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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mean sea surface model is updated at short wavelengths using the 30-years of sea surface slope measurements that have been archived and computed at Scripps Institution of Oceanography.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/ .

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]

• 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]

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]

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.

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]

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]

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.

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.

River stage fluctuation (RSF) is one of the most important factors influencing the physical, chemical, and ecological aspects of rivers. Despite widespread interest in river stage variations, there is currently no global benchmark of RSF and their spatial patterns. Our understanding of these characteristics remains limited. We used Sentinel‐3 altimetry data to establish a benchmark data set for RSF in wide rivers (width >1 km). We conducted an initial investigation of the spatial patterns and inter‐annual variability associated with RSF. The results show a wide range of fluctuation amplitudes spanning from a mere 1 to 18 m. Notably, rivers in semi‐arid regions exhibit more pronounced fluctuations. Further analyses indicate that human activities play a significant role in RSF. The results are of substantial interest to the scientific community, as they are closely linked to critical hydrological processes, including floods, river‐floodplain dynamics, river‐groundwater interaction, greenhouse gas emissions, and river restoration. Plain Language Summary: Rivers show a seasonal rhythm over time due to multiple processes. A critical aspect of the rhythm is the river stage, which resembles the pulse of a river as it rises and falls. Traditionally, river stages have been monitored using gauging stations. However, these local monitoring networks fall short in providing a comprehensive global perspective on river stage fluctuations, which are directly linked to significant events like floods and droughts. Advanced Earth Observation techniques now offer a means to better understand the pulse of rivers on broader scales. Specifically, satellite radar altimetry serves as a valuable tool for river stage records by measuring water surface elevation, thereby providing insights into the normality or abnormality of river conditions. This study represents one of the first global‐scale investigations into the patterns of river stage fluctuations and inter‐annual variability spanning from 2016 to 2022. Moreover, this new data set holds practical value for related studies, such as the validation of the average depth of the channel when the river is full, the assessment of river channel storage variation, the facilitation of river navigation, stepwise ecological restoration, and more. Key Points: Stage fluctuations of large rivers were estimated globally for the first time using satellite radar altimetryRivers in semi‐arid regions have larger fluctuations than those in other climate regionsThe top five river basins with the highest stage fluctuations (>7 m) are the Orinoco, Mississippi, Yangtze, Irrawaddy, and Amazon basins [ABSTRACT FROM AUTHOR]

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Sea level rise is associated with increased coastal erosion and inundation. However, the effects of sea level change on the shoreline can be enhanced or counteracted by vertical land motion and morphological processes. Therefore, knowledge about the individual contributions of sea level change, vertical land motion and morphodynamics on shoreline changes is necessary to make informed choices when applying coastal defence measures. Here, we assess the potential of remote sensing techniques to detect a geometrical relationship between sea level rise and shoreline retreat for a case study at the Terschelling barrier island at the Northern Dutch coast. First, we find that sea level observations from satellite radar altimetry retracked with ALES can represent sea level variations between 2002 and 2022 at the shoreline when the region to extract altimetry timeseries is chosen carefully. Second, results for cross-shore timeseries of satellite-derived shorelines extracted from optical remote sensing images can change considerably dependent on choices made for tidal correction and parameter settings during the computation of timeseries. While absolute shoreline positions can differ on average by more than 200 m, the average trend differences are below 1 m yr-1. Third, by intersecting the 1992 land elevation with time variable sea level, we find that inundation through sea level rise caused on average -0.3 m yr-1 of shoreline retreat between 1992 and 2022. The actual shoreline movement in this period was on average between -2.8 m yr-1 and -3.2 m yr-1, leading to the interpretation that the larger part of shoreline changes at Terschelling is driven by morphodynamics. We conclude that the combination of sea level from radar altimetry, satellite derived shorelines and land elevation provides valuable information about the influence of sea level rise, vertical land motion and morphodynamics on shoreline movements. [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 Ice Bridge (OIB) over the period 2011–2019 to investigate 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. Temporal variations in dz align with climatic events and reveal an expansion of heterogeneous firn between 2011–2013 covering an area of ~338,450 km2, followed by firn replenishment over the years 2014–2019 spanning an area of ~664,734 km2. 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]

