Preprints
https://doi.org/10.5194/amtd-4-7597-2011
https://doi.org/10.5194/amtd-4-7597-2011

  19 Dec 2011

19 Dec 2011

Review status: this preprint was under review for the journal AMT. A revision for further review has not been submitted.

Aerosol optical depth retrieval in the Arctic region using MODIS based on prior knowledge

L. Mei1,8, Y. Xue1,2, G. de Leeuw3,4,5, T. Hou6,8, J. Guang1, L. Yang7, Y. Li1,8, H. Xu1,8, and X. He1,8 L. Mei et al.
  • 1State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijin
  • 2Faculty of Computing, London Metropolitan University, 166-220 Holloway Road, London N7 8DB, UK
  • 3Department of Physics, University of Helsinki, Helsinki, Finland
  • 4Finnish Meteorological Institute, Climate Change Unit, Helsinki, Finland
  • 5Netherlands Organisation for Applied Scientific Research TNO, Utrecht, The Netherlands
  • 6Center for Earth Observation and Digital Earth of the Chinese Academy of Sciences, Beijing 100094, China
  • 7School of Geography, Beijing Normal University, Beijing 100875, China
  • 8Graduate University of the Chinese Academy of Sciences, Beijing 100049, China

Abstract. The Arctic is especially vulnerable to the long-term transport of aerosols and other pollutants because aerosols can affect the albedo of the surface by deposition on snow and ice. However, aerosol observations for this area are sparse and hence there is considerable uncertainty in the knowledge on the properties of the Arctic aerosol. Arctic aerosol observations are needed to fill this gap because these are among the basic and most important parameters for researching the Arctic environment. Atmospheric remote sensing using satellites offers us an opportunity to describe the aerosol distribution in terms of both local, regional and global coverage. However, AOD retrieval over a bright surface remains a difficult task because it is hard to separate and explicitly describe the contribution of the observed signal reflected by the variable surface and back scattering by the semi-transparent aerosols, especially with a large solar or sensor zenith angle. In this paper, an approach using a synergetic approach with Moderate Resolution Imaging Spectroradiometer (MODIS) data based on prior knowledge is presented. The detailed analysis of the model demonstrates that it is suitable for Arctic region AOD retrieval. Six AERONET stations at high latitude (Andenes, Barrow, Ittoqqortoormiit, OPAL, Thule, and Tiksi) were used for validation, and the correlation coefficient between retrieved AODs and AERONET AODs was 0.75 and the retrieval absolute error is approximately 0.1, while the relative error is 20% (at some stations with clear skies as low as 10% was found). Furthermore, the Russian wildfires that occurred in late July of 2010 and their effect on the Arctic environment is presented; Satellite retrieved AODs in the Arctic increased to 1.0 during 1 August and 15 August 2010, even 2.0, during the burning phase, and subsequently returned to normal values (lower than 0.1), which was fully in line with the AERONET observations. This indicates that the fire plumes were transported to the Arctic region.

L. Mei et al.

 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

L. Mei et al.

L. Mei et al.

Viewed

Total article views: 2,018 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
546 1,393 79 2,018 65 63
  • HTML: 546
  • PDF: 1,393
  • XML: 79
  • Total: 2,018
  • BibTeX: 65
  • EndNote: 63
Views and downloads (calculated since 01 Feb 2013)
Cumulative views and downloads (calculated since 01 Feb 2013)

Saved

Latest update: 01 Aug 2021