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  • Xin Kong
  • Renate Forkel
  • Peter Suppan
  • Alexander Baklanov
  • Michael Gauss
  • Dominik Brunner
  • Rocìo Barò
  • Alessandra Balzarini
  • Gabriele Curci
  • Pedro Jiménez-Guerrero
  • Marcus Hirtl
  • Luka Honzakj
  • Ulas Im
  • Juan Pérez
  • Guido Pirovano
  • Roberto San Jose
  • Heinke Schlünzenm
  • George Tsegas
  • Paolo Tuccella
  • Johannes Werhahn
  • Rahela Žabkar
  • Stefano Galmarini
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Original languageEnglish
Pages (from-to)527-540
JournalAtmospheric Environment
Journal publication dateAug 2015
Volume115
Early online date6 Sep 2014
DOIs
Publication statusPublished - Aug 2015

Abstract

This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.

Notes

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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