Considering the relatively low calving frequencies measured in August of each year (Liu et al., 2013) and the time limitations of available satellite images, we define the annual calving recurrence interval as running from August of the current year to August of the following year. We know that it is difficult to create such a circum-Antarctic iceberg calving dataset based on a single satellite platform. To continuously monitor Antarctic iceberg calving for 2005 to 2020, multisource remotely sensed data are used in this study. We prioritize using SAR (synthetic aperture radar) images for early August each year given that their quality is minimally affected by polar nights and cloudy days. For periods and areas for which SAR data are not available, optical images for close dates are used instead. Satellite images used in the development of this product include Wide Swath Mode (WSM) images from Envisat ASAR for 2005 to 2011 (downloaded from http://eogrid.esrin.esa.int/browse, last access: 11 September 2021); MODIS (Moderate-resolution Imaging Spectroradiometer) 250 m Calibrated Radiances product images (MODIS Characterization Support Team, 2017) for 2012 to 2014 (downloaded from https://worldview.earthdata.nasa.gov/, last access: 11 September 2021); the synthetic images of Landsat 8 OLI (Operational Land Imager) for bands 4 (630–680 nm), 3 (525–600 nm), and 2 (450–515 nm) for 2013 to 2020 (downloaded from https://www.usgs.gov/, last access: 11 September 2021); and the Extra Wide Swath (EW) mode images of Sentinel-1 SAR for 2015 to 2020 (downloaded from https://www.esa.int/ESA, last access: 11 September 2021). Detailed descriptions of these data are given in Table 1.

Additional remote sensing data were also used to facilitate product development and analyses. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2 (where InSAR stands for interferometric synthetic aperture radar Rignot et al., 2011; Mouginot et al., 2012), is used to simulate the expansion of the ice shelf frontal edge and locate calved areas. MEaSUREs Phase-Based Antarctica Ice Velocity Map, Version 1 (Mouginot et al., 2019), and MEaSUREs Annual Antarctic Ice Velocity Maps 2005–2017, Version 1 (Mouginot et al., 2017a), are used for calving mass calculation for marine-terminated glaciers. MEaSUREs Antarctic Boundaries, Version 2 (Rignot et al., 2013), is used for the ice shelf delineation and spatial analysis of the calving distribution. Two ice thickness datasets, Bedmap2 and BedMachine (Morlighem et al., 2020; Fretwell et al., 2013), are used for calving thickness extraction and calving mass calculation for both calving from ice shelves and marine-terminated glaciers. The Reference Elevation Model of Antarctica (REMA; Howat et al., 2019) is used for the uncertainty evaluation of the extracted thickness. The Antarctic daily surface melt dataset (Picard and Fily, 2006) is used to analyze the response of iceberg calving to ice sheet surface melting.

Detailed descriptions of each remote sensing product used are presented in Table 2.

An annual calving event occurs when an independent calved area has an outline that does not overlap or is spatially adjacent to other calving events occurring in the same year (even if it occurs on the same ice shelf), namely the topology requires nonoverlapping and nonadjacent annual calved-area polygons for the specific year. Data generation involves the following three steps: preprocessing the data, extracting iceberg calving, and acquiring attributes (Fig. 1). Each of these steps is discussed in the following sections. Moreover, the consistency of multisource satellite imagery used in monitoring annual iceberg calving has been validated.

Data preprocessing involves geocoding, geometric correction, and mosaic generation. SAR images for the first 3 d of each month of August are used preferentially to generate the circum-Antarctic coastline mosaic for the periods of 2005–2011 and 2015–2020. For 2012–2014, data vacancies were filled with images of the same sensors from close dates. For the mosaic for 2012, we used MODIS images for September combined with SAR images for April to facilitate detection. For 2013 and 2014, which are without SAR images, we chose both MODIS and Landsat 8 OLI circum-Antarctic coastline mosaics to extract iceberg calving. To reduce errors due to different imaging times, we overlaid the satellite image strictly by time order, namely images taken on a date closer to 1 August should be on the upper layer. The preprocessing results of the remotely sensed data are shown in Fig. 2 and provide good coverage of the Antarctic coastline and the frontal edges of ice shelves.

To create the annual iceberg calving dataset for the Antarctic ice shelves, we simulated the expansion of the ice shelf frontal edge and detected the calved areas based on satellite images. It is worth mentioning again that our iceberg calving extraction only included calving from ice shelves but did not include marine-terminating glaciers, and the boundaries of ice shelves are referenced from MEaSUREs Antarctic Boundaries, Version 2, released by NSIDC. We first manually digitalized the ice shelf frontal line in August 2005, 2010, and 2015 as the input benchmark coastline. The following steps were then iterated for the extraction of each annual calving cycle with the methodology divided into two overarching tasks: velocity-based ice shelf front edge simulation and semiautomatic annual iceberg calving extraction (Qi et al., 2020).

For individual calving events, attributes include the area, calving scale, average thickness, mass, calving recurrence interval, and uncertainties of relevant parameters. Therefore, the acquisition of calved area and calved mass, uncertainties, and recurrence intervals are discussed in the following sections.