With the success of the Sentinel‐6 Michael Freilich satellite, the satellite radar altimetry record of sea level has now surpassed 30 years in length. This reference satellite mission has continued uninterrupted alongside a significant expansion of the satellite sea‐level observing network in the past decade. This expansion was punctuated by the launch of the Surface Water and Ocean Topography mission in December 2022, which will bring higher resolution measurements of sea level closer to the shore than ever before. Here, we take stock of where we are now in terms of using satellites to measure sea level, and what is still needed to address the growing need of those living along the coast for information to support planning and adaptation efforts. Key Points: With the launch of the Sentinel‐6 MF satellite, the satellite radar altimetry record of sea level has now surpassed 30 years in lengthOther satellites have been launched—including the Surface Water and Ocean Topography mission—that complement the altimeter missionFuture missions should be targeted to provide the information that coastal communities need to prepare for rising sea levels [ABSTRACT FROM AUTHOR]

Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry‐derived sea ice thickness. During winter of the MOSAiC Expedition, the "KuKa" dual‐frequency, fully polarized Ku‐ and Ka‐band radar was deployed in "stare" nadir‐looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dual‐frequency, dual‐polarization and waveform shape, and compared to independent snow depth measurements. Novel dual‐polarization approaches yielded r2 values up to 0.77. Mean snow depths agreed within 1 cm, even for data sub‐banded to CryoSat‐2 SIRAL and SARAL AltiKa bandwidths. Snow depths from co‐polarized dual‐frequency approaches were at least a factor of four too small and had a r2 0.15 or lower. r2 for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters. Plain Language Summary: Data collected using a surface‐based radar instrument on sea ice during the MOSAiC Arctic expedition were used to develop new techniques to estimate the depth of the overlying snow. We used different polarizations of the radiation to detect the depths of the upper and lower snow surfaces, and subtracted them to give snow depth. These depths agreed well with an independently collected snow depth data set. Estimates of snow depth using two different radar frequencies were less accurate, whilst using information of the shape of the returning pulse of radiation also showed a relationship with the independent snow depths, though not as strong as the polarization method. These results indicate that polarimetry (using a new satellite mission) and/or waveform shape (using existing missions) could be used to estimate snow depth on sea ice from airborne or satellite platforms. Key Points: Novel polarization‐based snow depth estimation techniques were developed using surface‐based Ku‐ and Ka‐band polarimetric radar altimeter dataThe dominant scattering surface was the air/snow and snow/ice interface in co‐ and cross‐polarized data, respectively, at both frequenciesRadar‐derived snow depths agreed with independent measurements, with r2 up to 0.77 and accuracy of 1 cm for best‐performing techniques [ABSTRACT FROM AUTHOR]

In recent decades, water availability, water use, water sharing and freshwater supply for basic human and economic needs have become central scientific and humanitarian issues. With increasing water scarcity in many regions and increasing frequency of extreme flooding in other regions, there is a need to improve predictive capacity, to collect a large amount of information on key hydrological variables such as flows or water stocks in lakes and floodplains and to best combine these data with hydrological and hydrodynamic models. Most of the world's water demand relies on continental surface waters (rivers, lakes, wetlands and artificial reservoirs) while less on underground aquifers and seawater desalination. However, ground-based hydrological survey networks have steadily and drastically decreased worldwide over the last decades. In this context, current remote sensing techniques have been widely used by several countries for water resource monitoring purposes. In this paper, we present such remote sensing techniques, in particular satellite altimetry and imagery, and discuss how they became essential for the study of the water cycle and hydrological phenomena on a broad range of spatial and temporal scales. Large lakes, rivers and wetlands play a major role in the global water cycle and are also markers, integrators and actors of climate change at work on Earth. We show several examples chosen from the literature that perfectly highlight both current scientific and societal issues, as well as the crucial role of space techniques to monitor terrestrial surface waters. [ABSTRACT FROM AUTHOR]

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 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.

