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dc.contributor.authorSmith, Molly B.
dc.contributor.authorMahowald, Natalie M.
dc.contributor.authorAlbani, Samuel
dc.contributor.authorPerry, Aaron
dc.contributor.authorLosno, Remi
dc.contributor.authorQu, Zihan
dc.contributor.authorMarticorena, Beatrice
dc.contributor.authorRidley, David Andrew
dc.contributor.authorHeald, Colette L.
dc.date.accessioned2017-06-07T19:29:45Z
dc.date.available2017-06-07T19:29:45Z
dc.date.issued2017-03
dc.date.submitted2016-12
dc.identifier.issn1680-7324
dc.identifier.issn1680-7316
dc.identifier.urihttp://hdl.handle.net/1721.1/109715
dc.description.abstractInterannual variability in desert dust is widely observed and simulated, yet the sensitivity of these desert dust simulations to a particular meteorological dataset, as well as a particular model construction, is not well known. Here we use version 4 of the Community Atmospheric Model (CAM4) with the Community Earth System Model (CESM) to simulate dust forced by three different reanalysis meteorological datasets for the period 1990–2005. We then contrast the results of these simulations with dust simulated using online winds dynamically generated from sea surface temperatures, as well as with simulations conducted using other modeling frameworks but the same meteorological forcings, in order to determine the sensitivity of climate model output to the specific reanalysis dataset used. For the seven cases considered in our study, the different model configurations are able to simulate the annual mean of the global dust cycle, seasonality and interannual variability approximately equally well (or poorly) at the limited observational sites available. Overall, aerosol dust-source strength has remained fairly constant during the time period from 1990 to 2005, although there is strong seasonal and some interannual variability simulated in the models and seen in the observations over this time period. Model interannual variability comparisons to observations, as well as comparisons between models, suggest that interannual variability in dust is still difficult to simulate accurately, with averaged correlation coefficients of 0.1 to 0.6. Because of the large variability, at least 1 year of observations at most sites are needed to correctly observe the mean, but in some regions, particularly the remote oceans of the Southern Hemisphere, where interannual variability may be larger than in the Northern Hemisphere, 2–3 years of data are likely to be needed.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (0932946)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (1003509)en_US
dc.description.sponsorshipUnited States. Department of Energy (DE-SC0006735)en_US
dc.description.sponsorshipUnited States. Department of Energy (DE-SC0016362)en_US
dc.description.sponsorshipUnited States. National Aeronautics and Space Administration (NN14AP38G)en_US
dc.language.isoen_US
dc.publisherCopernicus GmbHen_US
dc.relation.isversionofhttp://dx.doi.org/10.5194/acp-17-3253-2017en_US
dc.rightsCreative Commons Attribution 3.0 Unported licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en_US
dc.sourceCopernicus Publicationsen_US
dc.titleSensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataseten_US
dc.typeArticleen_US
dc.identifier.citationSmith, Molly B.; Mahowald, Natalie M.; Albani, Samuel; Perry, Aaron; Losno, Remi; Qu, Zihan; Marticorena, Beatrice; Ridley, David A. and Heald, Colette L. “Sensitivity of the Interannual Variability of Mineral Aerosol Simulations to Meteorological Forcing Dataset.” Atmospheric Chemistry and Physics 17, no. 5 (March 7, 2017): 3253–3278 © Author(s) 2017en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.mitauthorRidley, David Andrew
dc.contributor.mitauthorHeald, Colette L.
dc.relation.journalAtmospheric Chemistry and Physicsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSmith, Molly B.; Mahowald, Natalie M.; Albani, Samuel; Perry, Aaron; Losno, Remi; Qu, Zihan; Marticorena, Beatrice; Ridley, David A.; Heald, Colette L.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-3890-0197
dc.identifier.orcidhttps://orcid.org/0000-0003-2894-5738
mit.licensePUBLISHER_CCen_US


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