## 3 Methods  
The area of iceberg A68A was measured by delineating its boundary from the Sentinel-1 SAR images. The boundary of iceberg can be automatically delineated from SAR image by using well-known edge filters or object-based iceberg detection methods [15; 18; 32]. However, the automatic detection techniques might produce incorrect result when there is low brightness contrast between the iceberg and the surroundings [15]. In several Sentinel-1 SAR images obtained in summer, iceberg A68A appeared as dark as the surrounding sea ice due to snowfall or ice surface melting (see Figure 4b) and would not be delineated correctly by the automatic detection techniques. For these reasons, the area of iceberg A68A was extracted by carefully digitizing the boundary of the iceberg captured in the Sentinel-1A/B SAR images based on visual inspection. The uncertainty in the iceberg area was calculated as the standard deviation of the area derived from repeatedly digitizing the same image by a single operator [33]. The drift speed and rotation angle of the iceberg were calculated by measuring the locations of the iceberg in consecutive SAR images. We calculated drift speed and rotation angle at the center of the iceberg, and points on the northern and southern edges of the iceberg (P1 and P2 in Figure 1) where there have hardly been any collapses so far. The locations of P3 and P4 have also hardly solved during the observation period. The changes in lengths of P1-P2 and P3-P4 with respect to time were calculated to analyze the stretching of the iceberg. The freeboards of A68A were derived from the CryoSat-2 profiles inside the boundary of the iceberg identified from the Sentinel-1 SAR images acquired on the same dates. The time difference of a few hours between the CryoSat-2 and Sentinel-1 observations was disregarded as the iceberg moves less than 100 meters per hour (see Section 4). To correct for the potential errors in the ellipsoidal surface elevation of A68A as measured by the CryoSat-2, we applied the freeboard measurements method described in [25]. For this, the ellipsoidal iceberg surface elevation was converted to the freeboard value using EIGEN-6C4 Geoid, in which changes in sea surface height by non-tidal and tidal effects are corrected using the DTU12 MDT and CATS2008a models, respectively. The freeboard of the iceberg A68A was derived from CryoSat-2 observations assuming that the iceberg is in the hydrostatic equilibrium state. The CryoSat-2 freeboard profile on 8 September 2017 was plotted over the Sentinel-1A SAR image acquired on the same date (Figure 2). Other CryoSat-2 profiles acquired on different dates were relocated to the location of A68A on 8 September 2017 based on the drift speed and rotation angle of the iceberg (Figure 2). The freeboard changes were calculated at the intersections of the CryoSat-2 profiles, with a total time span of more than 180 days. We derived the linear fitting of each freeboard profile using the least squares method to define the intersections of different profiles. The mean and standard deviation of freeboard values for each profile located within a radius of 1.5 km from the point of the intersection were used to calculate freeboard change. Averaging the freeboard values within the 1.5 km radius can reduce systematic errors in the CryoSat-2 observations, and the calculated standard deviations can be regarded as a measure of freeboard uncertainty [17]. If the iceberg is in a hydrostatic equilibrium state, the change in ice thickness (\(\Delta Z\)) can be estimated by [34]  
\[\Delta Z=\frac{\rho_{w}}{\rho_{w}-\rho_{i}}\Delta e-\frac{\rho_{w}-\rho_{s}}{ \rho_{w}-\rho_{i}}\Delta\delta \tag{1}\]  
where \(\Delta e\) is the change in freeboard, \(\Delta\delta\) is the change in snow depth and firn densification, \(\rho_{i}\) is the ice density, \(\rho_{w}\) is the sea water density, and \(\rho_{s}\) is the snow/firn density, respectively [25; 34].