Accurate bathymetry estimation is made possible by combining depth data with free-air gravity anomalies on the sea surface recovered from the geoidal heights that are equivalent to the mean sea surface derived from satellite radar altimetry. The residual gravity anomalies that represent the short-wavelength effect are required to accurately estimate bathymetry by combining satellite altimetry-derived free-air gravity anomalies and shipborne data including depth and gravity anomalies. In this study, the optimized ensemble model of machine learning techniques was applied to the residual gravity anomalies to estimate bathymetry by the gravity--geologic method (GGM) from various geospatial information including shipborne depth, shipborne gravity anomalies, and satellite altimetry-derived free-air gravity anomalies, in the Ulleung Basin in the East Sea. From the results, the GGM bathymetry predicted using the optimized ensemble model of machine learning was improved by 32.3 m over the GGM bathymetry estimated using the original depth and gravity anomalies. The method presented in this study is for estimating deep-water bathymetry using machine learning, and it has been proven to have superior performance compared with conventional methods. [ABSTRACT FROM AUTHOR]

Wave-affected marginal ice zone (MIZ) is an integral part of the sea ice cover and key to the atmosphere-ice-ocean interaction in the polar region. While we mainly rely on in-situ campaigns for studying MIZs, great challenges still exist for the remote sensing of the MIZs by satellites. In this study we develop a novel retrieval algorithm for wave-affected MIZs based on the delay-Doppler radar altimeter onboard CryoSat-2 (CS2). CS2 waveform power and the waveform stack statistics are used to determine the part of the 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. As indicated by the MIZ record, no significant change of either the mean MIZ width or the extreme width is detected, although large temporal and spatial variability is present. In particular, extremely wide MIZs (over 300 km) are observed in the Barents Sea, while in other part of the Atlantic Arctic, MIZs are generally narrower. We also compare the CS2-based retrieval with those 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 MIZ yields systematically narrower MIZs than CS2, and there is no statistically significant correlation between the two. Besides CS2, the proposed retrieval algorithm can be adapted for various historical and future radar altimetry campaigns. The synergy of multiple satellites can further improve the spatial and temporal representation of the altimeters' observation of the MIZs.c [ABSTRACT FROM AUTHOR]

We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed. Plain Language Summary: Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type. Key Points: Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missionsTrusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐termBenchmarking allows to include more GPS stations in hydrogeodetic analyses [ABSTRACT FROM AUTHOR]

In this study, a new method to assimilate freeboard (FB) derived from satellite radar altimetry is presented with the goal of improving the initial state of sea ice thickness predictions in the Arctic. In order to quantify the improvement in sea ice thickness gained by assimilating FB, we compare three different model runs: one reference run (refRun), one that assimilates only sea ice concentration (SIC) (sicRun), and one that assimilates both SIC and FB (fbRun). It is shown that estimates for both SIC and FB can be improved by assimilation, but only fbRun improved the FB. The resulting sea ice thickness is evaluated by comparing sea ice draft measurements from the Beaufort Gyre Exploration Project (BGEP) and sea ice thickness measurements from 19 ice mass balance (IMB) buoys deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The sea ice thickness of fbRun compares better than refRun and sicRun to the longer BGEP observations more poorly to the shorter MOSAiC observations. Further, the three model runs are compared to the Alfred Wegener Institute (AWI) weekly CryoSat-2 sea ice thickness, which is based on the same FB observations as those that were assimilated in this study. It is shown that the FB and sea ice thickness from fbRun are closer to the AWI CryoSat-2 values than the ones from refRun or sicRun. Finally, comparisons of the abovementioned observations and both the fbRun sea ice thickness and the AWI weekly CryoSat-2 sea ice thickness were performed. At the BGEP locations, both fbRun and the AWI CryoSat-2 sea ice thickness perform equally. The total root-mean-square error (RMSE) at the BGEP locations equals 30 cm for both sea ice thickness products. At the MOSAiC locations, fbRun's sea ice thickness performs significantly better, with a total 11 cm lower RMSE. [ABSTRACT FROM AUTHOR]

