Fluctuations in Antarctic Ice Sheet elevation and mass occur over a variety of time scales, owing to changes in snowfall and ice flow. Here we disentangle these signals by combining 25 years of ...satellite radar altimeter observations and a regional climate model. From these measurements, patterns of change that are strongly associated with glaciological events emerge. While the majority of the ice sheet has remained stable, 24% of West Antarctica is now in a state of dynamical imbalance. Thinning of the Pine Island and Thwaites glacier basins reaches 122 m in places, and their rates of ice loss are now five times greater than at the start of our survey. By partitioning elevation changes into areas of snow and ice variability, we estimate that East and West Antarctica have contributed −1.1 ± 0.4 and +5.7 ± 0.8 mm to global sea level between 1992 and 2017.
Plain Language Summary
Climate change can trigger long‐term loss in ice sheet mass, which in turn drives global sea level rise. To isolate this signal, short‐term fluctuations in snowfall have to be accounted for in measurements of ice sheet elevation change. In this study, we do this by combining satellite altimetry and a regional climate model. This allows us to show that the extent of ice sheet dynamical imbalance has grown over the past 25 years to incorporate 24% of the West Antarctic Ice Sheet. The thinning of Antarctic glaciers reaches 122 m in places, and their combined ice losses have increased by a factor of 5. Altogether, Antarctica has contributed 4.6 ± 1.2 mm to global sea level rise.
Key Points
We combine satellite radar altimetry and a regional climate model to separate changes in Antarctic elevation into snow and ice contributions
Between 1992 and 2017, ice thinning has grown in extent to include 24% of West Antarctica and reaches 122 m in places
Ice losses from Pine Island and Thwaites Glaciers have risen fivefold; East and West Antarctica have contributed 4.6 ± 1.2 mm to sea level
This article investigates and demonstrates the suitability of the Sentinel-1 interferometric coherence for land cover and vegetation mapping. In addition, this study analyzes the performance of this ...feature along with polarization and intensity products according to different classification strategies and algorithms. Seven different classification workflows were evaluated, covering pixel- and object-based analyses, unsupervised and supervised classification, different machine-learning classifiers, and the various effects of distinct input features in the SAR domain-interferometric coherence, backscattered intensities, and polarization. All classifications followed the Corine land cover nomenclature. Three different study areas in Europe were selected during 2015 and 2016 campaigns to maximize diversity of land cover. Overall accuracies (OA), ranging from 70% to 90%, were achieved depending on the study area and methodology, considering between 9 and 15 classes. The best results were achieved in the rather flat area of Doñana wetlands National Park in Spain (OA 90%), but even the challenging alpine terrain around the city of Merano in northern Italy (OA 77%) obtained promising results. The overall potential of Sentinel-1 interferometric coherence for land cover mapping was evaluated as very good. In all cases, coherence-based results provided higher accuracies than intensity-based strategies, considering 12 days of temporal sampling of the Sentinel-1 A stack. Both coherence and intensity prove to be complementary observables, increasing the overall accuracies in a combined strategy. The accuracy is expected to increase when Sentinel-1 A/B stacks, i.e., six-day sampling, are considered.
The Greenland Ice Sheet has been a major contributor to global sea-level rise in recent decades
, and it is expected to continue to be so
. Although increases in glacier flow
and surface melting
have ...been driven by oceanic
and atmospheric
warming, the magnitude and trajectory of the ice sheet's mass imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet's volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. The ice sheet was close to a state of balance in the 1990s, but annual losses have risen since then, peaking at 345 ± 66 billion tonnes per year in 2011. In all, Greenland lost 3,902 ± 342 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.8 ± 0.9 millimetres. Using three regional climate models, we show that the reduced surface mass balance has driven 1,964 ± 565 billion tonnes (50.3 per cent) of the ice loss owing to increased meltwater runoff. The remaining 1,938 ± 541 billion tonnes (49.7 per cent) of ice loss was due to increased glacier dynamical imbalance, which rose from 46 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. The total rate of ice loss slowed to 222 ± 30 billion tonnes per year between 2013 and 2017, on average, as atmospheric circulation favoured cooler conditions
and ocean temperatures fell at the terminus of Jakobshavn Isbræ
. Cumulative ice losses from Greenland as a whole have been close to the rates predicted by the Intergovernmental Panel on Climate Change for their high-end climate warming scenario
, which forecast an additional 70 to 130 millimetres of global sea-level rise by 2100 compared with their central estimate.
