Comparisons of a chemical transport model with a four-year (April to September) analysis of fine- and coarse-mode aerosol optical depth retrievals over the Canadian Arctic

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1080/07055900.2017.1356263
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Name affiliation
  1. National Research Council Canada. Aerospace
FormatText
TypeArticle
Journal titleAtmosphere-Ocean
ISSN0705-5900
1480-9214
Volume55
Issue4-5
Pages213–229
SubjectAERONET; aerosol optical depth; Arctic; chemical transport model; GEOS-Chem
Abstract
We compared April to September retrievals of total, fine-mode (sub-micron), and coarse-mode (super-micron) aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET) with simulations from a global three-dimensional chemical transport model, the Goddard Earth Observing System (GEOS-Chem), across five Arctic stations and a four-year sampling period. It was determined that the AOD histograms of both the retrievals and the simulations were better represented by a lognormal distribution and that the successful simulation of this empirical feature as well as its consequences (including a better model versus retrieval coefficient of determination in log-log AOD space) represented a general indicator of model evaluation success. Seasonal (monthly averaged) AOD retrievals were sensitive to the way in which the averaging was performed; this was ascribed to the presence of highly variable fine-mode smoke in the western Arctic. The retrieved and modelled station-by-station fine-mode AOD averages showed a peak in April/May that decreased over the summer, while the model underestimated the fine-mode AOD by an average of about 0.004 (∼6%). Both the retrievals and simulations showed seasonal coarse-mode AOD variations with a peak in April/May that was attributed to Asian and/or Saharan dust. The model's success in capturing such weak seasonal events helps to confirm the relevance of the separation of the fine and coarse modes and the general validity of model estimates in the Arctic.
Publication date
PublisherTaylor & Francis
Terms of use
LanguageEnglish
Peer reviewedYes
NPARC number23002672
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Record identifierc09204f2-fcda-4417-9173-415b0b6ed48f
Record created2017-12-19
Record modified2017-12-19
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