Search

The height of the mean sea surface above the reference ellipsoid is a time independent reference model that can be removed from radar altimeter measurements to isolate the oceanographic signals.  This document explains how the CLS mean sea surface model is updated at short wavelengths using the 30-years of sea surface slope measurements that have been archived and computed at Scripps Institution of Oceanography.  The data are available at https://topex.ucsd.edu/pub/ .

Rivers play a crucial role in maintaining ecosystems and regional climates, while also providing essential water for irrigation and drinking. With the increasing impacts of climate change and human activities, rivers are becoming more prone to extreme events (droughts and floods) and induced erosion/deposition processes, making water-related risk management more challenging. The recent launch of the Surface Water and Ocean Topography (SWOT) mission, which focuses on continental surfaces with a spatial resolution of 100 m, has opened new avenues for applications in hydrology, hydrodynamics, and geomorphology. This study examines the initial results of the SWOT mission for sixteen rivers (ranging in width from 50 to 2,000 m) in the Cuvette Centrale of the Congo Basin, obtained in April 2023 during the fast sampling phase. The study assesses water surface elevations (WSE) and backscatter coefficient (s0) measured from SWOT. Comparisons of WSE with data from other radar altimetry missions (Sentinel-3A and 3B, Jason-3, and Sentinel-6A) and GEDI data show high correlation coefficients of 0.977 (with a bias of 0.538 m) and 0.992 (with a bias of 1.011 m), respectively. The first maps of WSE slopes show realistic values, even in rivers less than 100mwide, with steeper slopes upstream. Various WSE longitudinal profiles are retrieved with unprecedented spatial resolution, surpassing what other nadir altimetry missions have achieved. The s0 values, between -10 and 20 dB on average, also appear consistent with other studies. These promising initial results pave the way for future studies on fluvial geomorphology dynamics and erosion/deposition processes from the new SWOT observations. [ABSTRACT FROM AUTHOR]

• SCMR achieves better performance than CMEMS and ESA CCI in the northern SCS. • Variation reveals a non-linear feature of sea level trends from offshore oceans to coasts. • The impact of ENSO signals on the sea level trends along the Chinese coast is dampened. With improved altimeter data near the coast, it is possible to use them in analysis of coastal sea level trends. In this study, we assess the sea level trends over January 2002-April 2022 with the SCMR-reprocessed altimeter dataset in the coastal zone of the northern South China Sea (SCS). The reliability of this dataset is confirmed by the inter-comparison with the CMEMS (Copernicus Marine Environment Monitoring Service) Level-3 along-track data product and the ESA CCI (European Space Agency Climate Change Initiative) v2.2 virtual station product, along with the validation against tide gauge records. Compared to two altimeter products, the SCMR has a higher number of data points for the analysis of sea level trends in the study region (28439 vs 1408 for CMEMS and 868 for ESA CCI). The monthly SLA time series from the SCMR dataset are more consistent with those from tide gauge records in terms of higher correlation coefficients (0.37–0.83) and lower root mean square of the differences (RMSD, 33.98–92.19 mm) between altimeter and tide gauge. The along-track sea level trends within the 0–20 km coastal strip range between 2–5 mm yr−1, and the degradation of sea level trends occurs when the along-track trends show significant fluctuations at the spatial scales of ∼ 300 m. Therefore, a further data editing strategy is recommended in this regard. We also find that the ENSO-related signals mainly impact on sea levels in the west of Luzon Strait and of the Philippine coast, but are dampened along the Chinese coast over 2002–2022. The regional mean sea level trend is reduced from 3.54 ± 0.85 mm yr−1 to 3.00 ± 0.84 mm yr−1 after removing the ENSO-related low-frequency variability. Finally, the variation of sea level trends from offshore oceans to coasts is found to be nonlinear, indicating the complexity of sea level changes in the study area. The blending of tide gauge records and the SCMR dataset has been successfully conducted in four tide gauges over a longer period of January 1993-April 2022, which would contribute to the analysis of long-term sea level trends at the local scales. [ABSTRACT FROM AUTHOR]

Sea state bias (SSB) is a crucial error of satellite radar altimetry over the ocean surface. For operational nonparametric SSB (NPSSB) models, such as two-dimensional (2D) or three-dimensional (3D) NPSSB, the solution process becomes increasingly complex and the construction of their regression functions pose challenges as the dimensionality of relevant variables increases. And most current SSB correction models for altimeters still follow those of traditional nadir radar altimeters, which limits their applicability to Synthetic Aperture Radar altimeters. Therefore, to improve this situation, this study has explored the influence of multi-dimensional SSB models on Synthetic Aperture Radar altimeters. This paper proposes a deep learning-based SSB estimation model called SNSSB, which employs a Siamese network framework, takes various multi-dimensional variables related to sea state as inputs, and uses the difference in sea surface height (SSH) at self-crossover points as the label. Experiments were conducted using Sentinel-6 self-crossover data from 2021 to 2023, and the model is evaluated using three main metrics: the variance of the SSH difference, the explained variance, and the SSH difference variance index (SVDI). The experimental results demonstrate that the proposed SNSSB model can further improve the accuracy of SSB estimation. On a global scale, compared to the traditional NPSSB, the multi-dimensional SNSSB not only decreases the variance of the SSH difference by over 11%, but also improves the explained variance by 5-10 cm2 in mid- and low-latitude regions. And the regional SNSSB also performs well, reducing the variance of the SSH difference by over 10% compared to the NPSSB. Additionally, the SNSSB model improves the computational efficiency by approximately 100 times. The favorable results highlight the potential of the multidimensional SNSSB in constructing SSB models, particularly the five-dimensional (5D) SNSSB, representing a breakthrough in overcoming the limitations of traditional NPSSB for constructing high-dimensional models. This study provides a novel approach to exploring the multiple influencing factors of SSB. [ABSTRACT FROM AUTHOR]

