Description: This study assesses the response on ice dynamics of Petermann Glacier, a major outlet glacier in northern Greenland, to the 2012 and a possible future calving event. So far Petermann Glacier has been believed to be dynamically stable as another large calving event in 2010 had no significant impact on flow velocity or grounding line retreat. By analyzing a time series of remotely sensed surface velocities, we find an average acceleration of 10% between winter 2011/2012 and winter 2016/2017. This increase in surface velocity is not linear but can be separated into two parts, starting in 2012 and 2016 respectively. By conducting modelling experiments, we show that the first speed-up can be directly connected to the 2012 calving event, while the second speed-up is not captured. However, on recent remote sensing imagery newly developing fractures are clearly visible ~12,km upstream from the terminus, propagating from the eastern fjord wall to the center of the ice tongue, indicating a possible future calving event. By including these fracture zones as a new terminus position in the modelling domain we are able to reproduce the second speed-up, suggesting that surface velocities remain on the 2016/2017 level after the anticipated calving event. This indicates that, from a dynamical point of view, the terminus region has already detached from the main ice tongue.

Description: Recovery Glacier reaches far into the East Antarctic Ice Sheet. Recent projections point out that its dynamic behaviour has a considerable impact on future Antarctic ice loss (Golledge et al. 2017). Subglacial lakes are thought to play a major role in the initiation of the rapid ice flow (Bell et al. 2007). Satellite altimetry observations have even suggested several actively filling and draining subglacial lakes beneath the main trunk (Smith et al. 2009). We present new data of the geometry of this glacier and investigate its basal properties employing radio-echo sounding. Using ice-sheet modelling, we were able to constrain estimates of radar absorption in the ice, but uncertainties remain large. The magnitude of the basal reflection coefficient is thus still poorly known. However, its spatial variability, in conjunction with additional indicators, can be used to infer the presence of subglacial water. We find no clear evidence of water at most of the previously proposed lake sites. Especially locations where altimetry detected active lakes, do not exhibit lake characteristics in RES. We argue that lakes far upstream the main trunk are not triggering enhanced ice flow, which is also supported by modeled subglacial hydrology.

Description: This study focuses on the present-day surface elevation of the Greenland and Antarctic ice sheets. Based on 3 years of CryoSat-2 data acquisition we derived new elevation models (DEMs) as well as elevation change maps and volume change estimates for both ice sheets. Here we present the new DEMs and their corresponding error maps. The accuracy of the derived DEMs for Greenland and Antarctica is similar to those of previous DEMs obtained by satellite-based laser and radar altimeters. Comparisons with ICESat data show that 80% of the CryoSat-2 DEMs have an uncertainty of less than 3 m ± 15 m. The surface elevation change rates between January 2011 and January 2014 are presented for both ice sheets. We compared our results to elevation change rates obtained from ICESat data covering the time period from 2003 to 2009. The comparison reveals that in West Antarctica the volume loss has increased by a factor of 3. It also shows an anomalous thickening in Dronning Maud Land, East Antarctica which represents a known large-scale accumulation event. This anomaly partly compensates for the observed increased volume loss of the Antarctic Peninsula and West Antarctica. For Greenland we find a volume loss increased by a factor of 2.5 compared to the ICESat period with large negative elevation changes concentrated at the west and southeast coasts. The combined volume change of Greenland and Antarctica for the observation period is estimated to be -503 ± 107 km**3/yr. Greenland contributes nearly 75% to the total volume change with -375 ± 24 km**3/yr.

Description: LiDAR scanning of the Yukon Coast and Herschel Island took place during the AIRMETH (AIRborne studies of METHane emissions from Arctic wetlands) campaigns (Kohnert et al., 2014) on 10 July 2012 and on 22 July 2013. Point cloud data were acquired with a RIEGL LMSVQ580 laser scanner instrument on board the Alfred Wegener Institute's POLAR-5 science aircraft. The laser scanner was operated with a 60° scan angle at a flight height of around 200 m above ground in 2012 and 500 m in 2013. This resulted in a scan width from 200 (2012) to 500 m (2013) and a mean point-to-point distance of 0.5–1.0 m. During the flight on July 10, 2012 the weather was cloudy with a cloud base around 200 m.a.s.l. . Air temperature ranged between 10 and 12 °C with wind speed ranging from 15 to 19 km/h from easterly direction (70–90°). The last recorded storm was on June 17. During the scanning on July 22, 2013, the weather was nearly cloudless with air temperature 9 °C. Wind speed was 15 km/h from easterly direction (60–80°). The last storm before the acquisition occurred on July 2. Raw laser data were calibrated, combined with the post-processed GPS trajectory, corrected for altitude, and referenced to the EGM (Earth Gravitational Model) 2008 geoid (Pavlis et al., 2008). The final georeferenced point cloud data accuracy was determined to be better than 0.15 ± 0.1 m. The loss of accuracy varied along the flight track because of the vertical accuracy of the post-processed GPS trajectory. The GPS datawere acquired in 50Hz resolutionwith aNovatel OEM4 receiver on board POLAR-5. The GPS trajectory was post-processed using precise ephemerides and the commercial software package Waypoint 8.5 (PPP [precise point positioning] processing). For the interpolation to the final DEM an inverse distance weighting (IDW) algorithm was applied using all cloud points within a 10 m radius of each point. Finally, the DEMs from the different acquisition years were interpolated toraster grids of 1 m horizontal resolution in NAD83 UTM zone 7 coordinate system. To quantify vertical change that is significant at the 99% confidence interval, we used three times RMS error procedure by Jaw (2001). Vertical accuracies for both datasets were estimated to be 0.15 m, which results in the threshold of 0.64 m for significant vertical elevation change. The accuracy of the datasets was additionally tested at locations characterized by the presence of anthropogenic features that presumably remain stable and are not affected by vertical movements because of artificial embankments underneath them. The differences between both DEM datasets were assessed along profiles and were within the previously-stated 0.15 m uncertainty.