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Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This letter examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10-km2 island in the northwestern Mediterranean). Forty-six repeat passes were analyzed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly, one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modeling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges but also greatly enhance the study of storm surges and other coastal phenomena.

Just as CryoSat-2, Sentinel-3 embarks on board a radar altimeter (SRAL) with the novel Synthetic Aperture Radar (SAR) mode that enables higher resolution and more accurate altimeter-derived parameters in the coastal zone, thanks to the reduced along-track footprint. Exploiting the SAR data in the recent years, many researchers have already proven that the performance of SAR altimetry with specific coastal retrackers is superior to collocated Pseudo-Low Resolution Mode (PLRM) coastal altimetry algorithms but they also pointed out that residual errors due to land contamination are still present in the very proximity of the land (0–3 km). The objective of this work is to further improve these results by exploiting extra information provided by SAR altimeters, namely the so-called Range Integrated Power (RIP), the new waveform built by a simple integration of the Doppler beams in the range direction. The RIP characterizes the backscattering state of the ground cell, towards which all the Doppler beams have been steered. These developments lead to a new retracker, here coined SAMOSA++, in which the RIP, as computed from the L1B-S data, is converted into a surface backscattering profile and directly integrated in the SAMOSA retracker as part of the model formulation itself. In this way, the modified SAMOSA model is automatically and autonomously able to cope with the different return waveform shapes from different surface types: either diffusive or specular. The mean square slope computed from the RIP is also estimated, representing a new output of the retracker. The performance of this new retracker is here cross-compared against its previous version, SAMOSA+, and against the standard Sentinel-3 marine PDGS (Payload Data Ground Segment) SAR retracker (SAMOSA2) in both coastal zone and open ocean in order to ensure a seamless transition between these zones. The new retracker SAMOSA++ is validated in the North East Atlantic region, where appropriate in situ validation data are available. The retrievals from the new retracker are cross-compared against the network of tide gauges and buoys in the German Bight and versus the output of the GCOAST Helmholtz-Zentrum Geesthacht (HZG) regional circulation and wave model. In addition, sea level estimates derived with different ocean tide and wet path delay geophysical correction models are compared. Results indicate that in this region the best geophysical correction models are the FES2014b tide model and the GPD+ wet tropospheric correction that incorporates data from the Sentinel-3 on-board radiometer. Analyses show that both SAMOSA+ and SAMOSA++ ensure the continuity of the PDGS SAR Marine retracker in the open ocean, leading to clear improvements in the coastal zone, larger for SAMOSA++ than for SAMOSA+. In summary, the new SAMOSA++ retracker retrieves more accurate altimetric parameters in the coastal zone, with a better consistency with respect to regional ocean models and in situ data.

As the first satellite altimetry mission operating in sar (delay-Doppler) mode, CryoSat-2 is an interesting mission to analyze its performance for water level monitoring over inland water bodies. It offers the opportunity to make comparison of sar and conventional altimeters by a multi-mode altimeter mounted on the same platform with a long repeat orbit. This comparison gives us more knowledge about the performance of the sar altimeter. Even tough it is not possible to perform it over same objects. In this paper we analyze the CryoSat-2 performance for water level monitoring via full- and sub-waveform retracking against in-situ gauge and L2 products of other satellite altimetry missions, e.g. Envisat and Jason-2. To this end, we retrack the full-waveforms and sub-waveforms with different empirical and physical retracking algorithms such as ocog , threshold, β -parameters and samosa 3. We evaluate its capability in all measurement modes, i.e. lrm , sar and sari n, over inland water bodies located in different climatic zones. We selected study areas with different shapes and sizes. Relative to in situ measurements we find a precision of the CryoSat-2 lrm mode of 15 cm rms over Qinghai lake (China) and 13 cm over Erie lake ( usa ). This is an improvement over Envisat, yielding precision of 17 cm in both cases. For the sar mode over Neagh lake (Northern Ireland) and Derg lake (Ireland) we obtain 15 cm and 13 cm where Envisat yields 28 cm and 100 cm , respectively. The sari n mode’s precision is assessed over Nasser lake (Egypt) with 25 cm rms and Athabasca lake (Canada) with 16 cm . Over these lakes Jason-2 achieved 54 cm and Envisat 19 cm , respectively. The most precise results of CryoSat-2 are obtained with our retracking and sub-waveform selection scenarios. Comparing CryoSat-2 results from our retracking scenarios using L1b data with those results obtained from L2 products (data) of this mission shows an improvement of 4–17 cm. The minimum and maximum improvements belong to Erie and Derg lakes respectively, the largest and smallest lakes. From the waveform analysis over lakes with different shapes and sizes, we found that the first and the mean-all sub-waveforms (mean correction from all sub-waveforms) retracked with the threshold and samosa 3 (only for sar mode) retrackers are appropriate to retrieve water level variation of small lakes and complex shaped lakes in this study. Over large lakes the full-waveform retracking leads to better results. In the case of icy-lake objects, sub-waveform retracking scenarios (the first and mean-all sub-waveforms) are more precise than the other scenarios. These are our findings over few samples, though more samples need to be analyzed to support them strongly.

