Articles | Volume 12, issue 7
https://doi.org/10.5194/amt-12-3521-2019
https://doi.org/10.5194/amt-12-3521-2019
Research article
 | 
02 Jul 2019
Research article |  | 02 Jul 2019

Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared

Tiziano Maestri, William Cossich, and Iacopo Sbrolli

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Cited articles

Adhikari, L., Whang, Z., and Deng, M.: Seasonal variations of Antarctic clouds observed by CloudSat and CALIPSO satellites, J. Geophys. Res.-Atmos., 117, D04202, https://doi.org/10.1029/2011JD016719, 2012. a
Ahmad, A.: Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis, Engineering, Technology and Applied Science Research, 2, 221–225, 2012. a
Amato, U., Lavanant, L., Liuzzi, G., Masiello, G., Serio, C., Stuhlmann, R., and Tjemkes, S. A.: Cloud mask via cumulative discriminant analysis applied to satellite infrared observations: scientific basis and initial evaluation, Atmos. Meas. Tech., 7, 3355–3372, https://doi.org/10.5194/amt-7-3355-2014, 2014. a
Bozzo, A., Maestri, T., and Rizzi, R.: Combining visible and infrared radiometry and lidar data to test simulations in clear and ice cloud conditions, Atmos. Chem. Phys., 10, 7369–7387, https://doi.org/10.5194/acp-10-7369-2010, 2010. a, b, c
Bromwich, D., Nicolas, J., M Hines, K., Kay, J., L Key, E., Lazzara, M., Lubin, D., Mcfarquhar, G., Gorodetskaya, I., Grosvenor, D., Lachlan-Cope, T., and Lipzig, N.: Tropospheric clouds in Antarctica, Rev. Geophys., 50, 2011RG000363, https://doi.org/10.1029/2011RG000363, 2012. a
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Short summary
An innovative and flexible methodology for cloud identification and classification, CIC, is tested on a synthetic dataset of high spectral resolution radiances in the far- and mid-infrared part of the spectrum, simulating measurements from the FORUM (Far Infrared Outgoing Radiation Understanding and Monitoring) mission. Results show that classification scores are greatly increased when far-infrared channels are accounted for and the identification of thin cirrus clouds is improved.
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