The mass balance of the Greenland ice sheet (GrIS) is an important factor in estimating the rate of increase of global sea levels. The complete melting of the GrIS could increase the global sea level by 7 m, and the state of the GrIS is critical to the survival of humanity [1
]. Typically, the mass balance of the GrIS is modelled by combining surface mass balance (SMB) from a climate model and ice flux across ice grounding lines from interferometry and other measurements. Such GrIS SMB models may undergo model uncertainties and the inter-annual mass variations of GrIS [3
]. Currently, the Gravity Recovery and Climate Experiment (GRACE) is the satellite gravimetric mission for GrIS mass balance estimates [5
]. GRACE has become a standard tool for monitoring the mass balance of ice sheets since 2002 [6
]. However, GRACE-based estimations of the mass balance of Greenland typically have spatial resolutions of approximately 300 km and can be further degraded by its systematic errors such as north-south stripes, data noises and errors introduced by the uncertainties of models that represent temporal gravity effects.
Mass balance can also be derived from elevation measurements observed by altimetry missions such as ERS-1, ERS-2, Envisat, ICESat, CryoSat-2 and SARAL. Mass change derived by satellite altimetry characterizes a higher spatial resolution than that observed by GRACE [9
]. However, issues such as snow surface penetration and steep terrain in estimating elevation change from satellite altimetry have been acknowledged since the first altimetry mission. The waveform retracking algorithm is an effective approach that tracks the actual surface to reduce the influence of surface penetration and topography [11
]. Thus, selecting an appropriate waveform retracker is a key factor in estimating elevation change over the GrIS.
Several approaches based on altimetry data have been used in estimating elevation change. For example, the digital elevation model (DEM) time series [10
], crossover locations [15
] and repeat-track (RT) methods [16
] have been used over ice sheets. Every method of estimating the rate of elevation change can be successfully applied to altimetry data. The DEM time series method demonstrates a high efficiency in computation time to derive the rate of elevation change; however, the accuracy of the elevation change rate is insufficient [13
]. The crossover location method exhibits high accuracy; however, the high resolution of this method remains a huge challenge. The RT method is currently considered a favorable method for estimating the rate of elevation change because the rare exactly repeated measurements, which can use all available data to provide an elevation change map with a high resolution, are overcome. Thus, the RT method was used in this study.
The Satellite with ARgos and ALtiKa (SARAL/ALtiKa), which was jointly developed by the French National Space Research Centre and the Indian Space Research Organization, was launched in 2013 as a follow-on mission to the mission of Envisat European Space Agency (ESA). SARAL/ALtiKa is the first mission-carried ALtiKa altimeter with the Ka-band (35.75 GHz). The high frequency of the Ka-band has the strength of a radar signal, but is less affected by snow surface penetration. This capability of the Ka-band is a significant improvement when compared with other radar altimeters for snow surface penetration and enables accurate observations over the GrIS [19
]. Thus, the elevation change from SARAL data might have a better performance over the GrIS. However, the accuracy and performance in estimating the elevation change derived from SARAL are unknown.
This study aimed to evaluate the accuracy of the elevation change from four waveform retracker algorithms. The results in the crossovers of descending and ascending orbits over GrIS were compared. Subsequently, a further comparison with ICEBridge results was also conducted. Furthermore, this study aimed to investigate the elevation change of the GrIS derived from SARAL. The results of elevation change from the Ka-band of SARAL/ALtiKa were compared with results from the Ku-band of CryoSat-2 and Envisat.
In this study, the differences between SARAL and ICEBridge were discussed. Figure 5
a demonstrates the rate differences between the OIB L4 and SARAL data with the ICE1 retracker. Considerable differences were found in the Northeast Greenland Ice Stream. The influence of topography with high surface slope might be an important cause of the differences. Figure 4
exhibits the statistics of the differences between the SARAL and ICEBridge data as a function of surface slope (marked in blue). Figure 4
a shows the bias of the differences between SARAL and ICEBridge with an interval of 0.1°. The bias in absolute values increased with the surface slope increase. Furthermore, Figure 4
b shows that the RMSE of differences also had a higher value with the increase in slope. This result indicates that a high surface slope could result in poor accuracy in the rate differences. Another possible reason for the rate differences might be the influence of distance from the central point of ICEBridge to the measurement point of SARAL. However, no correlation was found between the bias and the point separation. Thus, the influence of the distance threshold could be disregarded.
