Substantial convection and precipitation enhancements by ultrafine aerosol particles

Simple item page
dc.contributor.authorFan, Jiwen
dc.contributor.authorRosenfeld, Daniel
dc.contributor.authorZhang, Yuwei
dc.contributor.authorGiangrande, Scott E.
dc.contributor.authorLi, Zhanqing
dc.contributor.authorMachado, Luiz A. T.
dc.contributor.authorMartin, Scot T.
dc.contributor.authorYang, Yan
dc.contributor.authorWang, Jian
dc.contributor.authorArtaxo, Paulo
dc.contributor.authorBarbosa, H. M. J.
dc.contributor.authorBraga, Ramon C.
dc.contributor.authorComstock, Jennifer M.
dc.contributor.authorFeng, Zhe
dc.contributor.authorGao, Wenhua
dc.contributor.authorGomes, Helber B.
dc.contributor.authorMei, Fan
dc.contributor.authorPöhlker, Christopher
dc.contributor.authorPöhlker, Mira L.
dc.contributor.authorPöschl, Ulrich
dc.contributor.authorde Souza, Rodrigo A. F.
dc.date.accessioned2024-06-28T18:10:06Z
dc.date.available2024-06-28T18:10:06Z
dc.date.issued2018-01-26
dc.description.abstractAerosol-cloud interactions remain the largest uncertainty in climate projections. Ultrafine aerosol particles smaller than 50 nanometers (UAP<₅₀) can be abundant in the troposphere but are conventionally considered too small to affect cloud formation. Observational evidence and numerical simulations of deep convective clouds (DCCs) over the Amazon show that DCCs forming in a low-aerosol environment can develop very large vapor supersaturation because fast droplet coalescence reduces integrated droplet surface area and subsequent condensation. UAP<₅₀ from pollution plumes that are ingested into such clouds can be activated to form additional cloud droplets on which excess supersaturation condenses and forms additional cloud water and latent heating, thus intensifying convective strength. This mechanism suggests a strong anthropogenic invigoration of DCCs in previously pristine regions of the world.
dc.description.sponsorshipThis study was supported by the U.S. DOE, Office of Science,Atmospheric System Research Program. The Pacific NorthwestNational Laboratory (PNNL) is operated for DOE by BattelleMemorial Institute under contract DE-AC06-76RLO1830. Thisresearch used PNNL Institutional Computing resources. Y.Z. andZ.L. were supported by NSF grant AGS1534670 and NationalScience Foundation of China grant 91544217. D.R. wassupported by project BACCHUS European CommissionFP7-603445. S.E.G. represents Brookhaven Science AssociatesLLC under DOE contract DE-SC0012704. The DOE AtmosphericRadiation Measurement (ARM) Climate Research Facility’s GoAmazon field campaign data were used. The x-band and s-band(SIPAM) radar data were supported by the CHUVA project. Wethank the GoAmazon team and the CHUVA team for their effort toproduce the observational data. We acknowledge support fromthe Central Office of the Large Scale Biosphere AtmosphereExperiment in Amazonia (LBA), Instituto Nacional de Pesquisas daAmazonia (INPA), Universidade do Estado do Amazonas (UEA),and the local Research Foundation (FAPEAM). L.A.T.M., P.A., andH.M.J.B. were supported by FAPESP grants 2009/15235-8,2013/05014-0, and 2013/50510-5. The work was conducted underauthorization 001030/2012-4 of the Brazilian National Councilfor Scientific and Technological Development (CNPq). Forthe operation of the ATTO site, we acknowledge support by theGerman Federal Ministry of Education and Research (BMBF contract 01LB1001A), the Brazilian Ministério da Ciência,Tecnologia e Inovação (MCTI/FINEP contract 01.11.01248.00), andthe Amazon State University (UEA), FAPEAM, LBA/INPA, andSDS/CEUC/RDS-Uatumã. We thank C. Schumacher and A. Funkat Texas A&M University for the SIPAM data, T. Biscaro for thex-band data, S. Tang at Lawrence Livermore National Laboratoryfor the input of local convective system selection, S. Hagos atPNNL for the input of model configuration, and C. Kuang atBrookhaven National Laboratory for help in understanding theuncertainty of Scanning Mobility Particle Sizer data. Theobservational data including x-band and SIPAM radar data fromCHUVA can be obtained from DOE ARM data archive www.archive.arm.gov/discovery/#v/results/s/fiop::amf2014goamazon, whichis available to the community. The model simulation data are archived at PNNL PIC and are available at https://dtn2.pnl.gov/data/jiwen/GoAmazon_simulations_sci/.
dc.description.urihttps://www.science.org/doi/10.1126/science.aan8461
dc.format.extent8 pages
dc.genrejournal articles
dc.identifierdoi:10.13016/m2futw-3nsz
dc.identifier.citationFan, Jiwen, Daniel Rosenfeld, Yuwei Zhang, Scott E. Giangrande, Zhanqing Li, Luiz A. T. Machado, Scot T. Martin, et al. “Substantial Convection and Precipitation Enhancements by Ultrafine Aerosol Particles.” Science 359, no. 6374 (January 26, 2018): 411–18. https://doi.org/10.1126/science.aan8461.
dc.identifier.urihttps://doi.org/10.1126/science.aan8461
dc.identifier.urihttp://hdl.handle.net/11603/34773
dc.language.isoen_US
dc.publisherAAAS
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Physics Department
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rightsPublic Domain
dc.rights.urihttps://creativecommons.org/publicdomain/mark/1.0/
dc.titleSubstantial convection and precipitation enhancements by ultrafine aerosol particles
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-4027-1855

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
science.aan8461.pdf
Size:
1.24 MB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
aan8461_fan_sm.pdf
Size:
3.45 MB
Format:
Adobe Portable Document Format
Download

Collections

UMBC Faculty Collection
UMBC Physics Department