily cycle in cloudiness is largely mediated by the frequency of pattern occurrence. All forms of mesoscale organization exhibit a pronounced daily cycle in their frequency of occurrence, with distinct 24-hr phasing. The patterns Fish and Sugar can be viewed as daytime patterns, with a frequency peak around noon for Fish and towards sunset for Sugar. The patterns Gravel and Flowers appear instead as night-time patterns, with a peak occurrence around midnight for Gravel and before sunrise for Flowers. The cloud cover for a given pattern, however, always maximizes at night-time (between 0000 and 0300 hr), regardless of the specific pattern. Analyses of the role of large-scale environmental conditions shows that the near-surface wind speed can explain a large part of the diurnal variability in pattern frequency and cloudiness.