We present results of contemporary coastal sea level changes along the coasts of Western Africa, obtained from a dedicated reprocessing of satellite altimetry data done in the context of the ESA ‘Climate Change Initiative’ sea level project. High sampling rate (20 Hz) sea level data from the Jason-1 and Jason-2 missions over a 14-year-long time span (July 2002 to June 2016) are considered. The data were first retracked using the ALES adaptative leading edge subwaveform retracker. The X-TRACK processing system developed to optimize the completeness and accuracy of the corrected sea level time series in coastal ocean areas was then applied. From the 14-year long sea level time series finally obtained, we estimate sea level trends along the Jason-1 & 2 tracks covering the study region. We analyze regional variations in sea level trends, with a focus on the changes observed between the open ocean to the coastal zone. Compared to the conventional 1 Hz sea level products dedicated to open ocean applications, the retracked 20 Hz measurements used in this study allow us to retrieve valid sea level information much closer to the coast (less than 3–4 km to the coast, depending on the satellite track location). The main objective of this study is twofold: (1) provide sea level products in the coastal areas from reprocessed altimetry data and (2) check whether sea level changes at the coast differ from that reported in the open ocean with conventional altimetry products. In the selected region, results show that over the study period, sea level trends observed near the coast of Western Africa are significantly different than offshore trends. In order to assess the robustness of the results, detailed analyses are performed at several locations to discriminate between possible drifts in the geophysical corrections and physical processes potentially able to explain the sea level changes observed close to the coast.