The Greenland and Antarctic ice sheets are important indicators of climate change and major contributors to sea level rise. Hence, precise, long-term observations of ice mass change are required to assess their contribution to sea level rise. Such observations can be achieved through three different methods. They can be achieved directly by measuring regional changes in the Earth's gravity field using the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) satellite system. Alternatively, they can be achieved indirectly by measuring changes in ice thickness using satellite altimetry or by estimating changes in the mass budget using a combination of regional climate model data and ice discharge across the grounding line, based on multi-sensor satellite radar observations of ice velocity. Satellite radar altimetry has been used to measure elevation change since 1992 through a combination of various missions. In addition to the surface slope and complex topography, it has been shown that one of the most challenging issues concerns spatial and temporal variability in radar pulse penetration into the snowpack. This results in an inaccurate measurement of the true surface elevation and consequently affects surface elevation change (SEC) estimates. To increase the accuracy of surface elevation measurements retrieved by retracking the radar return waveform and thus reduce the uncertainty in the SEC, we developed a deep convolutional-neural-network architecture (AWI-ICENet1). AWI-ICENet1 is trained using a simulated reference data set with 3.8 million waveforms, taking into account different surface slopes, topography, and attenuation. The successfully trained network is finally applied as an AWI-ICENet1 retracker to the full time series of CryoSat-2 Low Resolution Mode (LRM) waveforms over both ice sheets. We compare the AWI-ICENet1-retrieved SEC with estimates from conventional retrackers, including the threshold first-maximum retracker algorithm (TFMRA) and the European Space Agency's (ESA) ICE1 and ICE2 products. Our results show less uncertainty and a great decrease in the effect of time-variable radar penetration, reducing the need for corrections based on its close relationship with backscatter and/or leading-edge width, which are typically used in SEC processing. This technique provides new opportunities to utilize convolutional neural networks in the processing of satellite altimetry data and is thus applicable to historical, recent, and future missions. [ABSTRACT FROM AUTHOR]

The provision of accurate wet tropospheric corrections (WTC), accounting for the delay of the radar pulses caused mostly by the atmospheric water vapor in the altimeter‐range observations, is pivotal for the full exploitation of altimeter‐derived surface heights. The WTC is best retrieved by measurements from Microwave Radiometers (MWR) on board the same altimeter mission. However, these instruments fail to provide valid WTC over land and ice and under rainy conditions. The GNSS‐derived Path Delay Plus (GPD+) algorithm has been designed to provide WTC over these surfaces where the onboard MWR WTC is invalid. This study focuses on the estimation of enhanced GPD+ WTC for the Copernicus Sentinel‐3A and Sentinel‐3B satellites, for the latest Baseline Collection 005.02 (BC005.2), spanning the period since the beginning of the missions until March 2023. GPD+ corrections are being provided operationally since 2022 and have been adopted as the default WTC in the calculation of the sea level anomaly (SLA). Compared to previous versions, the BC005.2 GPD+ WTC features improved data combination procedures, possesses a larger percentage of points estimated from observations, a better intermission alignment and reduced systematic differences among ascending and descending passes. Overall, GPD+ WTC are consistent, calibrated corrections, valid over all points present in the Non Time Critical marine product, allowing to recover, on average, about 17% of the altimeter observations with valid SLA, which otherwise, most of them would be rejected. Impacts of these WTC are most significant over coastal and inland water regions, at high latitudes and during rain events. Plain Language Summary: Satellite radar altimetry is a powerful technique to measure the Earth's topography during day and night, in all weather conditions. It uses radar pulses to measure the distance between the satellite and the surface beneath the satellite, from which the height of the mean sea level, rivers and lakes, for example, can be obtained. The atmosphere affects the propagation by delaying the signal and increasing the measured trajectory. The effect of the atmospheric water vapor is particularly difficult to model, since it is highly variable. This study concerns with a method to estimate the so‐called wet tropospheric correction, which accounts for the water vapor effects in the altimeter measurements. Over open ocean, the correction is usually based on the measurements from a dedicated instrument collocated on the same satellite, which fails to provide valid information over non‐water surfaces. The method, called GNSS‐derived Path Delay Plus (GPD+), aims to fill the gaps left by the previous instrumental correction. The study describes the latest version of the GPD+ wet tropospheric corrections for the Copernicus Sentinel‐3 altimeter products. It is demonstrated that these corrections can extend the altimeter observations to important regions such as coastal regions, rivers and lakes and high latitudes. Key Points: New GPD+ wet tropospheric corrections have been produced for Sentinel‐3, for the latest Baseline Collection (BC) 005.02These corrections are consistent, calibrated, valid over all surface types, improving data coverage mainly over coastal and polar regionsGPD+ are improved wet tropospheric corrections with respect to the Sentinel‐3 onboard radiometer and to the European Centre for Medium Range Weather Forecasts (ECMWF) operational model [ABSTRACT FROM AUTHOR]

The Sentinel-3A and Sentinel-3B satellites, launched in February 2016 and April 2018 respectively, build on the legacy of CryoSat-2 by providing high-resolution Ku-band radar altimetry data over the polar regions up to 81° North. The combination of synthetic aperture radar (SAR) mode altimetry (SRAL instrument) from Sentinel-3A and Sentinel-3B, and the Ocean and Land Colour Instrument (OLCI) imaging spectrometer, results in the creation of the first satellite platform that offers coincident optical imagery and SAR radar altimetry. We utilise this synergy between altimetry and imagery to demonstrate a novel application of deep learning to distinguish sea ice from leads in spring. We use SRAL classified leads as training input for pan-Arctic lead detection from OLCI imagery. This surface classification is an important step for estimating sea ice thickness and to predict future sea ice changes in the Arctic and Antarctic regions. We propose the use of Vision Transformers (ViT), an approach adapting the popular deep learning algorithm Transformer, for this task. Their effectiveness, in terms of both quantitative metric including accuracy and qualitative metric including model roll-out, on several entire OLCI images is demonstrated and we show improved skill compared to previous machine learning and empirical approaches. We show the potential for this method to provide lead fraction retrievals at improved accuracy and spatial resolution for sunlit periods before melt onset. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions. [ABSTRACT FROM AUTHOR]

