Antarctic cloud detection and classification from far and mid infrared downwelling radiance spectra: performances optimization and results

This work aims at identifying the best performing mid- and far- infrared (MIR and FIR) joint spectralinterval to identify and classify clouds in the Antarctic region by mean of a machine learningalgorithm.About 1700 high spectral resolution radiances, collected during 2013 by the ground based RadiationExplorer in the Far InfraRed-Prototype for Applications and Development, REFIR-PAD (Palchetti etal., 2015) at Dome C, Antarctic Plateau, are co-located with backscatter and depolarization profilesderived from a tropospheric lidar system (Ricaud et al., 2017) to pre-classify clear sky, ice clouds, ormixed phase clouds.A machine learning cloud identification and classification algorithm named CIC (Maestri et al., 2019),trained with a pre-selected set of REFIR-PAD spectra, is applied to the selected radiance dataset byassuming that no other information than the spectrum itself is known.The CIC algorithm is applied by considering different spectral intervals, in order to maximize theclassification results for each class (clear sky, ice clouds, mixed phase clouds). A CIC "threat score" isdefined as the classification true positives divided by the sum of true positives, false positives, andfalse negatives. The maximization of the threat score is used to assess the algorithm performances thatspan from 58% to 96% in accordance with the selected interval. The best performing spectral range isthe 380-1000 cm -1 . The result, besides suggesting the importance of a proper algorithm calibration inaccordance with the used sensor, highlights the fundamental role of the far infrared part of thespectrum.The calibrated CIC algorithm is then applied to a larger REFIR-PAD dataset of about 90000 spectracollected from 2012 to 2015. Some results of the full dataset cloud classification are also presented.The present work contributes to the preparatory studies for the Far-infrared Outgoing RadiationUnderstanding and Monitoring (FORUM) mission that has recently been selected as ESA's 9 th EarthExplorer mission, scheduled for launch in 2026.References:Maestri, T., Cossich, W., and Sbrolli, I., 2019: Cloud identification and classification from high spectralresolution data in the far infrared and mid-infrared, Atmos. Meas. Tech., 12, pp. 3521 - 3540Palchetti, L., Bianchini, G., Di Natale, G., and Del Guasta, M., 2015: Far infrared radiative properties of watervapor and clouds in Antarctica. Bull. Amer. Meteor. Soc., 96, 1505-1518, doi: http://dx.doi.org/10.1175/BAMS-D-13-00286.1.Ricaud, P., Bazile, E., del Guasta, M., Lanconelli, C., Grigioni, P., and Mahjoub, A., 2017: Genesis of diamonddust, ice fog and thick cloud episodes observed and modelled above Dome C, Antarctica, Atmos. Chem. Phys.,17, 5221-5237, https://doi.org/10.5194/acp-17-5221-2017.