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Knowledge of sea ice lead and floe density is important for ship navigation, understanding ice pack dynamics, and mapping primary productivity. Furthermore, reliable lead and floe discrimination is essential for the calculation of sea ice freeboard and thickness from satellite altimetry. Despite its value for shipping, the Northwest Passage is commonly excluded from Arctic-wide satellite altimetry sea ice observations owing to the challenges of obtaining accurate retrievals in the region. Here, we map the distribution of leads and floes in the Northwest Passage using Landsat 8 satellite optical imagery, and we use these to evaluate the efficacy of near-coincident classifications from CryoSat-2 satellite radar altimetry. We test different pulse peakiness and stack standard deviation thresholds for discriminating returns from CryoSat-2 into leads and floes and assess the agreement with near-coincident Landsat 8 estimates. CryoSat-2 lead and floe densities are, on average, 14% higher and 45% lower than Landsat 8, respectively. We attribute the difference to a range of factors including the coarser spatial sampling of CryoSat-2 which results in mixed surface types within the radar footprint, off-nadir ranging of leads, and the misidentification of sea ice floes as ambiguous surface type. In particular, we find the poorest agreement in October, when the ice pack is fragile after the summer melt season. We use our findings to develop a bias adjustment to bring CryoSat-2 lead and floe density estimates in line with Landsat 8, reducing the root mean square difference between them from 20% to 5% and 47% to 6%, respectively.

CryoSat-2 (CS2) is the first mission equipped with a pulse-limited radar altimeter capable of operating in Synthetic Aperture Radar (SAR) Interferometric (SARIn) mode. Over ice sheets and ice caps, CS2 SARIn data have been used to retrieve surface elevations over an across-track ground “swath.” This work demonstrates that retracking multiple coherent peaks of CS2 SARIn waveforms, in combination with the interferometric phase, enables to obtain more than one valid height estimate from single SARIn waveforms over Arctic sea ice. For some SARIn waveforms, the scattering from sea ice at the satellite nadir is successfully separated from returns originating from off-nadir leads. An average bias of −1.8 cm is found for absolute sea ice elevations when using a 50% threshold retracker. It is shown that including multiple SARIn peaks and the associated phase difference in the processing does not introduce any bias on the average sea ice freeboard heights compared with the estimates from regular SAR processing schemes, while significantly increasing the number of valid sea surface height retrievals (+55%) and the number of freeboard estimates in the coastal domain and in multi-year ice regions (~3 times). This results in an average ~34% reduction of the gridded random freeboard uncertainty, corresponding to a ~20% reduction of the gridded total sea ice thickness uncertainty. The results of this work show that SARIn acquisitions over Arctic sea ice provide improved spatial coverage and denser sampling of sea level and sea ice freeboard compared with the SAR mode, with accuracy being largely driven by the retracking algorithm. [ABSTRACT FROM AUTHOR]

CryoSat-2 (CS2) is the first mission carrying on board an altimeter instrument able to operate in Synthetic Aperture Radar Interferometric (SARIn) mode. CS2 SARIn acquisitions have been exploited for different scientific applications that take advantage of the capability to determine the across-track angle of the first return and, in particular, they have been proved to reduce the uncertainty of sea ice freeboard retrievals. Nonetheless, the analysis of pan-Arctic freeboard obtained by processing CS2 Baseline C L1b products has shown large negative freeboard estimates in correspondence of the beginning of SARIn acquisitions. Throughout this letter, the SARIn waveforms are analyzed to identify the cause of this behavior. An improvement of the CS2 L1b processor is then prototyped and used to obtain a pan-Arctic freeboard data set where the percentage of negative freeboard is successfully minimized. [ABSTRACT FROM AUTHOR]