Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery

Abstract

Abstract. In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Copolarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6.2 m s −1 ), with a Spearman's correlation coefficient of 0.46. At low wind speeds (0.6 m s −1 ), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of −0.53. To further investigate these relations, regression fits were made both for the intermediate (R 2 fit = 0.21) and low (R 2 fit = 0.26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51×51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above ∼ 40 • , restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future.

Predicting Melt Pond Fraction on Landfast Snow Covered First Year Sea Ice from Winter C-Band SAR Backscatter Utilizing Linear, Polarimetric and Texture Parameters

“…Overall, our correlation values are not as high as those found by Scharien et al [24], which may be the result of their object-based approach versus our polygon-based approach. In comparison to Fors et al [23], we find higher correlations for H, α, ρ and φ at FR, but lower correlations for H, α, ρ and φ at NR. Given that their X-band correlations are for sea ice with existing melt ponds, versus our C-band correlations for snow covered sea ice during winter, discrepancies are not unexpected.…”

“…Scharien et al [22] report on the usefulness of co-polarization and cross-polarization ratios in estimating f p during ponding using RADARSAT-2 quad-pol data; their RMSE values range from 0.05 to 0.43. Using TerraSAR-X, Fors et al [23] also find the co-polarization ratio useful during the ponding stage, at intermediate wind speeds, with an RMSE is 0.4; they also evaluate four polarimetric parameters and find reasonable correlations. To evaluate prediction of f p from winter images, Scharien et al [24,25] use ENVISAT-ASAR and Sentinel-1 co-and cross-polarized backscatter and texture measures thereof.…”

“…Given that the most consistent skill in estimating f p is reported by winter prediction of f p [24], we build on the winter prediction technique in this paper. We maintain the use of texture parameters as in Mäkynen et al [21] and Scharien et al [24] and expand on the analysis by evaluating the contributions of polarimetric parameters as per Fors et al [23], and we assess texture measures of the polarimetric parameters. Furthermore, given the relationship of winter snow thickness and subsequent f p , we attempt an initial inversion of f p to estimate snow thickness.…”

Spring melt pond fraction in the Canadian Arctic Archipelago predicted from RADARSAT-2

“…Gulf of Boothia) are associated with lower f pk values. We should expect a lower f pk over MYI regions compared to FYI regions (Grenfell and Perovich, 2004;, and indeed the overall spatial distribution of RADARSAT-2 f pk is in excellent agreement with the spatial distribution of sea ice stage of development prior to the melt season for all years. Figure 5a shows the time series of RADARSAT-2 f pk variability together with mean April MYI area in the CAA from 2009-2018.…”

“…Specifically, the accumulation of meltwater on the surface of the sea ice lowers the albedo from ∼ 0.8 to between 0.2-0.4 and enhances melt . The topographical constraints over multi-year ice (MYI) imposed by hummocks typically result in MYI exhibiting a lower melt pond fraction (f p ) compared to seasonal first-year ice (FYI) (Grenfell and Perovich, 2004;Polashenski et al, 2012;Landy et al, 2015). With Arctic sea ice transitioning from a MYI-to FYIdominated icescape (Maslanik et el., 2011), the lower f p of MYI will gradually be replaced with the higher f p of FYI, facilitating even more sea ice energy absorption and further enhancing sea ice melt (Perovich and .…”