The volcanic Kerguelen Islands are formed on one of the world's largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the Cretaceous history of the continents. This is reflected in the varying age of the oceanic crust adjacent to the plateau and the highly heterogeneous bathymetry of the Kerguelen Plateau, with seafloor structure differing for the southern and northern segments. Remote sensing data derived from marine gravity and satellite radar altimetry surveys serve as an important source of information for mapping complex seafloor features. This study incorporates geospatial information from NOAA, EMAG2, WDMAM, ETOPO1, and EGM96 datasets to refine the extent and distribution of the extracted seafloor features. The cartographic joint analysis of topography, magnetic anomalies, tectonic and gravity grids is based on the integrated mapping performed using the Generic Mapping Tools (GMT) programming suite. Mapping of the submerged features (Broken Ridge, Crozet Islands, seafloor fabric, orientation, and frequency of magnetic anomalies) enables analysis of their correspondence with free-air gravity and magnetic anomalies, geodynamic setting, and seabed structure in the southwest Indian Ocean. The results show that integrating the datasets using advanced cartographic scripting language improves identification and visualization of the seabed objects. The results include 11 new maps of the region covering the Kerguelen Plateau and southwest Indian Ocean. This study contributes to increasing the knowledge of the seafloor structure in the French Southern and Antarctic Lands. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the applicability conditions for the significant wave height (SWH) measurement approach based on measuring the cross-correlation function of two signals with similar frequencies reflected by the sea surface in the bistatic problem statement (the transmitting antenna and the receiving antenna are separated in space). When implementing this approach, the modulus of the normalized cross-correlation function for several pairs of signals with different frequency bases will be measured in the experiment. The advantage of this approach over the traditional method for radar altimetry, based on the analysis of the shape of the reflected pulse, is the high accuracy in measuring the SWH for weak waves. In the bistatic formulation of the problem, an important advantage of the approach under study is the possibility of obtaining analytical formulas for solving the direct problem. This paper presents the derivation of a formula for the modulus of the normalized cross-correlation function of reflected signals, which expresses an explicit relationship with the parameters of sea waves and the measurement geometry in the bistatic formulation of the problem. This paper considers the influence on the modulus of the normalized cross-correlation function of the antenna patterns of the transmitting and receiving antennas, the distances to the sea surface, the wave slope variances, the SWH and the frequency base of the transmitted signals. The optimal variants of the measurement scheme are discussed. The results and conclusions obtained can be easily expanded to underwater acoustic sounding. [ABSTRACT FROM AUTHOR]

More than 30 years of observations from an international suite of satellite altimeter missions continue to provide key data enabling research discoveries and a broad spectrum of operational and user-driven applications. These missions were designed to advance technologies and to answer scientific questions about ocean circulation, ocean heat content, and the impact of climate change on these Earth systems. They are also a valuable resource for the operational needs of oceanographic and weather forecasting agencies that provide information to shipping and fishing vessels and offshore operations for route optimization and safety, as well as for other decision makers in coastal, water resources, and disaster management fields. This time series of precise measurements of ocean surface topography (OST)—the "hills and valleys" of the ocean surface—reveals changes in ocean dynamic topography, tracks sea level variations at global to regional scales, and provides key information about ocean trends reflecting climate change in our warming world. Advancing technologies in new satellite systems allows measurements at higher spatial resolution ever closer to coastlines, where the impacts of storms, waves, and sea level rise on coastal communities and infrastructure are manifest. We review some collaborative efforts of international space agencies, including NASA, CNES, NOAA, ESA, and EUMETSAT, which have contributed to a collection of use cases of satellite altimetry in operational and decision-support contexts. The extended time series of ocean surface topography measurements obtained from these satellite altimeter missions, along with advances in satellite technology that have allowed for higher resolution measurements nearer to coasts, has enabled a range of such applications. The resulting body of knowledge and data enables better assessments of storms, waves, and sea level rise impacts on coastal communities and infrastructure amongst other key contributions for societal benefit. Although not exhaustive, this review provides a broad overview with specific examples of the important role of satellite altimetry in ocean and coastal applications, thus justifying the significant resource contributions made by international space agencies in the development of these missions. [ABSTRACT FROM AUTHOR]

