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Sugar, gravel, fish and flowers: Mesoscale cloud patterns in the trade winds

Stevens, Bjorn and Bony, Sandrine and Brogniez, Hélène and Hentgen, Laureline and Hohenegger, Cathy and Kiemle, Christoph and L'Ecuyer, Tristan S. and Naumann, Ann Kristin and Schulz, Hauke and Siebesma, Pier A. and Vial, Jessica and Winker, Dave M. and Zuidema, Paquita (2020) Sugar, gravel, fish and flowers: Mesoscale cloud patterns in the trade winds. Quarterly Journal of the Royal Meteorological Society, 146, pp. 141-152. Wiley. DOI: 10.1002/qj.3662 ISSN 0035-9009

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Official URL: http://dx.doi.org/10.1002/qj.3662


An activity designed to characterise patterns of mesoscale (20 to 2,000 km) organisation of shallow clouds in the downstream trades is described. Patterns of mesoscale organisation observed from space were subjectively defined and learned by 12 trained scientists. The ability of individuals to communicate, learn and replicate the classification was evaluated. Nine-hundred satellite images spanning the area from 48W to 58W, 10N to 20N for the boreal winter months (December–February) over 10 years (2007/2008 to 2016/2017) were classified. Each scene was independently labelled by six scientists as being dominated by one of six patterns (one of which was “no-pattern”). Four patterns of mesoscale organisation could be labelled in a reproducible manner, and were labelled Sugar, Gravel, Fish and Flowers. Sugar consists of small, low clouds of low reflectivity, Gravel clouds form along apparent gust fronts, Fish are skeletal networks (often fishbone-like) of clouds, while Flowers are circular clumped features defined more by their stratiform cloud elements. Both Fish and Flowers are surrounded by large areas of clear air. These four named patterns were identified 40% of the time, with the most common pattern being Gravel. Sugar was identified the least and suggests that unorganised and very shallow convection is unlikely to dominate large areas of the downstream trade winds. Some of the patterns show signs of seasonal and interannual variability, and some degree of scale selectivity. Comparison of typical patterns with radar imagery suggests that even this subjective and qualitative visual inspection of imagery appears to capture several important physical differences between shallow cloud regimes, such as precipitation and radiative effects.

Item URL in elib:https://elib.dlr.de/131194/
Document Type:Article
Title:Sugar, gravel, fish and flowers: Mesoscale cloud patterns in the trade winds
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Stevens, BjornMPI für Meteorologie, HamburgUNSPECIFIED
Bony, SandrineSorbonne Université, Paris, FrankreichUNSPECIFIED
Brogniez, HélèneLatmos/IPSL, FrankreichUNSPECIFIED
Hentgen, LaurelineIAC, ETH Zürich, SchweizUNSPECIFIED
Hohenegger, CathyMPI für Meteorologie, HamburgUNSPECIFIED
Kiemle, ChristophDLR, IPAhttps://orcid.org/0000-0003-1231-2813
L'Ecuyer, Tristan S.Univ. Madison-Wisconsin, Madison, USAUNSPECIFIED
Naumann, Ann KristinMPI für Meteorologie, HamburgUNSPECIFIED
Schulz, HaukeMPI für Meteorologie, HamburgUNSPECIFIED
Siebesma, Pier A.Univ. Delft, NiederlandeUNSPECIFIED
Vial, JessicaSorbonne Université, Paris, FrankreichUNSPECIFIED
Winker, Dave M.NASA Langley, Hamption, VA, USAUNSPECIFIED
Zuidema, PaquitaUniv. Miami, FL, USAUNSPECIFIED
Date:January 2020
Journal or Publication Title:Quarterly Journal of the Royal Meteorological Society
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1002/qj.3662
Page Range:pp. 141-152
Keywords:cloud feedbacks, mesoscale organisation, shallow convection, trade clouds
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben LIDAR-Forschung und -Entwicklung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Lidar
Deposited By: Kiemle, Dr.rer.nat. Christoph
Deposited On:25 Nov 2019 10:56
Last Modified:27 May 2020 13:15

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