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Contrasting effects on deep convective clouds by different types of aerosols

Jiang, Jonathan H. and Su, Hui and Huang, Lei and Wang, Yuan and Massie, Steven and Zhao, Bin and Omar, Ali and Wang, Zhien (2018) Contrasting effects on deep convective clouds by different types of aerosols. Nature Communications, 9 . Art. No. 3874. ISSN 2041-1723. PMCID PMC6155150. doi:10.1038/s41467-018-06280-4.

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Convective clouds produce a significant proportion of the global precipitation and play an important role in the energy and water cycles. We quantify changes of the convective cloud ice mass-weighted altitude centroid (Z_(IWC)) as a function of aerosol optical thickness (AOT). Analyses are conducted in smoke, dust and polluted continental aerosol environments over South America, Central Africa and Southeast Asia, using the latest measurements from the CloudSat and CALIPSO satellites. We find aerosols can inhibit or invigorate convection, depending on aerosol type and concentration. On average, smoke tends to suppress convection and results in lower Z_(IWC) than clean clouds. Polluted continental aerosol tends to invigorate convection and promote higher Z_(IWC). The dust aerosol effects are regionally dependent and their signs differ from place to place. Moreover, we find that the aerosol inhibition or invigoration effects do not vary monotonically with AOT and the variations depend strongly on aerosol type. Our observational findings indicate that aerosol type is one of the key factors in determining the aerosol effects on convective clouds.

Item Type:Article
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URLURL TypeDescription CentralArticle
Jiang, Jonathan H.0000-0002-5929-8951
Su, Hui0000-0003-1265-9702
Huang, Lei0000-0002-4941-7814
Wang, Yuan0000-0001-6657-8401
Zhao, Bin0000-0001-8438-9188
Omar, Ali0000-0003-1871-9235
Additional Information:© The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Received 12 February 2018; Accepted 27 July 2018; Published 24 September 2018. The data used for this study can be downloaded from the NASA Distributed Active Archive Centers at This research is supported by NASA CCST and ACMAP programs. The work was conducted at the NASA sponsored Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. We also acknowledge the support by the NASA Langley Research Center, University of California, Los Angeles, University of Colorado, Boulder and the University of Wyoming. Author Contributions: J.H.J. designed the analysis and wrote the paper. J.H.J. and L.H. processed, computed and analyzed the CloudSat and CALIPSO data. H.S., Y.W., S.M. and B.Z. contributed to the data analysis and writing of the paper. A.O. and Z.W. provided guideline for CloudSat and CALIPSO data processing and usage. Everyone edited the manuscript. The authors declare no competing interests.
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PubMed Central ID:PMC6155150
Record Number:CaltechAUTHORS:20181008-133238661
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90154
Deposited By: Tony Diaz
Deposited On:08 Oct 2018 21:48
Last Modified:16 Nov 2021 00:41

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