As mentioned above, a single satellite platform cannot accommodate long-time-series observations of circum-Antarctic calving events. Thus, multisource remotely sensed data are used in this study. To check whether the results derived from different sensors are similar, especially for the results derived from optical sensors and SAR, we performed the following verification.

For the year for which we have both SAR and optical images, we extracted circum-Antarctic annual iceberg calving using the same method based on different sources of remotely sensed imagery. We chose to repeat the calving extraction for 2016/2017 through Terra/Aqua MODIS imagery and to compare it to the contemporaneous extraction results for our dataset derived from Sentinel-1 SAR imagery. We define area differences as the calving area obtained from MODIS subtracted from that obtained from SAR, and we define the calving perimeter as the calved-area perimeter obtained from SAR. We then analyze the area differences of the same calving events and calculate error-equivalent perimeter widths by dividing the area differences by the calving perimeter.

We extracted a total of 220 calving events from MODIS for 2016/2017 covering a total area of 9064.6 km2. As shown in Table 4, both the total number of calving events and the total calved area are slightly lower than values derived from SAR imagery. The numbers of calving events at different scales extracted from the two sources of satellite images are similar. The frequency error mainly originates from small-scale calving, although it accounts for a small percentage of the total area. The calved area derived from MODIS at all four scales is underestimated compared with that from SAR, which might be a result of lower image quality for cloudy areas.

The area of individual calving events extracted by MODIS is generally smaller. As the calving scale increases, errors caused by different data sources account for a lower percentage of the total calved area (Fig. 4a, b, c). The error-equivalent perimeter widths generally exhibit a normal distribution with a standard deviation of 0.15 km and a mean value of -0.06 km (Fig. 4d). Based on this, the errors introduced by multisource satellite data are acceptable.

We assessed the accuracy of the calved area, the calved-area thickness, and the calved mass attributes using Eqs. () and ()–().

The maximum area measurement uncertainty of a single calving event represented in this dataset was calculated as 30.7 km2 with an annual average calved-area uncertainty value of 14.3 km2 and a standard deviation of 5.1 km2. The calved-area uncertainty is mainly determined by the perimeter of each single calving event. In the case of the same area, a long and narrow calving area has higher uncertainty than a square calving area. Thickness uncertainty is mainly attributed to firn depth correction. For individual calving events, thickness uncertainty ranges from 1.0 to 67.7 m with a mean value of 18.5 m and a standard deviation of 9.1 m. The calved mass uncertainty is mainly determined by thickness uncertainty with a mean value of 29.5 Gt and a standard deviation of 23.6 Gt for 15 years, and its annual percentage fluctuates from 1.9 % to 6.0 % each year.

We identify 1975 annual calving events covering areas larger than 1 km2 occurring in the circum-Antarctic ice shelves from August 2005 to August 2020. The annual average number of calving events, the calved area, and the calved mass are 131.7 times, 3549.1±14.3 km2, and 770.3±29.5 Gt, respectively. The number of calving events, calved area, and calved mass show high levels of year-to-year variability (Table 5), highlighting the need for longer records to determine long-term changes in ice shelves.

The number of calving events seemed to be stable for the period from 2005/2006 to 2015/2016, fluctuating from 69 to 127, but it increased substantially in 2015/2016 and fluctuated from 168 to 225 for the period from 2015/2016 to 2019/2020 (Fig. 5a). The total calved area was anomalously low in 2006/2007 compared with other years. It then increased in the following 3 years – especially in 2008/2009 and 2009/2010, during which two extra-large calving events occurred in the Wilkins Ice Shelf and Mertz Ice Shelf. The total calved area then decreased again in 2010/2011 and fluctuated in 2010/2011–2014/2015. In 2016/2017, the total calved area increased considerably to a maximum of 9262.0 km2 over the 15 years, during which an extra-large disintegration of the Larsen C Ice Shelf occurred. Following this, we find the most dramatic reduction in 2017/2018, with a total calved area of 1386.3 km2 reducing to a minimum during the observation cycle. In 2018/2019, the total calved area rose slightly to a level close to that of 2005/2006–2015/2016; in 2019/2020, mainly contributed by the extra-large calving of Amery Ice Shelf in September 2019, the calved mass reached the third-highest level of the 15-year observation period. For annual calving mass, the maximum value appeared in 2016/2017 at 1832.6 Gt, and the minimum value was recorded at 332.0 Gt in 2010/2011. This fluctuating trend of calved mass is generally consistent with that of the calved area.

We assessed the annual calved area and calved mass of the less than 1 km2 calving from the Antarctic ice shelves and the annual calving mass from the marine-terminating glaciers (Table 6). We indirectly estimated an average calved area of 92.7±27.8 km2 and an average calved mass of 18.4±6.7 Gtyr-1 of the less than 1 km2 calving from the Antarctic ice shelves. We also took the calved mass of the marine-terminating glaciers into consideration by calculating the ice flux along grounding lines, which is about 166.7±15.2 Gtyr-1. Therefore, the annual average calving rate of whole Antarctica is 955.4±51.4 Gtyr-1.