In this study, we also estimated the mean elevation change rate derived from CryoSat-2 for 2013–2015, according to the method used by Simonsen et al. [23
]. In the same period from 2013–2015, the results of rate from CryoSat-2 data were used as a comparison for our results from SARAL. The rate differences between CryoSat-2 and ICEBridge are presented in Figure 5
b. Over the whole of Greenland, the rate differences between CryoSat-2 and ICEBridge were estimated with a bias of 0.14 m year−1
and RMSE of 0.28 m year−1
. Results showed that the rate differences between SARAL and ICEBridge with a bias of 0.11 m year−1
were slightly better than the bias of 0.14 m year−1
between CryoSat-2 and ICEBridge. The RMSE of rate differences of 0.43 m year−1
between SARAL and ICEBridge was slightly worse than the RMSE of 0.28 m year−1
between CryoSat-2 and ICEBridge. Similar statistics were also observed in the LRM region of Greenland. The rate differences between SARAL and ICEBridge with a bias of 0.10 m year−1
and RMSE of 0.38 m year−1
were used as a comparison for the rate differences between CryoSat-2 and ICEBridge with a bias of 0.15 m year−1
and RMSE of 0.23 m year−1
. The different abilities of snow surface penetration between the Ka-band and Ku-band might be an important reason for the results of different RMSE. The depth of snow surface penetration of the Ka-band is smaller than the Ku-band. The elevation change derived from SARAL was closer to the surface of the ice sheet when compared with the results from CryoSat-2. Meanwhile, SARAL is more subject to weather variability, as Ku-band radars may not see light snowfall events, which are observed by SARAL and ICEBridge. Another possible reason for the results of RMSE is the different orbit densities. The density of CryoSat-2 orbit was much higher than the density of the SARAL orbit. From the result of bias, the Ka-band of SARAL had a better performance than CryoSat-2. This might suggest that the elevation change rate derived from the Ka-band was a closer reflection of the snow surface change rate than the Ku-band.
The distribution of elevation change derived from the SARAL data acquired from March 2013–April 2016 over the GrIS is exhibited in Figure 6
a. The rates of elevation change over the GrIS were estimated from the SARAL data retracked using the ICE1 retracker through the RT method. A clear pattern of thinning (blue) along the margins of Greenland can be observed in Figure 6
a. Only a few variations or nearly no change in the interior of the GrIS is depicted in Figure 6
a. The pattern generally agreed with the findings inferred from Envisat, ICESat and CryoSat-2 [12
]. The strong thinning in Jakobshavn Isbræ on the west coast of Greenland was the most prominent and extended far inland. This phenomenon was observed by CryoSat-2 and ICESat [12
], thereby presenting the recently large elevation loss in the area of the major outlet glaciers. Kangerlussuaq Glacier (Figure 3
and Figure 6
a) is another outlet glacier with large thinning. In the Zacharias Isstrømen (Figure 3
), the outlet glacier of the Northeastern GrIS presents a high rate of elevation loss. The trend of thinning in this region extended to approximately 150 km upstream of the Northeast Greenland Ice Stream. The pattern of pronounced thinning was only observed by the CryoSat-2 data [36
]. This pattern represented the increase in the speed of Zacharias Isstrømen. Thickening was the most evident near Storstrømmen in the Northeastern GrIS. This phenomenon was consistent with an on-going dynamic response to the identified surge and was previously found based on the ICESat and CryoSat-2 data [12
]. Simonsen previously reported that a slight thickening was also found inland of East Greenland (approximately 75°N) [23
]. SARAL showed thinning in the northwestern margins over the GrIS (Figure 6
a), thereby confirming the findings over the GrIS that were previously observed by Khan et al. [37
] and Sørensen et al. [18
The uncertainty of elevation change derived from SARAL was based on the least-square model. This uncertainty can also be inferred in Figure 6
b. Low uncertainties in the interior of Greenland can be observed in Figure 3
, and most values were less than 1 cm year−1
. The high uncertainties were generally observed in the margins over the GrIS. The complicated terrain might be an important reason for the non-perfect relocation and preferential sampling of high points of radar return.
