Refinement of the ice absorption spectrum in the visible using radiance profile measurements in Antarctic snow

Abstract

Ice is a highly transparent material in the visible. According to the most widely used database (IA2008; Warren and Brandt, 2008), the ice absorption coefficient reaches values lower than 10−3 m−1 around 400 nm. These values were obtained from a vertical profile of spectral radiance measured in a single snow layer at Dome C in Antarctica. We reproduced this experiment using an optical fiber inserted in the snow to record 56 profiles from which 70 homogeneous layers were identified. Applying the same estimation method on every layer yields 70 ice absorption spectra. They present a significant variability but absorption coefficients are overall larger than IA2008 by 1 order of magnitude at 400–450 nm. We devised another estimation method based on Bayesian inference that treats all the profiles simultaneously. It reduces the statistical variability and confirms the higher absorption, around 2 × 10−2 m−1 near the minimum at 440 nm. We explore potential instrumental artifacts by developing a 3-D radiative transfer model able to explicitly account for the presence of the fiber in the snow. The simulation shows that the radiance profile is indeed perturbed by the fiber intrusion, but the error on the ice absorption estimate is not larger than a factor of 2. This is insufficient to explain the difference between our new estimate and IA2008. The same conclusion applies regarding the plausible contamination by black carbon or dust, concentrations reported in the literature are insufficient. Considering the large number of profiles acquired for this study and other estimates from the Antarctic Muon and Neutrino Detector Array (AMANDA), we nevertheless estimate that ice absorption values around 10−2 m−1 at the minimum are more likely than under 10−3 m−1. A new estimate in the range 400–600 nm is provided for future modeling of snow, cloud, and sea-ice optical properties. Most importantly, we recommend that modeling studies take into account the large uncertainty of the ice absorption coefficient in the visible and that future estimations of the ice absorption coefficient should also thoroughly account for the impact of the measurement method.