G3.2

Runoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems. Runoff now accounts for most of Greenland’s contemporary mass imbalance, driving a decline in its net surface mass balance as the regional climate has warmed. Although automatic weather stations provide point measurements of surface mass balance components, and satellite observations have been used to monitor trends in the extent of surface melting, regional climate models have been the principal source of ice sheet wide estimates of runoff. To date however, the potential of satellite altimetry to directly monitor ice sheet surface mass balance has yet to be exploited. Here, we explore the feasibility of measuring ice sheet surface mass balance from space by using CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. In total, the ice sheet lost 3571 ± 182 Gt of ice through runoff over the 10-year survey period, with record-breaking losses of 527 ± 56 Gt/yr first in 2012 and then 496 ± 53 Gt/yr in 2019. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

How to cite: Slater, T., Shepherd, A., McMillan, M., Leeson, A., Gilbert, L., Muir, A., Kuipers Munneke, P., Noël, B., Fettweis, X., van den Broeke, M., and Briggs, K.: Increased variability in Greenland Ice Sheet runoff detected by CryoSat-2 satellite altimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2834, https://doi.org/10.5194/egusphere-egu22-2834, 2022.

Estimates of mass balance across the Greenland Ice Sheet (GrIS) are commonly based on the joint interpretation of satellite radar altimetry measurements and the outputs of climate models. Conventional radar altimetry measurements, such as those produced by ESA’s CryoSat-2 platform, provide an observational constraint on the physical dimensions of the ice sheet (i.e., surface height), while climate models attempt to constrain relevant mass fluxes (i.e., precipitation, run-off, and evaporation/sublimation). However, this approach provides no direct observational insight into the large-scale state and temporal evolution of near-surface density across the ice sheet; a critical quantity through which surface deformation and mass flux estimates are linked to overall mass balance.

To date, the analysis of space-based radar altimetry measurements over the GrIS has been predominantly concerned with determining the range between the satellite and the surface as a means of quantifying changes in ice column thickness. While some studies have investigated the relative shape of the measured return echo, little attention has been paid to its actual recorded strength. Radar Statistical Reconnaissance (RSR), originally developed for use with radar reflections from the surface of Mars, provides a framework for the interpretation of backscattered surface echo powers and the quantitative estimation of near-surface properties. The RSR method relies on using the distribution of a set of observed echo strengths in order to determine their coherent and incoherent components. These decomposed reflection components are then assumed to be related to near-surface density (coherent) and wavelength-scale surface roughness (incoherent) respectively.

In this study, we present the first attempt to apply the RSR methodology to Ku-band (SIRAL; on-board ESA CryoSat-2) and Ka-band (ALtiKa; on-board ISRO/CNES SARAL) radar altimetry measurements acquired over the GrIS. In continual operation since July 2010 and March 2013 respectively, the longevity of these spacecraft along with their dense spatial coverage of the GrIS provides a tantalizing opportunity to produce long-term trends in near-surface density. Surface echo powers are extracted from recorded waveforms contained in CryoSat-2 SARin FBR data products as well as SARAL SGDR data products and organized by month. We focus on waveforms in the CryoSat-2 SARin FBR data products in lieu of those from LRM Level 1B data products in order to increase the spatial density of surface echo power measurements and therefore, the spatial resolution of the RSR results. Estimates of coherent and incoherent power are then produced on a month-by-month basis for a constant set of grid points (5 km by 5 km spacing) across the GrIS. We calibrate the coherent component of the CryoSat-2 and SARAL surface echoes to near-surface density using in situ measurements from the SUMup dataset.

This research into leveraging the radiometric information previously ignored in radar altimetry measurements to determine near-surface densities across the GrIS is a new frontier in Earth Observation. The capability to observationally determine near-surface density across the GrIS represents a fundamental contribution to refining surface mass balance estimates and understanding the evolution of the ice sheet in face of a changing climate.

How to cite: Scanlan, K. M. and Simonsen, S. B.: Inferring Near-Surface Density and Surface Roughness from Satellite-Based Radar Altimetry over Greenland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-241, https://doi.org/10.5194/egusphere-egu22-241, 2022.