Subglacial lakes have been mapped across Antarctica with two methods, radio‐echo sounding (RES) and ice‐surface deformation. At sites where both are coincident, these methods typically provide conflicting interpretations about the ice‐bed interface. With a single exception, active subglacial lakes identified by surface deformation do not display the expected flat, bright, and specular bed reflection in RES data, characteristic of non‐active lakes. This observational conundrum suggests that our understanding of Antarctic subglacial hydrology, especially beneath important fast‐moving ice streams, remains incomplete. Here, we use an airborne RES campaign that surveyed a well‐characterized group of active subglacial lakes on lower Mercer and Whillans ice streams, West Antarctica, to explore inconsistency between the two observational techniques. We test hypotheses of increased scattering and attenuation due to the presence of an active subglacial lake system that could suppress reflected bed‐echo power for RES observations in these locations, finding that entrained water is most plausible. Plain Language Summary: The bottom of an ice sheet is insulated from cold air temperatures, often warm enough to melt and pond liquid water into lakes. These lakes beneath the ice sheet have been identified by two independent measurements, first with radar methods and second with changes in height of the ice surface (altimetry). Interestingly, the two methods rarely identify the same lakes: radar generally detects lakes in the ice‐sheet interior, whereas altimetry detects active lakes near the ice‐sheet margins that fill and drain within the time series of repeated measurements (∼years). In this study, we investigate a group of active subglacial lakes at which both radar and altimetry data sets are available. We demonstrate that the radar returns from active lake reflections are much dimmer than expected based on non‐active lake signatures and investigate the physical processes controlling those dim reflections. We argue that water moves into the ice when the lake fills or drains and that is the most plausible explanation for the observational discrepancy. Key Points: Active subglacial lakes, identified by surface deformation, do not create the expected bright and specular radar reflectionEntrained water in basal ice suppresses radar power by scattering and attenuation, and it also likely alters the basal ice mechanicsUnderstanding the radar expression of subglacial water on Earth provides context for investigations of subsurface water on planetary bodies [ABSTRACT FROM AUTHOR]

The impact of an episodic river flood is intimately linked to its duration. Yet it is still unclear how often should a river be observed to accurately determine the occurrence and duration of extreme events. Here we assess flow statistics along with peak flow event detection and duration as a function of the discharge sampling period for large tributaries of the Mississippi basin using hourly gages over 2010–2022. Median event durations above high quantiles spatially vary from around 2 days upstream to 30 days downstream. Discharge mean, standard deviation, and quantiles can all be estimated within 2.5% error for sampling periods up to 8 days. A minimum temporal sampling 4× (2×) finer than peak flow event median duration is required to detect 95 ± 3% (85 ± 5%) of events and to estimate their duration within 90 ± 5% (75 ± 10%) median accuracy. Our findings have direct implications for future satellite missions concerned with capturing flood events. Plain Language Summary: High flow events and their duration in rivers are key aspects of flood studies. Yet, it is still unclear how often a river should be observed to detect floods and determine their durations. Analyzing hourly stream gage data in the Mississippi River basin from 2010 to 2022, we calculate that flood events vary widely in duration from upstream (2 days) to downstream (30 days). We show that observing large rivers every few days is sufficient to compute common long‐term river flow statistics within 2.5% error. However, capturing most floods and accurately assessing their duration (within 10% error) requires monitoring at least four times more frequently than the typical duration of these events. This means that if a major flood typically lasts 10 days, the river data should be collected at least every 2–3 days. Our findings have implications for the design of monitoring systems concerned with the accurate capture of floods, including those using Earth orbiting satellites. Key Points: Peak flow events in the Mississippi basin range from 2 days upstream to 30 days downstream, hence exhibiting acute spatial variabilityDecadal mean, standard deviation and quantiles of hourly discharge can all be computed within 2.5% error up to an 8‐day sampling periodSampling periods must be a factor of 4 finer than median peak flow event durations to estimate durations within 90 ± 5% median accuracy [ABSTRACT FROM AUTHOR]

The Cassini spacecraft performed several flybys of Saturn's largest moon, Titan, collecting valuable data. During several passes, altimetric data were acquired. Here, we focus on altimetric measurements collected by Cassini's radar when flying over the same region at different epochs in order to correlate such measurements (crossovers) and investigate differences in altimetry. In our study, we assess altimetric errors associated with three distinct methods for extracting topography from Cassini's radar data: the maximum likelihood estimator (MLE), the threshold method, and the first moment technique. Focusing on crossover events, during which Cassini revisited specific areas of Titan's surface, we conduct a detailed examination of the consistency and accuracy of these three topography extraction methods. The proposed analysis involves closely examining altimetric data collected at different epochs over identical geographical regions, allowing us to investigate potential errors due to the variations in off-nadir angle, relative impact, uncertainties, and systematic errors inherent in the application of these methodologies. Our findings reveal that the correction applied for the off-nadir angle to the threshold and first moment methods significantly reduces the dispersion in the delta difference at the crossover, resulting in a dispersion of the order of 60 m, even lower than what is achieved with the MLE (~70 m). Additionally, an effort is made to assess the potential of Cassini for estimating the tidal signal on Titan. Considering the altimetric errors identified in our study and the relatively low number of crossovers performed by Cassini, our assessment indicates that it is not feasible to accurately measure the tidal signal on Titan using the currently available standard altimetry data from Cassini. Our assessment regarding the accuracy of the Cassini altimeter provides valuable insights for future planetary exploration endeavors. Our study advances the understanding of Titan's complex landscape and contributes to refining topographical models derived from Cassini's altimetry observations. These insights not only enhance our knowledge of Saturn's largest moon but also open prospects for Titan surface and interior exploration using radar systems. [ABSTRACT FROM AUTHOR]

The wave-affected marginal ice zone (MIZ) is an essential part of the sea ice cover and crucial to the atmosphere–ice–ocean interaction in the polar region. While we primarily rely on in situ campaigns for studying MIZs, significant challenges exist for the remote sensing of MIZs by satellites. This study develops a novel retrieval algorithm for wave-affected MIZs based on the delay-Doppler radar altimeter on board CryoSat-2 (CS2). CS2 waveform power and waveform stack statistics are used to determine the part of the sea ice cover affected by waves. Based on the CS2 data since 2010, we generate a climate record of wave-affected MIZs in the Atlantic Arctic, spanning 12 winters between 2010 and 2022 (10.5281/zenodo.8176585,). The MIZ record indicates no significant change in the mean MIZ width or the extreme width, although large temporal and spatial variability is present. In particular, extremely wide MIZ events (over 300 km) are observed in the Barents Sea, whereas in other parts of the Atlantic Arctic, MIZ events are typically narrower. We also compare the CS2-based retrieval with the retrievals based on the laser altimeter of ICESat2 and the synthetic aperture radar images from Sentinel-1. Under spatial and temporal collocation, we attain good agreement among the MIZ retrievals based on the three different types of satellite payloads. Moreover, the traditional sea-ice-concentration-based definition of MIZ yields systematically narrower MIZs than CS2, and no statistically significant correlation exists between the two. Beyond its application to CS2, the proposed retrieval algorithm can be adapted to historical and future radar altimetry campaigns. The synergy of multiple satellites can improve the spatial and temporal representation of the altimeters' observation of the MIZs. [ABSTRACT FROM AUTHOR]

