Relationship between specular returns in CryoSat-2 data, surface albedo, and Arctic summer minimum ice extent

• Published in: Elementa: Science of the Anthropocene
• Main Authors: Kwok, R., Cunningham, G. F., Armitage, T. W. K.
• Other Authors: Deming, Jody W., Timmermans, Mary-Louise
• Format: Article in Journal/Newspaper
• Language: English
• Published: University of California Press 2018
• Subjects: albedo; Sea ice
• Online Access: http://dx.doi.org/10.1525/elementa.311; http://online.ucpress.edu/elementa/article-pdf/doi/10.1525/elementa.311/471875/311-5406-1-pb.pdf

Specular (mirror-like) reflections in radar altimeter returns are sensitive indicators of flat open water in leads and melt ponds within the Arctic sea ice cover. Here we find increased specular and near-specular returns in CryoSat-2 waveforms as the sea ice cover transitions from a high albedo snow-covered surface to a lower albedo surface dominated by ponds from snow melt. During early melt, mid-May to late June, increases in fractional coverage of specular returns (FSR) show spatial correspondence with concurrent decreases in albedo. To examine the utility of FSR, we compared its efficacy with that of satellite-derived albedo in forecasting summer minimum ice extent (SMIE). Regression analysis of the area-averaged FSR (F—SR) (2011–2017) shows that ~72% of SMIE variance can be explained by the dates when F—SR climbs to 0.5 within two latitudinal bands covering 70–80°N and 80–90°N. The lag between the two crossing dates provides a measure of the relative rate of the poleward progression of melt. Approximately 93% of SMIE variance can be explained by the date when albedo drops to 0.6 in these same latitudinal bands. Standard errors for these regressions are 0.37 and 0.19 × 106 km2, respectively. Calculating the regression coefficients using only 2011–2016, the 2017 SMIE was forecast with residuals of 0.06 (2% of the total extent) and –0.17 × 106 km2 (4%). Using only 2011–2015 yielded residuals that are less than 0.5 × 106 km2 (~10%) in forecasts of both 2016 and 2017 SMIE, demonstrating the robustness of the regression models. Even though large-scale changes in albedo during summer melt is a characteristic feature of the ice surface, available albedo fields have not been directly used in SMIE forecasts. While this CryoSat-2 record is short, these results suggest that both FSR and albedo could be potentially useful for enhancing forecasts of SMIE.