Sugar, Gravel, Fish, and Flowers: Dependence of Mesoscale Patterns of Trade-Wind Clouds on Environmental Conditions.

low‐cloud feedback mesoscale organization shallow convection trade‐wind clouds

Journal

Geophysical research letters
ISSN: 0094-8276
Titre abrégé: Geophys Res Lett
Pays: United States
ID NLM: 9882887

Informations de publication

Date de publication:
16 Apr 2020
Historique:
received: 25 10 2019
revised: 11 12 2019
accepted: 05 01 2020
entrez: 28 7 2020
pubmed: 28 7 2020
medline: 28 7 2020
Statut: ppublish

Résumé

Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large-scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low-level cloud amount, and cloud-radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low-cloud feedback should thus be investigated.

Identifiants

pubmed: 32713982
doi: 10.1029/2019GL085988
pii: GRL60093
pmc: PMC7375147
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e2019GL085988

Informations de copyright

©2020. The Authors.

Références

Philos Trans A Math Phys Eng Sci. 2015 Nov 13;373(2054):
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Proc Natl Acad Sci U S A. 2016 May 31;113(22):E3062-70
pubmed: 27185925
Surv Geophys. 2017;38(6):1331-1353
pubmed: 29238118
Surv Geophys. 2017;38(6):1529-1568
pubmed: 31997845

Auteurs

Sandrine Bony (S)

LMD/IPSL, CNRS, Sorbonne University Paris France.

Hauke Schulz (H)

Max Planck Institute for Meteorology Hamburg Germany.

Jessica Vial (J)

LMD/IPSL, CNRS, Sorbonne University Paris France.

Bjorn Stevens (B)

Max Planck Institute for Meteorology Hamburg Germany.

Classifications MeSH