Spatio-temporal dynamics of surface water reservoirs at regional and global scales remain poorly understood. Using satellite remote sensing provides a unique opportunity to address this problem. This study aims to (1) quantify the extent and volume of surface water and (2) compare our approach with other datasets. We utilized MODIS-based spectral indices to monitor temporal variations in inundation extent. By interpolating water levels across the surface water extent, we generated water level maps and quantified surface water volume from 2000 to 2022. Evaluation against ICESat-2 data involved 64 comparisons, with approximately 58% showing an R2 value greater than or equal to 0.5, and 38% were higher than or equal to 0.7. Compared to the flooding model, our method aligns more closely with ICESat-2 data, contrary to the flooding model which tends to overestimate water levels and, consequently, water storage. [ABSTRACT FROM AUTHOR]

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth's surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth's surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. [ABSTRACT FROM AUTHOR]

This study presents a generalised characterisation of the surface circulation over the northern shelf of the Gulf of Cadiz, based on 4 years of high-resolution satellite altimetry data from Sentinel-3A and wind model data. The altimetry-based surface zonal currents, adjusted for bottom-drag and wind effects, are compared with a generic CMEMS product and validated against in-situ ADCP measurements. The proposed altimetry product demonstrates superior performance than the CMEMS product, accurately reflecting surface circulation direction compared to in-situ measurements (r = 0.77, RMSE = 0.10 m/s, bias = 0.01 m/s). The use of the bottom-drag and wind-corrected/uncorrected altimetry product for spatiotemporal analysis of the shelf circulation revealed the distinct contributions of wind-driven and geostrophic components in different basin sectors. The results show that over the western basin, positive (eastward) surface currents were predominantly driven by westerly winds, while only occasionally, westward flows coincided with easterly winds, suggesting a higher control of the geostrophic component over the westward flows. In contrast, over the eastern basin, both eastward and westward flows were found to be primarily driven by favourable winds. Additionally, the analysis of Absolute Dynamic Topography (ADT) values along the whole basin showed the presence of ADT gradients both along-shore and cross-shore over the shelf, contributing to geostrophic flows. Finally, the seasonal analysis showed that eastward circulation tends to dominate during the spring and summer months, related to the upwelling season in the Gulf of Cadiz and associated westerly winds. Westward flows prevail during the winter months, related to easterly winds and the rebalancing of the along-shore sea level gradient during relaxed upwelling conditions. The findings demonstrate a significant improvement in the use of satellite altimetry data to study complex oceanographic dynamics in coastal areas, where both spatial and temporal variability are high. Moreover, the similarity of our results to those obtained from in-situ systems supports the use of altimetry data and publicly available wind models to support oceanographic studies in remote or resource-limited areas. [ABSTRACT FROM AUTHOR]

The firn layer on the Greenland Ice Sheet (GrIS) plays a crucial role in buffering surface meltwater runoff, which is constrained by the available firn pore space and impermeable ice layers that limit deeper meltwater percolation. Understanding these firn properties is essential for predicting current and future meltwater runoff and its contribution to global sea-level rise. While very-high-frequency (VHF) radars have been extensively used for surveying the GrIS, their lower bandwidth restricts direct firn stratigraphy extraction. In this study, we use concurrent VHF airborne radar and laser altimetry data collected as part of Operation IceBridge over the 2011–2019 period to investigate our hypothesis that vertical heterogeneities in firn (i.e. ice layers) cause vertical offsets in the radar surface reflection (dz). Our results, corroborated by modelling and firn core analyses, show that a dz larger than 1 m is strongly related to the vertical heterogeneity of a firn profile and effectively delineates between vertically homogeneous and vertically heterogeneous firn profiles over a depth range of ∼ 4 m. Temporal variations in dz align with climatic events and reveal an expansion of heterogeneous firn between 2011–2013 covering an area of ∼ 350 815 km 2 , followed by firn replenishment over the years 2014–2019 spanning an area of ∼ 667 725 km 2. Our approach reveals the firn evolution of key regions on the Greenland Ice Sheet, providing valuable insights for detecting potential alterations in meltwater runoff patterns. [ABSTRACT FROM AUTHOR]

For nearly three decades, satellite radar altimetry has provided measurements of the water surface elevation (WSE) of rivers. These observations can be used to calculate the water surface slope (WSS), which is an essential parameter for estimating flow velocity and river discharge. In this study, we calculate a non time‐varying high‐resolution WSS of 11 Polish rivers based on multi‐mission altimetry observations from 11 satellites in the period from 1994 to 2023. The proposed approach is based on a weighted least squares adjustment with an additional Laplace condition and an a priori gradient condition. The processing is divided into river sections not interrupted by dams and reservoirs. After proper determination of the WSE for each river kilometer (bin), the WSS between adjacent bins is calculated. To assess the accuracy of the estimated WSS, it is compared with slopes between gauge stations, which are referenced to a common vertical datum. Such gauge stations are available for 8 studied rivers. The root mean squared error (RMSE) ranges from 4 mm/km to 77 mm/km, with an average of 27 mm/km. However, the mean RMSE decreases to 11 mm/km when the 2 mountain rivers are excluded. The WSS accuracies are also compared with slope data sets based on digital elevation models, ICESat‐2 altimetry, and lidar. For 6 rivers the estimated WSS shows the highest accuracy. The improvement was particularly significant for mountain rivers. The proposed approach allows an accurate, non time‐varying high‐resolution WSS even for small and medium‐sized rivers and can be applied to almost any river worldwide. Plain Language Summary: The Water Surface Slope (WSS) of a river is a measure of how steeply it flows downstream. This value affects the velocity of the water and also the force with which the water erodes the river bed. WSS is calculated by dividing the difference between two water surface elevations (WSE) by the length of the river section between these points. In this paper, we determine the non time‐varying WSS on almost every kilometer of 11 Polish rivers. For this purpose, we used almost 30 years of satellite altimetry measurements, which provide information about the height of the water surface at a given place and time. After filtering and mathematical adjustment of these measurements, we determined the WSE and WSS on almost every kilometer of the studied rivers. We compared our results with the average gradients between neighboring water level gauge stations, and for most rivers we obtained very small errors. Compared to other sources of WSS data, our method showed the highest accuracy. The results presented in this work are the first such accurate and spatially dense WSS information of Polish rivers. Moreover, the proposed method allows the determination of WSS on almost any river in the world. Key Points: High‐resolution non time‐varying water surface slope (WSS) for 11 Polish rivers have been determined using cross‐calibrated multi‐mission altimetry measurementsFor 8 rivers studied, we obtained a mean root mean square error of 27 mm/km, which decreases to 11 mm/km if 2 mountain rivers are excludedFor 6 rivers, the estimated WSS showed the highest accuracy compared to WSS data sets based on digital elevation models, ICESat‐2, or lidar [ABSTRACT FROM AUTHOR]

