Estimation of cloudiness in different areas of Antarctica from broadband radiation measurements

The importance and impact of clouds on the surface radiation balance has been much discussed in recent research. Estimation of cloudiness mostly relied on human observers for many years, before measurements from satellites, sky cameras, ceilometers and lidars became available. Yet, despite these tools, evaluation in polar regions still remains difficult because of a relative lack of measurements. Throughout the years several methods to evaluate cloudiness from surface broadband radiation measurements, both shortwave and longwave, have been developed. They are able to provide information on cloudiness where direct observations are lacking. Furthermore, combining all-sky broadband radiation measurements and clear sky estimates, the cloud radiative effect on the surface radiation budget can be estimated. In this work we present the challenges of the implementation of such methods for Antarctica using measurements from seven stations representing different geographic areas of the continent. Marambio (641450S - 563739W, 196 asl) and Professor Julio Escudero (621257S - 585735W, 10 asl) stations are located in the Antarctic Peninsula; Concordia (750559S 1231957E, 3233 asl) and Amundsen-Scott South Pole (90S 0E, 2835 asl) stations in the Antarctic Plateau; Shwa (60 0 25.1S - 39 35 1.5E, 29 asl), Neumayer III (704100S - 081600W, 43 asl) and Jang Bogo station (743738S - 1641416E, 36.6 asl) are in the East Antarctica coastal sector. Four belong to the Baseline Surface Radiation Network1, and therefore collect high quality measurements for all radiation components following specific quality standards. We will illustrate how to apply different methods for deriving cloudiness parameters radiometrically using these data sets. To maximize the information that can be obtained at the different sites, the evaluated methods are: Kasten and Czeplak2, Long3, BrightSun4, RADFLUX5, APCADA6, Van den Broeke7, and Solomon8. The last four are based on (or include) longwave and meteorological data and are particularly useful in Antarctica for their potential to provide data during the polar night and at unstaffed locations.Bibliography1 Driemel et al. (2018): Baseline Surface Radiation Network (BSRN): structure and data description (19922017). doi: 10.5194/essd-10-1491-20182 Kasten and Czeplak (1980): Solar and terrestrial radiation dependent on the amount and type of cloud. doi: 10.1016/0038-092X(80)90391-63 Long et al. (2006): Estimation of fractional sky cover from broadband shortwave radiometer measurements. doi.org: 10.1029/2005JD0064754 Bright et al. (2020): Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model. doi: 10.1016/j.rser.2020.1097065 Riihimaki et al. (2019): Radiative Flux Analysis (RADFLUXANAL) Value-Added Product ... . doi: 10.2172/15694776 Drr and Philipona (2004): Automatic cloud amount detection by surface longwave downward radiation measurements. doi: 10.1029/2003JD0041827 Van Den Broeke et al. (2004): Surface radiation balance in Antarctica as measured with automatic weather stations. doi: 10.1029/2003JD0043948 Solomon et al. (2023): The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign. doi: 10.1525/elementa.2022.00104