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: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Volume 10, issue 9
Atmos. Chem. Phys., 10, 4241–4251, 2010
https://doi.org/10.5194/acp-10-4241-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 10, 4241–4251, 2010
https://doi.org/10.5194/acp-10-4241-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 May 2010

06 May 2010

Detection of dust aerosol by combining CALIPSO active lidar and passive IIR measurements

B. Chen1, J. Huang1, P. Minnis2, Y. Hu2, Y. Yi3, Z. Liu4, D. Zhang1, and X. Wang1 B. Chen et al.
  • 1Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Science, Lanzhou University, Lanzhou, 730000, China
  • 2NASA Langley Research Center, Hampton, VA, 23666, USA
  • 3Science Systems and Applications Incorporated, Hampton, VA, 23666, USA
  • 4National Institute of Aerospace, Hampton, VA, 23666, USA

Abstract. The version 2 Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) dust layer detection method, which is based only on lidar measurements, misclassified about 43% dust layers (mainly dense dust layers) as cloud layers over the Taklamakan Desert. To address this problem, a new method was developed by combining the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and passive Infrared Imaging Radiometer (IIR) measurements. This combined lidar and IR measurement (hereafter, CLIM) method uses the IIR tri-spectral IR brightness temperatures to discriminate between ice cloud and dense dust layers, and lidar measurements alone to detect thin dust and water cloud layers. The brightness temperature difference between 10.60 and 12.05 μm (BTD11−12) is typically negative for dense dust and generally positive for ice cloud, but it varies from negative to positive for thin dust layers, which the CALIPSO lidar correctly identifies. Results show that the CLIM method could significantly reduce misclassification rates to as low as ~7% for the active dust season of spring 2008 over the Taklamakan Desert. The CLIM method also revealed 18% more dust layers having greatly intensified backscatter between 1.8 and 4 km altitude over the source region compared to the CALIPSO version 2 data. These results allow a more accurate assessment of the effect of dust on climate.

Please read the corrigendum first before accessing the article.
Publications Copernicus
Download
Notice on corrigendum

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Citation