Abstract
Abstract. For large-scale and long-term Arctic climate simulations appropriate parameterization of the surface albedo is required. Therefore, the sea ice surface (SIS) albedo parameterization of the coupled regional climate model HIRHAM–NAOSIM was examined against broadband surface albedo measurements performed during the joint ACLOUD (Arctic CLoud Observations Using airborne measurements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) campaigns, which were performed in May–June 2017 north of Svalbard. The SIS albedo parameterization was tested using measured quantities of the prognostic variables surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes (snow-covered ice, bare ice, and melt ponds) derived from digital camera images taken on board the Polar 5 and 6 aircraft. The selected low-altitude (less than 100 m) flight sections of overall 12 flights were performed over surfaces dominated by snow-covered ice. It was found that the range of parameterized SIS albedo for individual days is smaller than that of the measurements. This was attributed to the biased functional dependence of the SIS albedo parameterization on temperature. Furthermore, a time-variable bias was observed with higher values compared to the modeled SIS albedo (0.88 compared to 0.84 for 29 May 2017) in the beginning of the campaign, and an opposite trend towards the end of the campaign (0.67 versus 0.83 for 25 June 2017). Furthermore, the surface type fraction parameterization was tested against the camera image product, which revealed an agreement within 1 %. An adjustment of the variables, defining the parameterized SIS albedo, and additionally accounting for the cloud cover could reduce the root-mean-squared error from 0.14 to 0.04 for cloud free/broken cloud situations and from 0.06 to 0.05 for overcast conditions.
Highlights
Arctic amplification is significantly driven by the snow–ice albedo feedback
The parameterizations of sea ice albedo and sea ice subtype fraction as used in the sea ice surface (SIS) albedo scheme of the coupled regional climate model HIRHAM–NAOSIM were tested with airborne surface albedo, sea ice fraction, and surface temperature measurements taken during the ACLOUD/PASCAL campaign performed north of Svalbard in May–June 2017
In HIRHAM– NAOSIM, these subtype fractions are calculated from the prognostic variables of surface temperature and snow depth
Summary
Arctic amplification is significantly driven by the snow–ice albedo feedback. The reduction in snow/ice cover results in a decrease in surface albedo, which enhances the solar heating of the surface due to more absorption of solar radiation at the surface, leading to a further decrease in snow and ice cover (Schneider and Dickinson, 1974; Curry et al, 1995). Thackeray et al (2018) calculated the sensitivity of snow-covered surface albedo (α) to surface temperature (Tsurf) in terms of α/ Tsurf based on the CMIP5 model results, and compared the model output with estimates from satellite observations and reanalysis data They found a range of −0.67 % K−1 >. Aircraft and ground-based observations taken during the concurrent ACLOUD (Arctic CLoud Observations Using airborne measurements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) campaigns (Wendisch et al, 2018) are used to validate the SIS albedo scheme of the coupled regional climate model HIRHAM–NAOSIM (Dorn et al, 2018) Both campaigns were performed north of Svalbard during the spring–summer transition in 2017.
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