Ground-based detection of Antarctic clouds: analysis of cycles and comparison with IASI products
Abstract. Over Antarctica, the identification of cloud layers from infrared satellite observations is extremely challenging due to the similarities in temperatures and radiative properties of the clouds and the underlying iced surfaces. Ground-based observations, collected by the Radiation Explorer in the Far InfraRed – Prototype for Applications and Development (REFIR-PAD) spectroradiometer operating at Concordia Station, Dome C, on the Antarctic Plateau are used to obtain scene classifications with the Cloud Identification and Classification (CIC) algorithm. The resulting cloud occurrence time series span the timeframe 2014–2020 showing cycles of 12 months (with maxima in December) and 6 months (with maxima in January and July), providing evidence of the semiannual oscillation of the Southern Hemisphere also in localized cloud occurrence. Similar harmonics are observed in the collocated surface temperature and pressure. Analysis of the cloud radiative effect shows that the far infrared downwelling radiance during the peaks of the semiannual oscillation is about twice as high as during its minima. Ground-based cloud classifications are compared to satellite-derived products of the Infrared Atmospheric Sounding Interferometer (IASI) flying on MetOp A, B, and C. Several IASI L2 cloud products (namely cloud tests, cloudiness summary and cloud phase) collocated with the Concordia Station geolocation are considered. The comparison regards more than 1,200 satellite observations from 2014 to 2020, and is conducted by means of a "one-to-one" correlation analysis and via the analysis of the observed cloud occurrences. The one-to-one analysis (conducted using temporally and spatially collocated measurements from IASI and REFIR-PAD) shows that, up to December 2019, the IASI products Artificial Neural Network (ANN) test and the Advanced Very-High-Resolution Radiometer (AVHRR) heterogeneity test are moderately correlated with ground classifications, while the Numerical Weather Prediction (NWP) test, AVHRR cloud fraction test, and flag cldnes are mostly anticorrelated. However, from December 2019, both the NWP test and the flag cldnes switch to positive correlation values. When the flag cloud phase is used as a scene classifier, a limited correlation is found up to December 2019 but significantly higher values are observed in 2020. Finally, it is shown that the IASI cloud phase classification (ice or mixed/liquid) is well correlated with the ground-based phase classification.