Inland water level and its dynamics are key components in the global water cycle and land surface hydrology, significantly influencing climate variability and water resource management. Satellite observations, in particular altimetry missions, provide inland water level time series for nearly three decades. Space-based remote sensing is regarded as a cost-effective technique that provides measurements of global coverage and homogeneous accuracy in contrast to in-situ sensors. The advent of Open-Loop Tracking Command (OLTC), and Synthetic Aperture Radar (SAR) mode strengthened the use of altimetry missions for inland water level monitoring. However, it is still very challenging to obtain accurate measurements of water level over narrow rivers and small lakes. This scoping systematic literature review summarizes and disseminates the research findings, highlights major results, and presents the limitations regarding inland water level monitoring from satellite observations between 2018 and 2022. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and through a double screening process, 48 scientific publications were selected meeting the eligibility criteria. To summarize the achievements of the previous 5 years, we present fundamental statistical results of the publications, such as the annual number of publications, scientific journals, keywords, and study regions per continent and type of inland water body. Also, publications associated with specific satellite missions were analyzed. The findings show that Sentinel-3 is the dominant satellite mission, while the ICESat-2 laser altimetry mission has exhibited a high growth trend. Furthermore, publications including radar altimetry missions were charted based on the retracking algorithms, presenting the novel and improved methods of the last five years. Moreover, this review confirms that there is a lack of research on the collaboration of altimetry data with machine learning techniques. [ABSTRACT FROM AUTHOR]

Meltwater forms at the base of the Antarctic Ice Sheet due to geothermal heat flux (GHF) and basal frictional dissipation. Despite the relatively small volume, this water has a profound effect on ice-sheet dynamics. However, subglacial melting and hydrology in Antarctica remain highly uncertain, limiting our ability to assess their impact on ice-sheet dynamics. Here we examine subglacial hydrology within the Amery Ice Shelf catchment, East Antarctica, using the subglacial hydrology model GlaDS. We calculate subglacial melt rates using a higher-order ice-flow model and two GHF estimates. We find a catchment-wide melt rate of 7.03 Gt year 1 (standard deviation = 1.94 Gt year 1), which is =50% greater than previous estimates. The contribution from basal dissipation is approximately 40% of that from GHF. However, beneath fast-flowing ice streams, basal dissipation is an order of magnitude larger than GHF, leading to a significant increase in channelized subglacial flux upstream of the grounding line. We validate GlaDS using high-resolution interferometric-swath radar altimetry, with which we detect active subglacial lakes and fine-scale ice-shelf basal melting. We find a network of subglacial channels that connects areas of deep subglacial water coincident with active subglacial lakes, and channelized discharge at the grounding line coinciding with enhanced ice-shelf basal melting. The concentrated discharge of meltwater provides 36% of the freshwater released into the iceshelf cavity, in addition to ice-shelf basal melting. This suggests that ice-shelf basal melting is strongly influenced by subglacial hydrology and could be affected by future changes in subglacial discharge, such as lake drainage or channel rerouting. Plain Language Summary Melting beneath the Antarctic Ice Sheet is relatively low, but the pattern of melting and meltwater drainage is important for controlling the flow of the overlying ice. Melting occurs due to geothermal heating from the underlying bedrock and heat generated from friction as the ice slides over the bedrock. Despite its importance, we know very little about melting beneath the Antarctic Ice Sheet. Here we use a numerical model to calculate meltwater drainage pathways beneath part of the ice sheet that flows into the Amery Ice Shelf, East Antarctica. We find that total melting is 7 gigatonnes per year. This is 50% more than previous studies because our model can resolve high melting beneath areas where the ice sheet is flowing fast. Using satellite observations of ice-sheet surface elevation change, we detect the filling and draining of lakes at the base of the ice sheet and ocean melting beneath the floating ice shelf. We use these observations to validate the modeled meltwater drainage pathways at the base of the ice sheet. These findings suggest that meltwater drainage from the base of the ice sheet may play an important role in controlling ocean melting of the floating ice shelf. [ABSTRACT FROM AUTHOR]

Generating accurate monthly estimations of water level fluctuations in reservoirs and lakes is crucial for supporting effective water resource management and protection. The dual-satellite configuration of Sentinel-3 makes it possible to monitor water level changes with great coverage and short time intervals. However, the potential of Sentinel-3's Synthetic Aperture Radar Altimetry (SRAL) data to enable operational monitoring of water levels across Jiangsu Province on a monthly basis has not yet been fully explored. This study demonstrated and validated the use of Sentinel-3's SRAL to generate accurate monthly water level estimations needed to inform water management strategies. The monthly water levels of lakes and reservoirs from 2017 to 2021 were produced using Sentinel-3 level-2 land products. Results showed that, compared with in situ data across eight studied lakes, all lakes presented R (Pearson correlation coefficient) values greater than 0.5 and Root Mean Square Error (RMSE) values less than 1 m. Notably, water level estimates for Tai Lake, Gaoyou Lake, and Luoma Lake were particularly accurate, with R above 0.9 and RMSE below 0.5 m. Furthermore, the monthly water level estimates derived from the Sentinel-3 data showed consistent seasonal trends over the multi-year study period. The annual water level of all lakes did not change significantly, except for Shijiu Lake, of which the difference between the highest and lowest water level was up to about 5 m. Our findings confirmed the water level observation ability of Sentinel-3. The accuracy of water level monitoring could be influenced by internal water level differences, terrain features, as well as the area and shape of the lake. Larger lakes with more altimetry sampling points tended to yield higher accuracy estimates of water level fluctuations. These results demonstrate that the frequent, wide-area coverage offered by this satellite platform provides valuable hydrological information, especially across remote regions lacking in situ data. Sentinel-3 has immense potential to support improved water security in data-scarce regions. [ABSTRACT FROM AUTHOR]