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changes in weather, season, climate and ice dynamics. Yet current Digital Elevation Models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. We here present four 500-meter resolution annual (2019-2022) summer DEMs of the Greenland ice sheet marginal zone (PRODEMs). The PRODEMs cover 50km wide band from the ice edge, and they capture all outlet glaciers of the Greenland ice sheet. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using a regionally-varying Kriging method. They are validated using leave-one-out cross-validation, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties, which have a median value of 1.4m. We observe a general lowering of surface elevations compared to ArcticDEM, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs will enable studies of the marginal ice sheet elevation changes in great detail, temporally as well as spatially. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions. Incorporating the PRODEM surface elevations in estimates of the solid ice discharge from Greenland outlet glaciers will e.g. improve our assessment of the mass balance of the Greenland ice sheet and its interannual variability. PRODEMs from summers 2019 through 2022 are available at https://doi.org/10.22008/FK2/52WWHG (Winstrup, 2023), and we plan to annually update the product henceforth. [ABSTRACT FROM AUTHOR]

The spatio-temporal variation of surface water storage (SWS) in the Congo River basin (CRB), the second-largest watershed in the world, remains widely unknown. In this study, satellite-derived observations are combined to estimate SWS dynamics at the CRB and sub-basin scales over 1992–2015. Two methods are employed. The first one combines surface water extent (SWE) from the Global Inundation Extent from Multi-Satellite (GIEMS-2) dataset and the long-term satellite-derived surface water height from multi-mission radar altimetry. The second one, based on the hypsometric curve approach, combines SWE from GIEMS-2 with topographic data from four global digital elevation models (DEMs), namely the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Observing Satellite (ALOS), Multi-Error-Removed Improved Terrain (MERIT), and Forest And Buildings removed Copernicus DEM (FABDEM). The results provide SWS variations at monthly time steps from 1992 to 2015 characterized by a strong seasonal and interannual variability with an annual mean amplitude of ∼101±23 km 3. The Middle Congo sub-basin shows a higher mean annual amplitude (∼71±15 km 3). The comparison of SWS derived from the two methods and four DEMs shows an overall fair agreement. The SWS estimates are assessed against satellite precipitation data and in situ river discharge and, in general, a relatively fair agreement is found between the three hydrological variables at the basin and sub-basin scales (linear correlation coefficient >0.5). We further characterize the spatial distribution of the major drought that occurred across the basin at the end of 2005 and in early 2006. The SWS estimates clearly reveal the widespread spatial distribution of this severe event (∼40 % deficit as compared to their long-term average), in accordance with the large negative anomaly observed in precipitation over that period. This new SWS long-term dataset over the Congo River basin is an unprecedented new source of information for improving our comprehension of hydrological and biogeochemical cycles in the basin. As the datasets used in our study are available globally, our study opens opportunities to further develop satellite-derived SWS estimates at the global scale. The dataset of the CRB's SWS and the related Python code to run the reproducibility of the hypsometric curve approach dataset of SWS are respectively available for download at 10.5281/zenodo.7299823 and 10.5281/zenodo.8011607 (Kitambo et al., 2022b, 2023). [ABSTRACT FROM AUTHOR]

