Cloud Patterns in the Trades Have Four Interpretable Dimensions

Martin Janssens*, Jordi Vilà‐Guerau De Arellano, Marten Scheffer, Coco Antonissen, A.P. Siebesma, Franziska Glassmeier

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Shallow cloud fields over the subtropical ocean exhibit many spatial patterns. The frequency of occurrence of these patterns can change under global warming. Hence, they may influence subtropical marine clouds’ climate feedback. While numerous metrics have been proposed to quantify cloud patterns, a systematic, widely accepted description is still missing. Therefore, this study suggests one. We compute 21 metrics for 5,000 satellite scenes of shallow clouds over the subtropical Atlantic Ocean and translate the resulting data set to its principal components (PCs). This yields a unimodal, continuous distribution without distinct classes, whose first four PCs explain 82% of all 21 metrics’ variance. The PCs correspond to four interpretable dimensions: Characteristic length, void size, directional alignment, and horizontal cloud top height variance. These dimensions span a space in which an effective pattern description can be given, which may be used to better understand the patterns’ underlying physics and feedback on climate.
Original languageEnglish
Article numbere2020GL091001
JournalGeophysical Research Letters
Volume48
Issue number5
Early online date16 Feb 2021
DOIs
Publication statusPublished - 16 Mar 2021

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