Multi-mission satellite altimetry data have been used to study the spatial and temporal variability in global storm surge water levels. This was done by means of a time-dependent extreme value analysis applied to the monthly maximum detided water levels. To account for the limited temporal resolution of the satellite data, the data were first stacked on a 5 ∘ × 5 ∘ grid. Moreover, additional scaling was applied to the extreme value analysis for which the scaling factors were determined by means of a resampling method using reanalysis data. In addition to the conventional analysis using data from tide gauges, this study provides an insight in the ocean-wide storm surge properties. Nonetheless, where possible, results were compared to similar information derived from tide gauge data. Except for secular changes, the satellite-derived results are comparable to the information derived from tide gauges (correlation > 0.5 ), although the tide gauges show more local variability. Where limited correlation was observed for the secular change, it was suggested that the satellites may not be able to fully capture the temporal variability in the short-lived, tropical storms, as opposed to extra-tropical storms. [ABSTRACT FROM AUTHOR]

Despite having approximately 100,000 lakes, Sweden has limited continuous gauged lake water level data. Although satellite radar altimetry (RA) has emerged as a popular alternative to measure water levels in inland water bodies, it has not yet been used to understand the large‐scale changes in Swedish lakes. Here, we quantify the changes in water levels in 144 lakes using RA data and in situ gauged measurements to examine the effects of flow regulation and hydroclimatic variability. We use data from several RA missions, including ERS‐2, ENVISAT, JASON‐1,2,3, SARAL, and Sentinel‐3A/B. We found that during 1995–2022, around 52% of the lakes exhibited an increasing trend and 43% a decreasing trend. Most lakes exhibiting an increasing trend were in the north of Sweden, while most lakes showing a decreasing trend were in the south. Regarding the potential effects of regulation, we found that unregulated lakes had smaller trends in water level and dynamic storage than regulated ones. While the seasonal patterns of water levels in the lakes in the north are similar in regulated and unregulated lakes, in the south, they differ substantially. This study highlights the need to continuously monitor lake water levels for adaptation strategies in the face of climate change and understand the downstream effects of water regulatory schemes. Plain Language Summary: Energy production and water consumption have led to the regulation of many lakes in Sweden. To understand the consequences of human activities, we studied water level changes in 144 regulated and non‐regulated lakes, utilizing satellite data. We found that regulated lakes show larger water level changes and variability compared to non‐regulated ones. These findings underscore the need for effective adaptation strategies to mitigate the impacts of water regulatory schemes. Key Points: Increasing lake water level trends in 52% of all lakes and decreasing in 43% of themIncreasing water level trends in northern Sweden and decreasing in the southDifferent Water level seasonal patterns in regulated and non‐regulated lakes in the South [ABSTRACT FROM AUTHOR]

Abstract The impact of an episodic river flood is intimately linked to its duration. Yet it is still unclear how often should a river be observed to accurately determine the occurrence and duration of extreme events. Here we assess flow statistics along with peak flow event detection and duration as a function of the discharge sampling period for large tributaries of the Mississippi basin using hourly gages over 2010–2022. Median event durations above high quantiles spatially vary from around 2 days upstream to 30 days downstream. Discharge mean, standard deviation, and quantiles can all be estimated within 2.5% error for sampling periods up to 8 days. A minimum temporal sampling 4× (2×) finer than peak flow event median duration is required to detect 95 ± 3% (85 ± 5%) of events and to estimate their duration within 90 ± 5% (75 ± 10%) median accuracy. Our findings have direct implications for future satellite missions concerned with capturing flood events.

Satellite altimetry has revolutionized river monitoring, particularly for hydrologists working on river flow monitoring in sparsely or ungauged areas. Despite this, there is a lack of a comprehensive evaluation of radar and LiDAR altimeters with varying sensor specifications for river water level retrieval, seasonal change characterization, and water surface slope (WSS) using gauged long-term water level and global navigation satellite system data. This study addresses this gap by combined evaluation of radar (ENVISAT to Sentinel-3) and LiDAR (ICESat-1, ICESat-2) altimeters along the Ganga River, from Prayagraj to Varanasi. We found that all the radar altimetry missions showed better accuracy for water level retrievals (R2 > = 0.8; RMSE 0.11 to 1.16 m) and water level change quantification (RMSE 0.59 m). However, Sentinel-3 with synthetic aperture radar (SAR) acquisition mode outperformed (RMSE 0.11 to 0.14 m) all the radar missions having low resolution mode. Despite LiDAR missions' high vertical accuracy, they show relatively lower accuracy in water level time series generation due to nonrepeating characteristics. In contrary, ICESat-2 demonstrates potential in capturing spatial and seasonal variability of WSS, enhancing the accuracy of surface water and ocean topography (SWOT) discharge products when combined with SWOT River database. This study provides a comprehensive baseline for end-users interested in utilizing radar and LiDAR missions for various hydrological applications, including river discharge estimation. Moreover, the studied river reach shares the SWOT calibration orbit, allowing the utilization of generated satellite and in-situ databases for the effective evaluation of SWOT measurements.

