Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.509 IF 5.509
  • IF 5-year value: 5.689 IF 5-year 5.689
  • CiteScore value: 5.44 CiteScore 5.44
  • SNIP value: 1.519 SNIP 1.519
  • SJR value: 3.032 SJR 3.032
  • IPP value: 5.37 IPP 5.37
  • h5-index value: 86 h5-index 86
  • Scimago H index value: 161 Scimago H index 161
Volume 18, issue 7
Atmos. Chem. Phys., 18, 5021-5043, 2018
https://doi.org/10.5194/acp-18-5021-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Coupled chemistry–meteorology modelling: status and...

Atmos. Chem. Phys., 18, 5021-5043, 2018
https://doi.org/10.5194/acp-18-5021-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Apr 2018

Research article | 12 Apr 2018

An assessment of aerosol optical properties from remote-sensing observations and regional chemistry–climate coupled models over Europe

Laura Palacios-Peña1, Rocío Baró1,2, Alexander Baklanov3, Alessandra Balzarini4, Dominik Brunner5, Renate Forkel6, Marcus Hirtl2, Luka Honzak7, José María López-Romero1, Juan Pedro Montávez1, Juan Luis Pérez8, Guido Pirovano4, Roberto San José8, Wolfram Schröder9, Johannes Werhahn6, Ralf Wolke9, Rahela Žabkar10, and Pedro Jiménez-Guerrero1 Laura Palacios-Peña et al.
  • 1Department of Physics, Regional Campus of International Excellence Campus Mare Nostrum, University of Murcia, Murcia, Spain
  • 2Section Chemical Weather Forecasts, Division Data/Methods/Modeling, ZAMG – Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
  • 3World Meteorological Organization, Geneva, Switzerland
  • 4Ricerca sul Sistema Energetico (RSE), Milan, Italy
  • 5Laboratory for Air Pollution and Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
  • 6Karlsruher Institut für Technologie (KIT), Institut für Meteorologie und Klimaforschung, Atmosphärische Umweltforschung (IMK-IFU), Garmisch-Partenkirchen, Germany
  • 7BO-MO d.o.o, Ljubljana Slovenia
  • 8Environmental Software and Modelling Group, Computer Science School – Technical University of Madrid, Madrid, Spain
  • 9Leibniz Institute for Tropospheric Research, Leipzig, Germany
  • 10Slovenian Environment Agency, Ljubljana, Slovenia

Abstract. Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry–climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol–radiation (ARI) or/and aerosol–cloud interactions (ACI) help improve the skills of modelling outputs.

Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality–climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).

Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30% in the model error) and AE (between 20 and 75%) is important to provide a better description of aerosol–radiation–cloud interactions in regional climate models.

Publications Copernicus
Special issue
Download
Short summary
Atmospheric aerosols modify the radiative budget of the Earth, and it is therefore mandatory to have an accurate representation of their optical properties for understanding their climatic role. This work therefore evaluates the skill in the representation of optical properties by different remote-sensing sensors and regional online coupled chemistry–climate models over Europe.
Atmospheric aerosols modify the radiative budget of the Earth, and it is therefore mandatory to...
Citation
Share