Cloud identification and classification from high spectral resolution data in the far and mid infrared Tiziano Maestri 1 , William Cossich 1 , and Iacopo Sbrolli 1 1 Alma Mater Studiorum - Università di Bologna Correspondence: tiziano.maestri@unibo.it Abstract. A new Cloud Identification and Classification algorithm, named CIC, is presented. CIC is a machine-learning algo- rithm, based on Principal Component Analysis, able to perform a cloud detection and scene classification using a univariate distribution and a threshold, which serves as a binary classifier. CIC is tested on a widespread synthetic dataset of high spectral resolution radiances in the far and mid infrared part of the spectrum simulating measurements from the ESA Earth Explorer Fast Track 9 competing mission FORUM (Far Infrared Outgoing Radiation Understanding and Monitoring) that is currently 5 (2018/19) undergoing the industrial and scientific Phase-A studies. Simulated spectra are representatives of many diverse cli- matic areas, ranging from the tropical to polar regions. Application of the algorithm to the synthetic dataset provides high scores for clear/cloud identification, especially when optimisation processes are performed. One of the main results consists in pointing out the high information content of spectral radiance in the far-infrared region of the electromagnetic spectrum to identify cloudy scenes specifically thin cirrus clouds. 10 1 Introduction At the end of 2017 the European Space Agency has selected FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission as one of the two instrument concepts to compete for the Earth Explorer 9 satellite program. FORUM is based on a Far-Infrared Spectrometer devoted to high spectral resolution (nominally 0.3 cm −1 ) measurements from 100 to 1600 cm −1 thus including the so called Far InfraRed (FIR) region, spanning from 100 to 667 cm −1 . 15 The FIR represents an important fraction of Earth’s outgoing longwave radiation, which contributes considerably to the planetary energy balance. The atmospheric emission in the FIR is driven by the rotational absorption band of the water vapour molecules and is characterised by strong absorption lines interspersed by narrow regions (called dirty micro-windows), where absorption is less intense. The strong absorption features of water vapor roto-vibrational lines cause atmospheric weighting functions in the FIR to peak in the Middle/Upper Troposphere thus making the on-line upward emission particularly sensible 20 to the atmospheric thermodynamic profile and water vapor content of the highest tropospheric levels. Micro-window radiance is highly sensitive to water vapour mixing ratio (Maestri et al. (2014)) and also affected by the water vapour continuum absorption, that is usually modelled through observations (Mlawer et al. (2012), Serio et al. (2000)). Moreover, the condensed phases of water, in form of liquid water and ice clouds, also affect Earth’s radiation budget significantly (Sinha and Harries (1995)) and, in particular, the presence of ice clouds causes lower emitting temperatures and, hence, a shift towards longer 25 1 Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-28 Manuscript under review for journal Atmos. Meas. Tech. Discussion started: 12 February 2019 c  Author(s) 2019. CC BY 4.0 License.