In comparison with previous conventional radar altimeters [12
], using SARAL could reduce the footprint to 1.4 km in radius when compared with the Ku-band footprint radius of 1.7 km. The high frequency of the Ka-band (35.75 Hz) also reduced the impact of snow surface penetration. Meanwhile, the waveform retracking algorithm, which tracks the actual surface, was also an effective approach in reducing the effect of surface penetration and topography [11
]. The results of elevation change from SARAL data were interpolated onto a 10-km grid for the calculation of volume change [28
]. The volume change of Greenland derived from SARAL was also estimated with a volume loss of 40 ± 12 km3
from March 2013–April 2016. In comparison, a volume estimation of Greenland derived from CryoSat-2 with a larger volume loss of 191 km3
was found in the time span from 2012–2016 [23
]. Due to the use of the new measurement mode of SARIn mode, the results of elevation change rate from CryoSat-2 data could provide more values in the fast-changing coastal areas. However, a similar phenomenon of elevation change was found by both SARAL and CryoSat-2. In the northwestern regions of Greenland, large areas of ice sheet thinning were observed by both SARAL and CryoSat-2. Meanwhile, the results from SARAL in this study were compared with the elevation change rate of Greenland derived from Envisat from 2002–2010 [18
]. An acceleration of loss of elevation was detected in the northeastern regions of Greenland. In the Northeast Greenland Ice Stream, the speed-up of loss of surface elevation was also found when compared to the results from Envisat. The acceleration of loss of volume in this area was also observed by CryoSat-2 in the time span from 2012–2016 [23
]. We also emphasized the underestimation of volume loss derived from SARAL by not measuring the fast-changing coastal areas. Through the comparison with satellites carrying the Ku-band, it suggests that SARAL/ALtiKa helped to investigate the current elevation change of the GrIS.
The accuracy of the elevation change results from the four waveform retracker algorithms provided by SARAL data was assessed. The results of rate differences were compared in the crossovers of the descending and ascending orbits over the GrIS from March 2013–April 2016. The ICE1 retracker was a better waveform retracking algorithm given the lowest SD of 0.30 m year−1. The elevation change rate with waveform retracking could significantly improve the accuracy of the elevation change results. The rate differences in the crossovers in the interior of the GrIS were lower than the results in the margins. The slope of the surface topography was considered an important factor for explaining this difference. However, the gap in the margins of GrIS remains unresolved. A possible interpretation is that the radar return onboard SARAL might be disturbed when the satellite moves from the ocean to the steep topography in the coastal areas of Greenland, thereby leading to a few points of the elevation change rate in the coastal area of Greenland.
The elevation change rate derived from SARAL using four waveform retracker algorithms were also validated against the OIB ATM L4 data. The ICE1 retracker determined the lowest rate difference with an RMSE of 0.43 m year−1. However, differences in the elevation change rate between SARAL and OIB ATM L4 data were also found. Several reasons can be used to interpret the rate differences. First, the ICEBridge mission measures only one or two months in Greenland per year. Second, the slope of the surface topography might be another reason. The high slope of surface topography might have large rate differences. The non-perfect relocation and complicated radar returns in the area with high surface slope can be important factors for these differences. Third is the selection of the distance threshold. However, the influence of the distance threshold can be disregarded.
The elevation change rate derived from SARAL was retracked with the ICE1 retracker based on the RT method, which is presented over the GrIS between 2013 and 2016. Simonsen previously reported that a slight thickening was found inland of East Greenland (approximately 75°N) [23
]. In Zacharias Isstrømen, the outlet glacier of the Northeastern GrIS presented a rapid rate of elevation loss. SARAL showed thinning in the northwestern margins over the GrIS, thereby confirming the previously-observed findings over the GrIS [18
].The volume change of Greenland derived from SARAL was also estimated with a volume loss of 40 ± 12 km3
from March 2013–April 2016. A comparison with the elevation change derived from 2012–2016 [23
] CryoSat-2 data was investigated. Large areas of ice sheet thinning were observed by both SARAL and CryoSat-2 in the northwestern regions of Greenland. The acceleration of the loss of surface elevation was also found through the comparison with the results from 2002–2010 [18
] Envisat data in this area. Through a comparison with satellites carrying the Ku-band, this suggests that SARAL/ALtiKa can help to investigate the current elevation change of the GrIS. Here, the volume loss from the SARAL data did not include the coastal areas of the GrIS, which are known to account for the majority of the GrIS volume loss.
SARAL/ALtiKa with a high frequency Ka-band (35.75 GHz) and reduced footprint radius of 1.4 km can provide further details of the elevation change over the GrIS, thereby providing a reliable performance. The ICE1 retracker demonstrated its optimal performance when the SARAL data were used to determine the elevation change rate over the GrIS. However, some gaps in the regions from ocean to land were found. An advanced waveform retracker might be required to improve the coverage of elevation change rate in the margins of Greenland.