Satellite Altimetry has been continuously providing precise sea level for the last 28 years. However, the conventional altimetry is not at its best for the coast because it is hampered by mixed returns of electromagnetic waves due to disturbance from lands and inconsistencies of corrections. Since coastal regions are a vital part of human societies, improving methods to understand the coastal ocean topography, sea level, and its change is essential. In the last seven years alone, there are several specifically-designed coastal retracker that aimed to overcome the disturbance that occurred on the coasts. However, until now, there are only a few extensive studies have compared the accuracy and precision of retrackers and range corrections combination with regards to tide gauges on the coast of Indonesia. A region where the oceanographic condition and land and sea interaction is challenging, mainly due to the existence of shallow seas, narrow straits, and bays.

In this study, we compare sea level heights obtained using six processing schemes mostly dedicated to coastal areas. Three of them are for conventional altimetry (ALES, X-TRACK, and X-TRACK/ALES) and the other for SAR altimetry (STARS, SAMOSA++ in SARvatore and SINCS in TUDaBo). The first covers 20 years and corresponds to the repeat-track phase of Jason-1, Jason-2, and Jason-3. The second covers 10 years and corresponds to the SAR-mode measurements of Cryosat-2, Sentinel-3A/3B, and Sentinel-6. We apply similar state-of-the-art corrections designed for coastal areas.

On the other hand, a set of Indonesian tide gauge stations are being evaluated and selected in terms of their time series and their relationship with the GNSS station near it, identifying the effect of vertical land motion. Those tide gauges are considered as reference and used to assess which combination of retrackers and range corrections provide the sea level height which best agrees with in-situ data.

The results will have implications for understanding the goodness of altimetry processing schemes and of the corrections in the coastal zone, at less than 10 km. Moreover, the result is also will be used to determine precise MDT and in turn, gravity anomaly of Indonesian seas.

How to cite: Nadzir, Z. A., Fenoglio-Marc, L., Uebbing, B., and Kusche, J.: Exploring Coastal Altimetry Datasets for Indonesian Seas in relation to Local Tide Gauges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-538, https://doi.org/10.5194/egusphere-egu22-538, 2022.

Almost ten years ago, the first elevation estimates based on swath processing of interferometric CryoSat-2 altimeter observations were published, mapping the surface of Devon ice cap. The new method holds a great potential to provide dense data coverage, in space and time. Indeed, ESA recently started releasing digital elevation models at a 2 by 2 km resolution for a rolling 3 month data aggregation cycle. Such spatiotemporal resolutions are especially valuable in versatile and dynamic regions as mountain glaciers. In this presentation, we describe systematic errors on the order of 10 m with about yearly periodicity that arise in the proximity of hills and valleys. One error is caused by the superposition of multiple signals, the other is caused by the Fourier-transformation in the SAR beam-forming process. Both are intrinsic to the measuring concept, but their effect can potentially be limited by data filtering strategies. We report the influence of the commonly used coherence and power threshold based filtering on derived elevation change rates. For data users, awareness of these issues is especially important to interpret the observations correctly and to understand that there is a large systematic part in the overall uncertainty.

How to cite: Haacker, J., Wouters, B., and Slobbe, C.: Systematic errors in Cryosat-2 swath elevations and their impacts on glacier mass balance estimates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4946, https://doi.org/10.5194/egusphere-egu22-4946, 2022.

Thirty years of altimetry satellite observations have provided important information that enables research discoveries and aids in the development of user-driven applications. National and international space and operational agencies have committed substantial resources to developing and continuing observations of the ocean and large water bodies (lakes, reservoirs, large rivers) through collaboration in these missions. Over the next few years, NASA and other agencies will launch new research missions with technologies that will extend, expand, and evolve observations of ocean, coastal and inland waters. New discoveries and advances in societally relevant applications can be leveraged with increased spatial, temporal and spectral resolutions. We will highlight the use of data from these existing and planned missions for operational and applied user-driven applications and their societal benefits. Topics may include the use of existing, retrospective, and expected time series that contribute to applications such as marine operations, marine biology and biodiversity, coastal studies, hurricanes and other hazards, as well as hydrologic assessments, water resources management, and other surface water applications.