Sea ice volume's significant interannual variability requires long-term series of observations to identify trends in its evolution. Despite improvements in sea ice thickness estimations from altimetry during the past few years thanks to CryoSat-2 and ICESat-2, former ESA radar altimetry missions such as the Environmental Satellite (Envisat) and especially the European Remote-Sensing Satellite (ERS-1 and ERS-2) have remained under-exploited so far. Although solutions have already been proposed to ensure continuity of measurements between CryoSat-2 and Envisat, there is no time series integrating ERS. The purpose of this study is to extend the Arctic radar freeboard time series back to 1995. The difficulty in handling ERS measurements comes from a technical issue known as the pulse blurring effect, altering the radar echoes over sea ice and the resulting surface height estimates. Here we present and apply a correction for this pulse blurring effect. To ensure consistency of the CryoSat-2, Envisat and ERS-2 time series, a multiparameter neural-network-based method to calibrate Envisat against CryoSat-2 and ERS-2 against Envisat is presented. The calibration is trained on the discrepancies observed between the altimeter measurements during the mission-overlap periods and a set of parameters characterizing the sea ice state. Monthly radar freeboards are provided with uncertainty estimations based on a Monte Carlo approach to propagate the uncertainties all along the processing chain, including the neural network. Comparisons of corrected radar freeboards during overlap periods reveal good agreement between the missions, with a mean bias of 0.30 cm and a standard deviation of 9.7 cm for Envisat and CryoSat-2 and a 0.20 cm bias and a standard deviation of 3.8 cm for ERS-2 and Envisat. The monthly corrected radar freeboards obtained from Envisat and ERS-2 are then validated by comparison with several independent datasets such as airborne, mooring, direct-measurement and other altimeter products. Except for two datasets, comparisons lead to correlations ranging from 0.41 to 0.94 for Envisat and from 0.60 to 0.74 for ERS-2. The study finally provides radar freeboard estimation for winters from 1995 to 2021 (from the ERS-2 mission to CryoSat-2). [ABSTRACT FROM AUTHOR]

A new mean sea surface (MSS) was determined by focusing on the accuracy provided by exact-repeat altimetric missions (ERM) and the high spatial coverage of geodetic (or drifting) missions. The goal was to obtain a high-resolution MSS that would provide centimeter-level precision. Particular attention was paid to the homogeneity of the oceanic content of this MSS, and specific processing was also carried out, particularly on the data from the geodetic missions. For instance, CryoSat-2 and SARAL/AltiKa data sampled at high frequencies were enhanced using a dedicated filtering process and corrected from oceanic variability using the results of the objective analysis of sea-level anomalies provided by DUACS multi-missions gridded sea-level anomalies fields (MSLA). Particular attention was also paid to the Arctic area by combining traditional sea-surface height (SSH) with the sea levels estimated within fractures in the ice (leads). The MSS was determined using a local least-squares collocation technique, which provided an estimation of the calibrated error. Furthermore, our technique takes into account altimetric noises, ocean-variability-correlated noises, and along-track biases, which are determined independently for each observation. Moreover, variable cross-covariance models were fitted locally for a more precise determination of the shortest wavelengths, which were shorter than 30 km. The validations performed on this new MSS showed an improvement in the finest topographic structures, with amplitudes exceeding several cm, while also continuing to refine the correction of the oceanic variability. Overall, the analysis of the precision of this new CNES_CLS 2022 MSS revealed an improvement of 40% compared to the previous model, from 2015. [ABSTRACT FROM AUTHOR]

