Articles | Volume 9, issue 8
https://doi.org/10.5194/amt-9-3619-2016
https://doi.org/10.5194/amt-9-3619-2016
Research article
 | 
09 Aug 2016
Research article |  | 09 Aug 2016

A multi-wavelength classification method for polar stratospheric cloud types using infrared limb spectra

Reinhold Spang, Lars Hoffmann, Michael Höpfner, Sabine Griessbach, Rolf Müller, Michael C. Pitts, Andrew M. W. Orr, and Martin Riese

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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Cited articles

Achtert, P. and Tesche, M.: Assessing lidar-based classification schemes for polar stratospheric clouds based on 16 years of measurements at Esrange, Sweden, J. Geophys. Res., 119, 1386–1405, https://doi.org/10.1002/2013JD020355, 2014.
Alexander, S. P., Klekociuk, A. R., McDonald, A. J., and Pitts, M. C.: Quantifying the role of orographic gravity waves on polar stratospheric cloud occurrence in the Antarctic and the Arctic, J. Geophys. Res.-Atmos., 118, 11493–11507, https://doi.org/10.1002/2013JD020122, 2013.
Arnone, E., Castelli, E., Papandrea, E., Carlotti, M., and Dinelli, B. M.: Extreme ozone depletion in the 2010–2011 Arctic winter stratosphere as observed by MIPAS/ENVISAT using a 2-D tomographic approach, Atmos. Chem. Phys., 12, 9149–9165, https://doi.org/10.5194/acp-12-9149-2012, 2012.
Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua Mission: Design, Science Objective, Data Products, and Processing Systems, IEEE T. Geosci. Remote Sens., 41, 253–264, 2003.
Avery, M., Winker, D., Heymsfield, A., Vaughan, M., Young, S., Hu, Y., and Trepte, C.: Cloud ice water content retrieved from the CALIOP space-based lidar, Geophys. Res. Lett., 19, L05808, https://doi.org/10.1029/2011GL050545, 2012.
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Short summary
We present a new classification approach for different polar stratospheric cloud types. The so-called Bayesian classifier estimates the most likely probability that one of the three PSC types (ice, NAT, or STS) dominates the characteristics of a measured infrared spectrum. The entire measurement period of the satellite instrument MIPAS from July 2002 to April 2013 is processed using the new classifier.