Due to the presence of sea ice, determining the sea surface height in the Arctic Ocean remains a significant challenge. State-of-the-art Arctic Mean Sea Surface (MSS) products are primarily derived from radar altimetry missions like CryoSat-2. However, the ICESat-2 laser altimeter can offer valuable sea surface observations up to 88° N latitude, extending the observational reach. This paper analyses the performance of combined CryoSat-2 and ICESat-2 data in determining the Arctic sea surface. Comparisons of overlapping observations from both missions reveal excellent consistency, with an inter-mission bias of less than 1 cm in the Arctic. Different geophysical corrections are considered, and the results suggest that only the ocean tide correction needs to be unified, while other corrections show minimal discrepancies. The MSS derived from combined data boasts both superior spatial coverage and precision compared to individual missions. The impact of summer melt pond is also discussed. The data from June, July and August are seriously contaminated, but only have limited effect on the mean sea surface calculation. Overall, the combined use of CryoSat-2 and ICESat-2 data offers a promising approach to accurately determining the Arctic sea surface, paving the way for improved understanding of sea level change and its implications in this critical region. [ABSTRACT FROM AUTHOR]

Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km 2 , representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through 10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online , last access: 12 December 2023). [ABSTRACT FROM AUTHOR]

• A frequency-domain retracker with interface to In-Flight Point-Target-Response. • Assessment of the impact of In-Flight Point-Target-Response for Sentinel-6 MF. • The range walk correction applied via a Chirp-Zeta-Transform algorithm. • Assessment of the impact of the range-walk correction for Sentinel-6 MF. • A full Cal/Val of the first year of Sentinel-6 MF altimetry science data. Poseidon-4 is a dual-frequency redundant radar altimeter on board the European Commission Copernicus Programme Sentinel-6 Michael Freilich satellite, that represents a significant breakthrough with respect to its predecessors Jason-class altimeters due to its digital architecture and to its innovative measurements and calibration modes. In the framework of the Sentinel-6 Michael Freilich commissioning preparatory activities, CNES has contracted CLS for the development of a Sentinel-6 Processing Prototype (S6PP) application. S6PP is a multi-chain processing suite able to process Sentinel-6 Level-1A and Level-1B data products up to Level-2. The novel algorithms developed in the CNES/CLS research and development activities are implemented within S6PP and validated to support the different thematic applications (in particular inland water and ocean) and in view of promoting them for possible implementation in the operational ground segment. The present work covers in particular the main results over open ocean for the main altimetric geophysical variables over the sea surface (sea surface height anomaly, significant wave-height, sigma-nought and wind speed) derived by the Low-Resolution Mode (LRM) and High-Resolution Mode (HRM) chains of S6PP in terms of precision, accuracy, spectral content and measurement stability. Given the reported variation of the payload in-orbit temperatures along with the reported instrumental ageing, and given the tight requirement to measure the GMSL (Global Mean Sea Level) in seamless continuity with Jason-3, the clear goal for S6PP was to process the S6-MF data with the minimum possible level of approximations along the processing pipeline but still maintaining a very efficient prototype from the computational point of view. For this scope, a novel and computationally efficient numerical retracking scheme with interface to the in-flight PTR (Point Target Response) provided by the instrument calibration chain has been put in place within S6PP for both the Low-Resolution and High-Resolution modes whereas the Delay-Doppler beam-forming is carried out by applying the range walk correction based on a computationally efficient algorithm (Chirp Zeta-Transform). The impact of the range walk correction and of the in-flight PTR interface is assessed for HRM and LRM, respectively. The paper shows that the proposed processing baseline ensures a dataset robust from the currently known instrumental degradation or ageing issues, both in LRM and HRM mode and, once this is done, that Sentinel-6 Michael Freilich global mean sea level measurement is in line with the one measured by Jason-3. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions.

The Cassini spacecraft performed several flybys of Saturn’s largest moon, Titan, collecting valuable data. During several passes, altimetric data were acquired. Here, we focus on altimetric measurements collected by Cassini’s radar when flying over the same region at different epochs in order to correlate such measurements (crossovers) and investigate differences in altimetry. In our study, we assess altimetric errors associated with three distinct methods for extracting topography from Cassini’s radar data: the maximum likelihood estimator (MLE), the threshold method, and the first moment technique. Focusing on crossover events, during which Cassini revisited specific areas of Titan’s surface, we conduct a detailed examination of the consistency and accuracy of these three topography extraction methods. The proposed analysis involves closely examining altimetric data collected at different epochs over identical geographical regions, allowing us to investigate potential errors due to the variations in off-nadir angle, relative impact, uncertainties, and systematic errors inherent in the application of these methodologies. Our findings reveal that the correction applied for the off-nadir angle to the threshold and first moment methods significantly reduces the dispersion in the delta difference at the crossover, resulting in a dispersion of the order of 60 m, even lower than what is achieved with the MLE (~70 m). Additionally, an effort is made to assess the potential of Cassini for estimating the tidal signal on Titan. Considering the altimetric errors identified in our study and the relatively low number of crossovers performed by Cassini, our assessment indicates that it is not feasible to accurately measure the tidal signal on Titan using the currently available standard altimetry data from Cassini. Our assessment regarding the accuracy of the Cassini altimeter provides valuable insights for future planetary exploration endeavors. Our study advances the understanding of Titan’s complex landscape and contributes to refining topographical models derived from Cassini’s altimetry observations. These insights not only enhance our knowledge of Saturn’s largest moon but also open prospects for Titan surface and interior exploration using radar systems.

AbstractSpatio-temporal dynamics of surface water reservoirs at regional and global scales remain poorly understood. Using satellite remote sensing provides a unique opportunity to address this problem. This study aims to (1) quantify the extent and volume of surface water and (2) compare our approach with other datasets. We utilized MODIS-based spectral indices to monitor temporal variations in inundation extent. By interpolating water levels across the surface water extent, we generated water level maps and quantified surface water volume from 2000 to 2022. Evaluation against ICESat-2 data involved 64 comparisons, with approximately 58% showing an R2 value greater than or equal to 0.5, and 38% were higher than or equal to 0.7. Compared to the flooding model, our method aligns more closely with ICESat-2 data, contrary to the flooding model which tends to overestimate water levels and, consequently, water storage.

