Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
AMT | Articles | Volume 12, issue 4
Atmos. Meas. Tech., 12, 2261–2285, 2019
https://doi.org/10.5194/amt-12-2261-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: CALIPSO version 4 algorithms and data products

Atmos. Meas. Tech., 12, 2261–2285, 2019
https://doi.org/10.5194/amt-12-2261-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Apr 2019

Research article | 12 Apr 2019

Application of high-dimensional fuzzy k-means cluster analysis to CALIOP/CALIPSO version 4.1 cloud–aerosol discrimination

Shan Zeng et al.
Related authors  
Discriminating between clouds and aerosols in the CALIOP version 4.1 data products
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019,https://doi.org/10.5194/amt-12-703-2019, 2019
Short summary
Related subject area  
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A new approach to estimate supersaturation fluctuations in stratocumulus cloud using ground-based remote-sensing measurements
Fan Yang, Robert McGraw, Edward P. Luke, Damao Zhang, Pavlos Kollias, and Andrew M. Vogelmann
Atmos. Meas. Tech., 12, 5817–5828, https://doi.org/10.5194/amt-12-5817-2019,https://doi.org/10.5194/amt-12-5817-2019, 2019
Short summary
ELIFAN, an algorithm for the estimation of cloud cover from sky imagers
Marie Lothon, Paul Barnéoud, Omar Gabella, Fabienne Lohou, Solène Derrien, Sylvain Rondi, Marjolaine Chiriaco, Sophie Bastin, Jean-Charles Dupont, Martial Haeffelin, Jordi Badosa, Nicolas Pascal, and Nadège Montoux
Atmos. Meas. Tech., 12, 5519–5534, https://doi.org/10.5194/amt-12-5519-2019,https://doi.org/10.5194/amt-12-5519-2019, 2019
Short summary
Estimating solar irradiance using sky imagers
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, and Stefan Winkler
Atmos. Meas. Tech., 12, 5417–5429, https://doi.org/10.5194/amt-12-5417-2019,https://doi.org/10.5194/amt-12-5417-2019, 2019
Short summary
Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties
Penny M. Rowe, Christopher J. Cox, Steven Neshyba, and Von P. Walden
Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019,https://doi.org/10.5194/amt-12-5071-2019, 2019
Short summary
Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products
Hye-Sil Kim, Bryan A. Baum, and Yong-Sang Choi
Atmos. Meas. Tech., 12, 5039–5054, https://doi.org/10.5194/amt-12-5039-2019,https://doi.org/10.5194/amt-12-5039-2019, 2019
Short summary
Cited articles  
Avery, M. A., Ryan, R., Getzewich, B., Vaughan, M., Winker, D., Hu, Y., and Trepte, C.: Impact of Near-Nadir Viewing Angles on CALIOP V4.1 Cloud Thermodynamic Phase Assignments, in preparation, 2019. 
Bezdek, J. C.: Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981. 
Bezdek, J. C., Ehrlich, R., and Full, W.: FCM: the fuzzy c-means clustering algorithm, Comput. Geosci., 10, 191–203, 1984. 
Burrough P. A. and McDonnell R. A.: Principles of Geographic Information Systems, Oxford University Press, Oxford, 1998. 
Burrough, P. A., Van Gaans, P. F. M., and MacMillan, R. A.: High-resolution landform classification using fuzzy K-means, Fuzzy Set. Syst., 113, 37–52, 2000. 
Publications Copernicus
Download
Short summary
We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol...
Citation