Preprints
https://doi.org/10.5194/egusphere-2023-2463
https://doi.org/10.5194/egusphere-2023-2463
08 Nov 2023
 | 08 Nov 2023

The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) principal component-based cloud mask: A simulation experiment

Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo

Abstract.

We describe a cloud mask simulation experiment developed for the PREFIRE mission. The basis of the cloud mask is a principal component (PC) methodology (PC-MSK) adapted from the algorithm heritage of the upcoming Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission. Simulated clear-sky and cloudy-sky PREFIRE radiances are calculated from the Goddard Earth Observing System (GEOS) meteorological fields and include a variety of complex cloud configurations. The simulation experiment is based on local training that is adjusted along segments of simulated orbits that mimic actual PREFIRE orbits. A numerically stable method of separating clear sky from cloudy sky is achieved using Otsu’s binary classification method and requires no a priori thresholding estimate for multimodal histograms. Comparisons are made against a machine-learning cloud mask (ML-MSK) developed for the PREFIRE mission. The global hit rate of PC-MSK (92.6 %) compares favorably to the hit rate of ML-MSK (95.3 %). The Arctic hit rate of PC-MSK (86.7 %) compares favorably to the hit rate of ML-MSK (89.4 %) and both cloud masks are shown to meet mission requirements for PREFIRE cloud detection. The simulation experiment demonstrates the potential for accurate cloud masking with PREFIRE despite a low number of information-containing PCs compared to those obtained from hyperspectral infrared sounders. We conclude with a discussion about clear-sky and cloudy-sky training sets that are suitable for an operational version of PC-MSK and their development during the post-launch checkout time period.

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Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2463', Anonymous Referee #1, 31 Jan 2024
    • AC1: 'Reply on RC1', Brian Kahn, 22 Apr 2024
  • RC2: 'Comment on egusphere-2023-2463', Anonymous Referee #2, 01 Feb 2024
    • AC2: 'Reply on RC2', Brian Kahn, 22 Apr 2024
  • RC3: 'Comment on egusphere-2023-2463', Anonymous Referee #3, 07 Feb 2024
    • AC3: 'Reply on RC3', Brian Kahn, 22 Apr 2024
Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo
Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo

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Short summary
A cloud detection mask algorithm is developed for the upcoming Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) satellite mission to be launched by NASA in May 2024. The cloud mask is compared to "truth" and is capable of detecting over 90 % of all clouds globally tested with simulated data, and about 87 % of all clouds in the Arctic region.