The wave energy resource potential and trends are assessed in coastal areas of the Atlantic French Façade. High-resolution satellite altimetry sea state estimates (significant wave height and backscatter coefficient) are used, taking advantage of the time and spatial coverage of ESA's CryoSat-2 mission data processed with the coastal zone SAMOSA + waveform retracker algorithm. Due to this novel retracker specifically designed for challenging regions like the coastal zone, the successful measurements of the significant wave height in the coastal zone allows us to solve previously difficult coastal issues such as land and calm water interference in the altimetry footprint. The study comprises 12 years, from January 2011 to December 2022, and applies a relatively simple empirical model to estimate the wave power density. Results are analyzed by season, showing the time of the year and location where the resource is abundant and identifying potential reserves of wave power. The highest value of the mean wave power density (27.1 kW/m) over the 12 years is found in the western sector and to the south of Belle-Île-en-mer, whereas the autumn, in which sea state conditions are less harsh for the extraction activity, appears as the most favorable season for extracting the wave resource. In conclusion, according to the estimated positive trend of wave power density, the wave resource is abundant in nearshore regions of the Atlantic French Façade and promising in view of its future exploitation. The study highlights the importance of an innovative methodology and the role of satellite data in enhancing the accuracy of wave energy assessments. • Estimation of wave renewable energy in the North Atlantic French coast. • High-resolution satellite altimetry can provide wave energy resource estimates much closer to the coast. • Satellite synthetic aperture radar altimetry is a robust tool for evaluating the prospects of wave-based renewable energy. [ABSTRACT FROM AUTHOR]

Records of Mars' climate history have been preserved by the ice-rich south polar layered deposits. An accurate knowledge of their properties is key to understanding the evolution of Mars. The combination of geophysical measurements, including gravity, altimetry and radar sounding, enables constraints on the density and composition of the south polar cap. We present a novel method that enables a thorough detection of the gravitational disturbances that are associated with lateral density variations in the ice deposits. A constrained least-squares technique is used to carry out a density inversion based on the modeling of mass concentrations, which represent local mass anomalies within the polar cap. The estimated density of the deposits varies locally in the range 850 − 1650 kg mˆ-3. A composition inversion was then carried out to investigate the volume fractions of dust, water ice, and dry ice. The local percentage of each constituent is accounted for to map out the lateral variations of the deposits composition and dielectric constant. Our results show a higher level of dust (15-30 vol%) on the west side of the deposits edge that is the boundary of the Dorsa Argentea Formation. We note that at least 80.5% of the area covered by the south polar deposits is characterized by a high concentration of water ice (≥ 50%), including areas where high basal echo power signatures were detected by the Mars Advanced Radar for Subsurface and Ionospheric Sounding. The volume of H 2 O ice in the south polar deposits is constrained to be between 1.0 × 10 6 − 1.3 × 10 6 km 3 (60 − 80 % of the total). • Novel method to characterize the lateral variations of SPLD density and composition. • The estimated densities of the deposits is between 850 and 1650 kg m−3. • The water ice covers at least 80.5% of the SPLD area and has a volume of 60%–80% of the total. • Higher level of dust is observed across the boundary of Dorsa Argentea Formation. [ABSTRACT FROM AUTHOR]

• Ice penetration impact on CryoSat-2 altimetry is examined in 257 lakes in cold area. • The average of maximum underestimation on lake levels by CryoSat-2 is ∼0.90 m. • The underestimation of lake level in Eurasia is smaller than that for North America. • The highest number of lakes with maximum level underestimation occurs in March. The CryoSat-2 satellite provides high-precision and long-term monitoring of global lake levels, offering advantages for water resource management, ecological protection, and disaster warning. However, the lake ice penetration by radar electromagnetic waves of CryoSat-2 altimetry tends to result in underestimation of water levels for lakes in high latitudes and altitudes. By contrast, the laser altimetry of ICESat-2 enables us to obtain the height measurements from lake ice surface and the ice penetration impacts on lake levels can be nearly ignored in the ICESat-2 elevation product. After converting the CryoSat-2 and ICESat-2 altimetry data to the same datum and height reference system, the water level difference of (near-) synchronous observations between the two satellites could be mainly attributed to the influences by the lake ice penetration from CryoSat-2 data. In this study, totally 257 lakes in high-latitude (north of 50°N) and high-altitude (the Tibetan Plateau, TP) regions that are covered by both CryoSat-2 and ICESat-2 satellite tracks are examined to explore the characteristics of ice penetration impacts on water level measurements. The altimetry data during unfreezing seasons (June to October) are used to correct the systematic height biases of these two satellite measurements, thus their water level differences during freezing seasons (November to May of the following year) are deemed as the influences of ice penetration on lake level measurements by CryoSat-2 radar altimetry. The results show that the maximum underestimation depth of water level for each lake varies within the range of 0.01–3.47 m, with an average of 0.90 m. Particularly in North America with a dense distribution of lakes, the underestimation of lake levels by CryoSat-2 gradually ascends with increasing latitude. CryoSat-2 underestimates lake levels in Europe and the TP less than in North America. Among different months, the lake ice leads to the maximum underestimation on the water level by CryoSat-2 altimetry in March. The spatial and temporal characteristics of lake ice impacts on the water level measurements by CryoSat-2 altimetry would be an essential reference for quantifying and reducing the uncertainties of satellite radar altimetry for monitoring inland water dynamics. [ABSTRACT FROM AUTHOR]

Ice loss from the Greenland and Antarctic ice sheets currently contributes one third of global sea level rise, yet monitoring their complex coastal regions remains a challenge. One of the principal methods for determining ice sheet imbalance is satellite radar altimetry, which provides a 30-year record of surface elevation change. Over rugged coastal topography, however, the altimeter echo returned from the ice sheet surface is often complex, with multiple distinct surface reflections degrading the accuracy of elevation measurements. Here, we present a new processing approach, termed the MultiPeak Ice (MPI) reprocessing strategy. This method is designed specifically for complex ice surfaces, where the majority of ice mass imbalance occurs, and is able to reliably retrieve multiple elevation measurements from a single altimetry echo. We apply this new approach to Sentinel-3 non-interferometric delay-Doppler altimeter echoes acquired over the Greenland Ice Sheet and demonstrate its capability to improve both the accuracy and the quantity of elevation measurements. Through comparison with coincident airborne and satellite laser altimetry we show that our MPI processing increases the number of elevation measurements by 31%, reduces the mean biases observed in conventional Level-2 processing from 4.3 m to 0.6 m, and lowers the outlier percentage (from 15% to 2%). Our new approach has the potential to extend the operational capability of non-interferometric radar altimeters over complex glaciological targets and ultimately to improve estimates of ice sheet mass imbalance. • A novel multipeak waveform retracker was developed for complex ice sheet terrain. • This significantly improves the accuracy and quantity of elevation retrievals. • This enhances the capability of SAR altimeters to track ice sheet imbalance. [ABSTRACT FROM AUTHOR]