Description: The study presented here is focused on the assessment of surface elevations derived from CryoSat-2 SARIn level 1b data over the Austfonna ice cap, Svalbard, in 2016. The processing chain that must be applied to the CryoSat-2 waveforms to derive heights is non-trivial, and consists of multiple steps, all requiring subjective choices of methods such as the choice of retracker, geo-relocation, and outlier rejection. Here, we compare six CryoSat-2 level-2 type data sets of surface elevations derived using different SARIn processing chains. These data sets are validated against surface elevation data collected from an airborne laser scanner, during a dedicated CryoSat validation experiment field campaign carried out in April 2016. The flight pattern of the airborne campaign was designed so that elevations were measured in a grid pattern rather than along single lines, as has previously been the standard procedure. The flight grid pattern was chosen to optimize the comparison with the CryoSat-2 SARIn elevation data, the location of which can deviate from nadir by several kilometers due to topography within the satellite footprint. The processing chains behind the six data sets include different outlier/error rejection approaches, and do not produce the same number of data points in our region of interest. To make a consistent analysis, we provide statistics from the validation of both the full data sets from each processing chain, and on only those data that all the six data sets provide a geo-located elevation estimate for. We find that the CryoSat-2 data sets that agree best with the validation data are those derived from dedicated land ice processing schemes. This study may serve as a benchmark for future CryoSat-2 retracker developments, and the evaluation software and data set are made publicly available.

Description: Coastal infrastructure, cultural, and archeological sites are increasingly vulnerable to erosion and flooding along permafrost coasts. Amplified warming of the Arctic, sea level rise, lengthening of the open water period, and a predicted increase in frequency of major storms compound these threats. Mitigation necessitates decision-making tools at an appropriate scale. We present a study of coastal erosion combining it with a flooding risk assessment for the culturally important historic settlement on Herschel Island, a UNESCO World Heritage candidate site. The resulting map may help local stakeholders devise management strategies to cope with rapidly changing environmental conditions. We analyzed shoreline movement using the Digital Shoreline Analysis System (DSAS) after digitizing shorelines from 1952, 1970, and 2011. Using these data, forecasts of shoreline positions were made for 20 and 50 years into the future. Flooding risk was assessed using a cost-distance map based on a high-resolution Light Detection and Ranging (LiDAR) dataset and current Intergovernmental Panel on Climate Change sea level estimates. Widespread erosion characterizes the study area. The rate of shoreline movement for different periods of the study ranges from -5.5 to 2.7 m·a-1 (mean -0.6 m·a-1). Mean coastal retreat decreased from -0.6 m·a-1 to -0.5 m·a-1, for 1952-1970 and 1970-2000, respectively, and increased to -1.3 m·a-1 in the period 2000-2011. Ice-rich coastal sections, and coastal sections most exposed to wave attack exhibited the highest rates of coastal retreat. The geohazard map resulting from shoreline projections and flood risk analysis indicates that most of the area occupied by the historic settlement is at extreme or very high risk of flooding, and some buildings are vulnerable to coastal erosion. The results of this study indicate a greater threat by coastal flooding than erosion. Our assessment may be applied in other locations where limited data are available.

Description: Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the presence of a complex snow stratigraphy.

Description: Time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions and satellite altimetry measurements from CryoSat-2 enable independent mass balance estimates of the Earth’s glaciers and ice sheets. Both approaches vary in terms of their retrieval principles and signal-to-noise characteristics. GRACE/GRACE-FO recovers the gravity disturbance caused by changes in the mass of the entire ice sheet with a spatial resolution of 300 to 400 km. In contrast, CryoSat-2measures travel times of a radar signal reflected close to the ice sheet surface, allowing changes of the surface topography to be determined with about 5 km spatial resolution. Here, we present a method to combine observations from the both sensors, taking into account the different signal and noise characteristics of each satellite observation that are dependent on the spatial wavelength. We include uncertainties introduced by the processing and corrections, such as the choice of the re-tracking algorithm and the snow/ice volume density model for CryoSat-2, or the filtering of correlated errors and the correction for glacial-isostatic adjustment (GIA) for GRACE. We apply our method to the Antarctic ice sheet and the time period 2011–2017, in which GRACE and CryoSat-2 were simultaneously operational, obtaining a total ice mass loss of 178 ± 23 Gt yr−1. We present a map of the rate of mass change with a spatial resolution of 40 km that is evaluable across all spatial scales, and more precise than estimates based on a single satellite mission.