The annual distributions of the number, total calved area, and total calved mass of calving events greater than 1 km2 at different scales are shown in Fig. 5a–c. Over the 15 years, the cumulative numbers of calving events of small-, medium-, large- and extra-large-scale events accounted for 72.6 %, 23.5 %, 3.5 %, and 0.3 %, respectively, and frequencies increased exponentially as the scale decreased. The cumulative calved areas of the four abovementioned different sizes accounted for 9.3 %, 25.3 %, 34.7 %, and 30.6 %, respectively. The distribution of calved mass is similar to that of the calved area.

The number of small-scale calving events accounts for a large percentage of total calving, especially in 2015/2016–2019/2020. The interannual variations in the number of small-scale calving events show obviously moderate variations. However, the area and mass of small-scale calving remain relatively stable and low. As the calving scale increases, interannual variations in frequency become less significant; in contrast, interannual variations in area and mass become increasingly volatile. In some years, the number of calving events increased but calved area and mass remained stable or even decreased because more small-scale calving events made a limited contribution to the total calved mass and area. Thus, further studies must be conducted at different scales.

The recurrence interval of calving provides additional qualitative information about the calving feature (Liu et al., 2015) and determines the suitable observation period for identifying the non-steady-state behavior of an ice shelf. For example, following the previous calving in 1963/1964, the rift-opening calving of the Amery Ice Shelf reoccurred in 2019, detaching along the preexisting rifts that had been there for decades (Li et al., 2020). Observational records spanning many decades would be needed to determine its non-steady-state behavior. In contrast, more frequent disintegration calving events are mainly caused by rapid basal crevasse propagation, which is difficult to observe (Liu et al., 2015). The calving front retreat associated with these frequent calving events can be robustly identified over a short observation period due to the shorter recurrence intervals. In other words, the calving events with shorter recurrence intervals are more sensitive to current climate change.

Figure 6a shows that there is no obvious relationship between the calving recurrence interval and calving scale. Two extra-large-scale (>1000 km2) calving events reoccurred on the Thwaite Glacier during our observed period, indicating its distinct retreat, while four other extra-large-scale events from the Larsen C, Wilkins, Totten, and Amery Ice shelves did not reoccur. Figure 6b shows that 76 % of the total number of calving events reoccurred during the observed period (i.e., their recurrence intervals of calving are less than 8 years), which suggests that the annual calving number is likely to be an indicator of the response of calving to climate change. Nearly half of the calved area was contributed by calving events with recurrence intervals longer than 8 years (i.e., calving only occurred once during the observed period), which suggests that the annual calved area is not suitable for identifying the non-steady-state behavior of some temporarily inactive ice shelves with a longer calving interval.

Figure 7 shows the spatial distribution of annual calving events at different scales from 2005/2006 to 2019/2020. Small- and medium-scale calving widely appeared in the Antarctic Peninsula, in West Antarctica, and on Wilkes Land in East Antarctica with interannual variations mainly found in Queen Maud Land in East Antarctica from 2011/2012 to 2015/2016. In 2011/2012–2015/2016, small-scale calving events were largely distributed in West Antarctica and sparsely occurred in East Antarctica. Large-scale calving events appeared quite randomly, usually in medium-sized ice shelf regions of the Antarctica Peninsula and West Antarctica. Extra-large-scale calving events only occurred twice in the Antarctica Peninsula, twice in West Antarctica, and twice in East Antarctica.

Figure 8 shows the average calving rates of the different Antarctic ice shelves from August 2005 to August 2020. We find that the calving mass of Antarctica is mainly affected by the iceberg calving of small ice shelves rather than that of larger ice shelves. Of these, the cumulative calving masses of two major ice shelves, the Ronne–Filchner Ice Shelf and the Ross Ice Shelf, are negligible over the 15-year observation cycle. The Amery Ice Shelf and the Larsen C Ice Shelf in the Antarctic Peninsula, the third- and the fourth-largest ice shelves in Antarctica, had a very low calving rate except for the extra-large disintegration events that occurred in September 2019 and July 2017, respectively. Additionally, some large ice shelves in Queen Maud Land show a low calving mass, while there were a few calving events along the entire coastline in some years (Fig. 7).

In contrast, small- and medium-sized ice shelves, widely found along the circum-Antarctic coastline, exhibit a higher calving rate (Gtyr-1). Among them, the Thwaites Ice Shelf, Pine Island Ice Shelf, and Getz Ice Shelf in West Antarctica show calving rates of 108, 91, and 52 Gtyr-1, respectively. These are followed by the Mertz Ice Shelf and Totten Ice Shelf in East Antarctica with calving rates of 52 and 35 Gtyr-1, respectively. Notably, during the observation period, we detected medium or large calving events from Totten Ice Shelf every year. It is different from calving from the Mertz Ice Shelf that was mainly contributed by an extra-large disintegration event covering more than 2500 km2 which occurred in February 2010.