How to cite: Srinivasan, M., Tsontos, V., and Hossain, F.: Applications of Satellite Altimetry Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13067, https://doi.org/10.5194/egusphere-egu22-13067, 2022.

Sea level variations from satellite altimetry need to be consistently calibrated and monitored when used for climate studies. Here, we focus on the estimation of biases and the monitoring of precision and drifts of three SAR-altimeter missions (Sentinel-3A, Sentinel-3B and Sentinel-6MF) at eleven tide gauge stations in the German Bight (Southeastern North Sea). The corresponding operational GNSS-controlled tide gauge stations are partly located in open water, partly at the coast close to mudflats and deliver data every minute in the period 2016 to 2021. Instantaneous sea level (total water envelope) from altimetry is extracted at virtual stations in close vicinity to the gauges (2 to 24 km) and for different retrackers. The processing is optimized for the region and empirically adjusted for the comparison with the nearby tide gauges readings. The precision of the altimeters is depending on location and mission and is shown to be better than 3 cm. The relative drifts between tide gauges and altimetry are discussed.

How to cite: Esselborn, S. and Schöne, T.: Monitoring SAR-altimeter missions at non-dedicated tide gauge stations in the German Bight, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13466, https://doi.org/10.5194/egusphere-egu22-13466, 2022.

Measuring river water level is essential for the global freshwater system monitoring, water resource management, hydrological model development, and climate change assessment. Despite its importance, the number of in-situ gauges has decreased over the recent decades. Moreover, many of the river systems are monitored either sparsely or not long enough to investigate their long-term evolution. Satellite altimetry is a unique technique that has enabled quantifying river levels for more than 25 years. Single mission altimetric water level time series can be obtained at the intersection of the satellite ground tracks and the river. For operational hydrology, however, single mission satellite altimetry is limited in its spatial and temporal sampling governed by the orbit configuration. This study proposes a framework to estimate the long-term sub-monthly river water level over the entire river using Least-Squares Collocation (LSC) by benefiting from multi-mission altimetric water levels (both interleaved and repeat orbit missions). The proposed method allows us to obtain dense water level observations both in time and space.  We present the results over the Mackenzie River basin, located in Canada, and validate against in-situ data.

How to cite: Saemian, P., Tourian, M. J., and Sneeuw, N.: A least-squares collocation approach to densifying river level from multi-mission satellite altimetry; Case study Mackenzie River basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3699, https://doi.org/10.5194/egusphere-egu22-3699, 2022.

Surface water level and river discharge are key observables of the water cycle and among the most sensible indicators that integrate long-term change within a river basin. Satellite altimetry provides valuable information on water level variation in rivers, lakes and reservoirs and once combined with satellite imagery, river discharge and lake storage changes can be estimated. Over the last decade, a two-dimensional observational field is derived by merging innovative space and in-situ data. The new generation of spaceborne altimeters includes Delay Doppler since 2010 with CryoSat-2, laser technique since 2018 with ICESAT-2 and bistatic SAR altimeter techniques with SWOT planned to be launched late this year. This shows a potential for monitoring the impact of water use and to characterize climate change. The mission SWOT will provide river discharge innovatively derived from contemporaneous river slope, height and width observations.

Our hypothesis is that the new space missions provide (a) surface water levels of higher accuracy and resolution compared to previous altimetric and in-situ observations and (b) new parameters to estimate river discharge and water storage change. A better sampling of flood event detection and of the long-term evolution is expected. We discuss here methodology and applications for satellite altimetry in the fields of hydrology and consider the two open research questions: (1) How can we fully exploit the new missions to derive best estimates of water level and storage change and river discharge and (2) can we separate natural variability from human water use.