The potential use of the interferometric coherence measured with Sentinel-1 satellites as input feature for crop classification is explored in this study. A one-year time-series of Sentinel-1 images ...acquired over an agricultural area in Spain, in which 17 crop species are present, is exploited for this purpose. Different options regarding temporal baselines, polarization, and combination with radiometric data (backscattering coefficient) are analyzed. Results show that both radiometric and interferometric features provide notable classification accuracy when used individually (overall accuracy lies between 70% and 80%). It is found that the shortest temporal baseline coherences (6 days) and the use of all available intensity images perform best, hence proving the advantage of the 6-day revisit time provided by the Sentinel-1 constellation with respect to longer revisit times. It is also shown that dual-pol data always provide better classification results than single-pol ones. More importantly, when both coherence and backscattering coefficient are jointly used, a significant increase in accuracy is obtained (greater than 7% in overall accuracies). Individual accuracies of all crop types are increased, and an overall accuracy above 86% is reached. This proves that both features provide complementary information, and that the combination of interferometric and radiometric radar data constitutes a solid information source for this application.
In this study, the use of Sentinel-1 interferometric coherence data as a tool for crop monitoring has been explored. For this purpose, time series of images acquired by Sentinel-1 and 2 spanning 2017 ...have been analysed. The study site is an agricultural area in Sevilla, Spain, where 16 different crop species were cultivated during that year. The time series of 6-day repeat-pass coherence measured at each polarimetric channel (VV and VH), as well as their difference, have been compared to the NDVI and to the backscattering ratio (VH/VV) and other indices based on backscatter. The contribution of different decorrelation sources and the effect of the bias from the space-averaged sample coherence magnitude estimation have been evaluated. Likewise, the usage of 12 days as temporal baseline was tested. The study has been carried for three different orbits, characterised by different incidence angles and acquisition times. All results support using coherence as a measure for monitoring the crop growing season, as it shows good correlations with the NDVI (R2>0.7), and its temporal evolution fits well the main phenological stages of the crops. Although each crop shows its own evolution, the performance of coherence as a vegetation index is high for most of them. VV is generally more correlated with the NDVI than VH. For crop types characterised by low plant density, this difference decreases, with VH even showing higher correlation values in some cases. For a few crop types, such as rice, the backscattering ratio outperforms the coherence in following the growth stages of the plants. Since both coherence and backscattering are directly computed from the radar images, they could be used as complementary sources of information for this purpose. Notably, the measured coherence performs well without the need of compensating the thermal noise decorrelation or the bias due to the finite equivalent number of looks.
•Sentinel-1 repeat-pass coherence is effective as a vegetation index for crops.•Time series of coherence are well correlated to NDVI series for most crops.•Both channels (VV and VH) show sensitivity to crop development.•Results are better for steep incidence angles and morning acquisitions.•Measured coherence can be exploited without any complicate post-processing.
Antarctic ice shelves moderate the contribution of the Antarctic Ice Sheet to global sea level rise; however, ice shelf health remains poorly constrained. Here, we present the annual mass budget of ...all Antarctic ice shelves from 1997 to 2021. Out of 162 ice shelves, 71 lost mass, 29 gained mass, and 62 did not change mass significantly. Of the shelves that lost mass, 68 had statistically significant negative mass trends, 48 lost more than 30% of their initial mass, and basal melting was the dominant contributor to that mass loss at a majority (68%). At many ice shelves, mass losses due to basal melting or iceberg calving were significantly positively correlated with grounding line discharge anomalies; however, the strength and form of this relationship varied substantially between ice shelves. Our results illustrate the utility of partitioning high-resolution ice shelf mass balance observations into its components to quantify the contributors to ice shelf mass change and the response of grounded ice.
Many Antarctic ice shelves are losing mass due to thinning and retreat, resulting in accelerated ice flow towards the ocean.
In this study the potential of ERS-1/2 Tandem InSAR data for land-cover classification was investigated at a 2500 km/sup 2/ study area around the Helsinki metropolitan area in Southern Finland. A ...time-series of 14 ERS-1/2 SAR Tandem image pairs was processed into 28 five-look intensity images, 14 Tandem coherence images and two coherence images with a longer temporal baseline (36 and 246 days). All image data was coregistered and orthorectified into map coordinates using an InSAR DEM. A two-stage hybrid classifier method was employed, where the water-class was classified separately in the first classifier stage, and the remaining classes were classified with an ISODATA classifier. Temporal averaging and Principal Components Transformation (PCT) were used to reduce the number of images fed into ISODATA. Classification accuracy was assessed using high-resolution aerial orthophotos, digital base maps and the Finnish National Forest Inventory (NFI). The overall accuracy for six classes (Field/Open Land, Dense Forest, Sparse Forest, Mixed Urban, Dense Urban, Water) was found to be 90% with kappa coefficient of 0.86. Interferometric coherence carries more land-cover related information than the backscattered intensity. This study confirms that the ERS-1/2 Tandem archives could be exploited for land-cover classification.
