Linking scales of sea ice surface topography: evaluation of ICESat-2 measurements with coincident helicopter laser scanning during MOSAiC

Abstract

Abstract. Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship navigation through the ice pack. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), part of the National Aeronautics and Space Administration (NASA) Earth Observing System, has been on orbit for over 4 years, sensing the sea ice surface topography with six laser beams capable of capturing individual features such as pressure ridges. To assess the capabilities and uncertainties of ICESat-2 products, coincident high-resolution measurements of sea ice surface topography are required. During the yearlong Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Arctic Ocean, we successfully carried out a coincident underflight of ICESat-2 with a helicopter-based airborne laser scanner (ALS), achieving an overlap of more than 100 km. Despite the comparably short data set, the high-resolution centimeter-scale measurements of the ALS can be used to evaluate the performance of ICESat-2 products. Our goal is to investigate how the sea ice surface roughness and topography are represented in different ICESat-2 products as well as how sensitive ICESat-2 products are to leads and small cracks in the ice cover. Here, we compare the ALS measurements with ICESat-2's primary sea ice height product, ATL07, and the high-fidelity surface elevation product developed by the University of Maryland (UMD). By applying a ridge-detection algorithm, we find that 16 % (4 %) of the number of obstacles in the ALS data set are found using the strong (weak) center beam in ATL07. Significantly higher detection rates of 42 % (30 %) are achieved when using the UMD product. While only one lead is indicated in ATL07 for the underflight, the ALS reveals many small, narrow, and only partly open cracks that appear to be overlooked by ATL07.

Arctic Freeboard and Snow Depth From Near‐Coincident CryoSat‐2 and ICESat‐2 (CRYO2ICE) Observations: A First Examination of Winter Sea Ice During 2020–2022

“…Furthermore, there are uncertainties related to the laser freeboards derived from IS2. As examples, including dark and/or specular leads in the surface classification changes the basin‐scale mean laser freeboard by 0.00–0.04 m (Kwok et al., 2021) and IS2 misses a portion of ridges and rougher topography over sea ice which is otherwise captured by airborne laser scanners (Ricker et al., 2023). Thus, there is a chance that systematic uncertainty in IS2 freeboard also causes the winter C2I rates of snow accumulation to be underestimated.…”

“…ATL07 recently refined the surface finding procedure (the identification of leads for sea surface height segments), where surface classifications such as dark leads have been removed (keeping only specular returns as leads) which has improved the performance (Kwok et al., 2021). A recent study (Ricker et al., 2023) suggested that weak beams, with ∼1/4 of the photon rate compared to strong beams, can provide useful information along the track and should be considered even if this is not what the operational monthly freeboard product (ATL20) currently does (Kwok et al., 2022). Based on these findings and due to the limited coverage of C2I observations, we shall include all six beams when binning the data to comparable resolutions (see Section 2.5).…”

“…When considering systematic biases of IS2, its worthy to consider the impact on precision there is from including all six beams in the binning of IS2 observations. While studies have investigated the overall precision of IS2's weak and strong beams in the Arctic (Ricker et al, 2023) along with inter-beam discrepancies (Bagnardi et al, 2021), it is not clear exactly what the impact is on derived freeboards over sea ice. The weak beams are ∼1/ 4th of the strong beams, and thus we expect lower precision and longer segment-lengths of ATL10 when using weak beams (Bagnardi et al, 2021 also noted that preliminary studies of the IS2 Project Science Office have identified range biases across the beams of centimetre-levels), as the study by Bagnardi et al (2021) identified an overall a small inter-beam bias on sea surface height anomalies over the Arctic Ocean between the strong beams of beam-pair 1 (GT1R) and beam-pair 3 or 5 (GT3R/GT5R) of ∼3 cm.…”

Arctic Sea Ice Topography Information From RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) Backscatter

“…The instrument uses a 532 nm (green) laser that measures returns from the snow surface. Comparisons with airborne Lidar (Duncan & Farrell, 2022) and airborne‐laser scanner (Ricker et al., 2023) data show that data processed using the UMD‐RDA detects ridges, sails and other obstacles at higher precision than ICESat‐2's standard ATL07 height product, and is therefore more appropriate for determining roughness. This analysis also showed that ATL07 tends to overestimate the roughness of smooth ice and underestimate the roughness of rougher ice.…”

Digital elevation models of the sea-ice surface from airborne laser scanning during MOSAiC

“…In general, the ALS distributions are expected to be broader given the higher spatial resolution of the freeboard data (0.5 m compared to about 15–30 m for ICESat-2 ATL10 segments) as shown by a direct comparison in Ricker et al . 36 because the ALS data resolve more ridges. This broadening is visible as the moderate difference in the standard deviation between ALS and ICESat-2 for the PPP flights.…”