Radar altimetry has been used to monitor sea level changes and ice sheet elevation changes for decades. Over mountain glaciers, radar altimetry has limited applications due to contaminated waveforms caused by complex glacier surfaces and steep terrains. In this study, we develop a glacier‐threshold method (GTM) to determine glacier elevation changes in Alaska and Yukon. The GTM retracks waveforms, reduces terrain effect and detects invalid elevation observations from the TOPEX/Poseidon (T/P) and Jason‐2 (J2) altimeters, resulting in an average usable rate of 35% from original altimeter‐measured heights. The selected measurements are used to construct time series of glacier elevation changes over 1993–2002 (T/P) and 2008–2016 (J2) at 47 sites. A crossover analysis, validation by airborne laser altimetry observations, and comparisons with recent studies confirm the estimated glacier elevation changes. Our findings suggest that the thinning of glaciers in Alaska and Yukon has been ubiquitous in recent years. The site near Walsh Glacier has the highest thinning rate of −5.71 ± 0.09 m/yr, followed by Chitina Glacier at −4.51 ± 0.21 m/yr. Only 17% of sites show glacier thickening due to surges and mass accumulations. Using a sophisticated data processing algorithm like the GTM, we show that altimeter data from the repeat TOPEX‐Jason missions can be used to monitor long‐term glacier elevation changes at inaccessible spots, creating an additional value for altimeter missions originally purposed for monitoring long‐term sea level change. Plain Language Summary: Satellite radar altimetry is an important observation technology to determine changes in surface elevations. However, altimeter measurement accuracy is very sensitive to terrain complexity, especially over mountain glaciers. Here, we present a glacier‐threshold method (GTM) to investigate the glacier elevation changes in Alaska and Yukon, using TOPEX/Poseidon (T/P) and Jason‐2 (J2) altimeter measurements. Internal and external measurement assessments show that the GTM enables us to retrieve precise changes in glacier elevations and improve the usable rate of original radar elevation observations. During the recent study period, the vast majority of Alaska and Yukon glaciers' elevations are rapidly declining. But in fewer glacier accumulation areas and over glaciers with active surface processes, the glacier elevations are rising. Environmental factors analysis shows that Pacific decadal oscillation, temperature, precipitation, surges, altitudes and locations of glaciers are responsible for the asynchronously spatiotemporal glacier elevation changes. All these findings from the repeat‐track radar altimetry and the GTM help to improve our knowledge about Alaska and Yukon glacier processes. Key Points: Glacier‐threshold method retrieves Alaska and Yukon glacier elevation changes using approximately 35% of repeated altimeter measurementsAlaska and Yukon have recently experienced notable glacier thinning, with the highest rate of −5.71 ± 0.09 m/yr near Walsh GlacierPacific decadal oscillation, surges, altitudes, and glacier locations affect Alaska and Yukon glacier elevation change pattern [ABSTRACT FROM AUTHOR]

Over the last few decades, satellite radar altimetry has developed enabling a wide range of applications, including the monitoring of lakes. As a method to measure lake water level time series, satellite radar altimetry contributes to gaps in data of in-situ networks in time and space, which is freely available, continuous, global, regular, and precise. However, depending on the location, shape, size, and surrounding environment of the lakes, the accuracy of water heights inferred from altimeters varies significantly. The accuracy of water heights also strongly depends on the quality of space-born instruments, with modern models having evolved from radar altimeters launched in the 1990 s. To determine the level of accuracy of radar altimeters, it is necessary to use ground observations of lake heights. However, the measurements performed onboard by altimeters and on the ground by water level gauges are not directly comparable because the physical properties and scaling of the measurements are completely different. In this study, we present an approach which permits realistic inter-comparison of water levels, in relation to a large lake with a large number of hydrological stations (at least 10) and the presence of at least 10 satellite measurements per month (on the example of lake Baikal), in order to provide diagnostics on the quality of the radar altimeter and statistics of the errors. [ABSTRACT FROM AUTHOR]

Objectives: Backscatter coefficient (σ 0) is one of observations of satellite radar altimetry, which is widely used in the processes of surface state monitoring, snow thickness inversion, data calibration and verification of satellite altimeters, and other fields. The geophysical data record data of Jason-2 is used to extract and isolate the Ku-band σ 0 data of the Tibetan Plateau (TP). Methods: Taking the GlobeLand30 2020 version data as the basis for surface classification, σ 0 is given surface attributes by latitude and longi‑ tude data. And we obtain the time-varying sequences of σ 0 under different types of surface features from De‑ cember 2008 to September 2016. The singular spectrum analysis principle is used to extract the σ 0 time change trend and period information, and the period results are analyzed by fast Fourier transform. Results: The results show that the σ 0 is higher in waters and wetland areas, and is lower in permanent snow and ice areas. There are multiple period signals of σ 0 in the TP. Conclusions: The surface properties of the artificial surfaces, bare land, and shrubland area are stable, and the annual σ 0 change is not significant. The other re‑ gions have significant annual and semi-annual cycles of σ 0 variability, and the amplitude of variability is not consistent across regions, with different regions corresponding to different changes in σ 0 trends. [ABSTRACT FROM AUTHOR]