Continuity of the European Remote Sensing Satellite Synthetic Aperture Radar (ERS SAR) archive by means of Envisat Advanced SAR (ASAR) data acquired from March 2002 has introduced the problem of the ...coherent combination of images coming from sensors with slightly different frequencies. The spectral shift principle states that in case of extended distributed targets, the frequency shift is equivalent to a change of looking angle. In this paper, the same principle is exploited to analyze the behavior of permanent scatterers (PSs) with an extension that is smaller than the ground resolution cell. The conditions under which the PSs identified by ERS can be continued by Envisat are then theoretically determined and experimentally validated. Moreover, this analysis shows that acquisitions characterized by different frequencies can be used to identify the slant-range position of scatterers with high subcell accuracy (tens of centimeters). From the processing side, a very precise images coregistration step is required to get the results described in this paper
The backscattered power recorded by a spaceborne scatterometer operating at C-band is sensitive to land surface parameters and is operationally used by some global remote sensing services, e.g., to ...estimate soil moisture. The estimation of forest variables, in particular above-ground biomass (AGB), from scatterometer data instead was seldom explored. Given the availability of multi-decadal sets of scatterometer observations from space, it is of interest to address the contribution of C-band scatterometer data to the quantification of carbon stocks stored in forests even if the spatial resolution of spaceborne scatterometers is very coarse. In this paper, we investigated the prospects of AGB estimation using backscatter observations by the MetOp Advanced SCATterometer (ASCAT) with a spatial resolution of 0.25°. For this study, ASCAT observations acquired in 2010 were used to be contemporary with AGB datasets selected to benchmark the performance of the estimation. A Water Cloud Model that integrates two allometric equations derived from spaceborne LiDAR data reproduced the relationship between observations of radar backscatter as a function of AGB. Estimates of AGB from individual observations were then combined with a weighted average to reduce uncertainties. Finally, a correction was introduced to compensate for the offset introduced by sloped terrain and surfaces not covered by woody vegetation on the AGB estimate of a pixel. Uncertainties associated with the scatterometer observations, and the modelling framework were propagated to obtain per-pixel values of the standard deviation of an AGB estimate. The proposed method explains much of the variance in AGB estimates when compared to measurements from inventory data (R2 = 0.72) and generated unbiased estimates globally (bias: −3.3 Mg⋅ha−1). Nonetheless, the discrepancy between estimated and plot-based AGB values tended to increase for decreasing biomass level from 20% to 60% of the reference AGB level. A further assessment related to global stocks indicated that the value estimated from the scatterometer dataset (596 Pg, 95% of which 563 Pg stored in forest land) was in line with two published estimates based on forest inventory data only (571 Pg and 600 Pg, respectively). Despite the coarse spatial resolution, our results indicate that C-band scatterometer observations from space can contribute to the characterization of terrestrial biomass pools. The record of observations starting in the early 1990s may provide an unprecedented way to look at long-term forest dynamics as well as to constrain the strength of carbon-climate cycle feedback simulated by Earth System models.
•First global estimation of biomass from C-band satellite scatterometer data.•Integration of radar backscatter and allometric models.•Globally unbiased estimates of above-ground biomass at 0.25°.•Strong potential to quantify the terrestrial carbon stocks.
The shape of the large ice sheets responds rapidly to climate change, making the elevation changes of these ice-covered regions an essential climate variable. Consistent, long time series of these ...elevation changes are of great scientific value. Here, we present a newly-developed data product of 25 years of elevation changes of the Greenland Ice Sheet, derived from satellite radar altimetry. The data product is made publicly available within the Greenland Ice Sheets project as part of the ESA Climate Change Initiative programme.
Analyzing repeated elevation measurements from radar altimetry is widely used for monitoring changes of ice-covered regions. The Greenland Ice Sheet has been mapped by conventional radar altimetry since the launch of ERS-1 in 1991, which was followed by ERS-2, Envisat and currently CryoSat-2. The recently launched Sentinel-3A will provide a continuation of the radar altimetry time series. Since 2010, CryoSat-2 has for the first time measured the changes in the coastal regions of the ice sheet with radar altimetry, with its novel SAR Interferometric (SARIn) mode, which provides improved measurement over regions with steep slopes.
Here, we apply a mission-specific combination of cross-over, along-track and plane-fit elevation change algorithms to radar data from the ERS-1, ERS-2, Envisat and CryoSat-2 radar missions, resulting in 25 years of nearly continuous elevation change estimates (1992–2016) of the Greenland Ice Sheet. This analysis has been made possible through the recent reprocessing in the REAPER project, of data from the ERS-1 and ERS-2 radar missions, making them consistent with Envisat data. The 25 years of elevation changes are evaluated as 5-year running means, shifted almost continuously by one year. A clear acceleration in thinning is evident in the 5-year maps of elevation following 2003, while only small elevation changes observed in the maps from the 1990s.
•25-year time series of Greenland ice sheet elevation changes is presented.•Combination of methods for generation of the consistent multi-mission time series.•Evidence for the change in the state of the Greenland Ice Sheet since the early 1990s.
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