For the first goal, we derive a multi-sensor database in an automatic processing which identifies the virtual gauge location and constructs the water height and water extension time-series. Water heights of the official release and of enhanced processing in project Hydrocoastal and in-house are used. Discharge and storage change time-series are derived from hydraulic equations using water extension and slope. First river basin considered is the Rhine river basin, where we obtain at 20 virtual stations a mean accuracy of 15 cm comparing altimeter and river height data. The derived discharge agrees within 18% with the in-situ discharge estimate.

For the second goal, we study past and present discharge and storage change, which are responses to both anthropogenic (deforestation, land use change, urbanization, reservoirs) and natural (climate modes, climate variability, rainfall, glacier and snow melting) processes. We discuss potential and limitations of satellite altimetry constellations for monitor recent river extremes and long-term changes. The work is part of Collaborative Research Centre CRC1502 “Regional Climate Change: Disentangling the role of Land Use and water management” of the German Research Foundation DFG.

How to cite: Fenoglio-Marc, L., Uyanik, H., Chen, J., and Kusche, J.: Impact analysis of surface water level and discharge from the new generation of altimetry observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10723, https://doi.org/10.5194/egusphere-egu22-10723, 2022.

Satellite altimetry is a technique of measuring height. Originally developed to observe sea level dynamics, altimetry has proven its usefulness in monitoring inland waters. Over the recent years these observations became an important supplement to the classical river gauge records. Due to the improvement of the accuracy of altimetric measurements, river water levels are being used in numerous hydrological projects, aiming to calculate water storage or to predict water levels and river discharges. Despite the improving quality of altimetric data, the accuracy of river stage measurements is still in the decimetre range, an order of magnitude lower than altimetry-based sea level observations. This is due to several factors that can lead to the deterioration of altimeter readings.

Our study is the first attempt to assess the accuracy of water levels measured by the Sentinel-3A altimetry at virtual stations (intersections of a satellite ground tracks and a river channel, hereinafter abbreviated as VS) located along Polish rivers. Further, this study aims to investigate the influence of the environmental factors on the data accuracy. The study is conducted on six biggest Polish rivers (Vistula, Odra, Warta, Bug, Narew, San) which drain predominantly lowlands, and – based on width – can be classified as small and medium rivers (40–610 m in width).

In order to assess the accuracy of measurements at virtual sites, we compare water level anomalies of these readings with stages from two adjacent gauges: one downstream and one upstream a VS. In this study we used Sentinel-3A water levels from the Hydroweb database (http://hydroweb.theia-land.fr/ – last access 09.01.2022). The time span of gauge and altimetry data ranges from April 2016 to August 2019. Since the virtual sites are located up to 73 km away from the adjacent gauges (with mean distance of 20.12 km), we decided to calculate the time shift occurring between the analysed stations. Such a unification of times is based on a two-gauge relationship, calculated for each of the satellite measurements.

We found that the root mean square error ranges from 0.12 to 0.44 m, with mean of 0.22 m. The Nash–Sutcliffe efficiency (NSE) varies between 0.40 and 0.98 (with mean of 0.84) for 67 pairs of time series, out of 68 considered. We found no correlation between the accuracy of Sentinel-3A water levels and the river width, neither for the small nor medium river sections. Likewise, land cover (determined using the Corine Land Cover 2018 data) has not been identified as an environmental factor to constrain the data accuracy. However, we found that complex river channel morphology (i.e. the occurrence of sandbars) and the unfavourable geographical setting of the VS (river channel parallel to satellite ground track or its multiple crossing) occur more often at VS with lower NSE (⩽0.8).

This study confirms the usability of the Sentinel-3A altimetry over Polish rivers and identifies factors to constrain its accuracy. The research is supported by the National Science Centre, Poland, through the project no. 2020/38/E/ST10/00295. Our results were recently published in Journal of Hydrology (https://doi.org/10.1016/j.jhydrol.2021.127355).

How to cite: Halicki, M. and Niedzielski, T.: Influence of environmental factors on the accuracy of the Sentinel-3A altimetry over Polish rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4221, https://doi.org/10.5194/egusphere-egu22-4221, 2022.