Sentinel-3 is a multi-instrument mission designed to measure sea-surface topography, sea- and land-surface temperature, ocean color and land color with high resolution and accuracy. The S3 mission is based on a constellation of two (3A and 3B) polar-orbiting satellites and it is designed and operated in the framework of the Copernicus programme, with planned 3C and 3D to ensure continuity. The mission builds up the legacy of ERS-1, ERS-2, ENVISAT and particularly CryoSat for the altimeter. Seninel-3A was launched in February 2016 and Seninel-3B in April 2018. They are equipped with a dual-frequency (Ku- and C-band) altimeter and can work both in low resolution (LRM) and SAR mode, the latter being designed to achieve high along-track discrimination. The low-resolution mode exploits conventional pulse-limited altimeter operation at C band. To approximate LRM operation at Ku band, a pseudo low-resolution mode is achieved by properly processing SAR acquisitions. Recently, a new research project funded by the European Space Agency, i.e., ALtimetry for BIOMass (ALBIOM), has been initiated to study the possibility of deriving forest biomass using Sentinel-3 altimetry data. ALBIOM aims at improving biomass global dataset, which is defined and classified as an Essential Climate Variable. In the last two decades, the exploitation of radar altimetry for studying land parameters has received renewed interest, including processing for the characterization of vegetation features and soil moisture. The vegetation cover has two main effects on the nadir backscatter measured by the altimeter. It attenuates the coherent reflection of the soil and add an incoherent volume scattering contribution. The relative weight of the two contributions depends of course form the frequency. To assess in what extent radar altimetry data are sensitive to the presence of vegetation forest, a study of the dynamic of the Sentinel-3 power waveforms with respect to the above ground biomass is needed. More importantly, the way radar waveforms are affected by disturbing land parameters, such as soil moisture, topography and surface roughness, has to be understood. In this work, an analysis considering both high- and low-resolution data made available by the Copernicus hub service is carried out. The sensitivity study of Sentinel-3 altimetry data to forest biomass over Africa is based on calibrated Sentinel-3 waveforms combined in space and time with forest biomass maps and ancillary information on the soil topography derived from a Digital Elevation Model. Comparison among Ku- and C-band waveforms are discussed, highlighting the critical aspect of the correct positioning of the time-tracking window over land, which often appears partly or completely misplaced, determining waveforms either truncated or containing noise only. The detrimental effect of the waveform truncation for the estimation of biomass and the possible mitigation approach has been considered. The study revealed that both waveforms and NRCSs can be sensitive to the presence of biomass in the order of 100-400 tons/ha, even if they can be strongly influenced by the presence of irregular topography within the system footprint. Different sensitivities with respect to the three channels (i.e., bandwidths and resolution modes) have been observed. A study about the use of differential NRCSs, defined as the difference between two different bandwidths, proposed by previous studies, is under investigation. Further research activities also connected to a modelling approach are in progress and will be discussed at the conference.

The Earth energy imbalance (EEI) at the top of the atmosphere is responsible for the accumulation of heat in the climate system. Monitoring the EEI is therefore necessary to better understand the Earth's warming climate. Measuring the EEI is challenging as it is a globally integrated variable whose variations are small (0.5–1 W m−2) compared to the amount of energy entering and leaving the climate system (∼340 W m−2). Since the ocean absorbs more than 90 % of the excess energy stored by the Earth system, estimating the ocean heat content (OHC) change provides an accurate proxy of the EEI. This study provides a space geodetic estimation of the OHC changes at global and regional scales based on the combination of space altimetry and space gravimetry measurements. From this estimate, the global variations in the EEI are derived with realistic estimates of its uncertainty. The mean EEI value is estimated at +0.74±0.22 W m−2 (90 % confidence level) between August 2002 and August 2016. Comparisons against estimates based on Argo data and on CERES measurements show good agreement within the error bars of the global mean and the time variations in EEI. Further improvements are needed to reduce uncertainties and to improve the time series, especially at interannual timescales. The space geodetic OHC-EEI product (version 2.1) is freely available at https://doi.org/10.24400/527896/a01-2020.003 (Magellium/LEGOS, 2020).

ALtimetry for BIOMass (ALBIOM) is a research project funded by the European Space Agency to study the possibility of estimating above ground biomass by means of low- and high-resolution Sentinel-3 altimetry data. We present preliminary results of a sensitivity analysis, developed to assess in what extent waveforms and altimetry observables are affected by the presence of forests. Ku- and C-band altimetry data have been collected and processed to properly select well-tracked waveforms over land, which are then related to collocated biomass data. A statistical analysis has been performed, highlighting a sensitivity of the estimated normalized radar cross section with respect to forest biomass, even though it is strongly disturbed by the soil topography within the radar footprint. Additionally, the inaccurate positioning of the time-tracking window limits the number of useful data.

The launch of Sentinel-3A in February 2016 represented the beginning of a new long-term series of operational satellite radar altimeters, which will provide Delay-Doppler altimetry measurements over ice sheets for decades to come. Given the potential benefits that these satellites can offer to a range of glaciological applications, it is important to establish their capacity to monitor ice sheet elevation and elevation change. Here, we present the first analysis of Sentinel-3 Delay-Doppler altimetry over the Antarctic ice sheet, and assess the accuracy and precision of retrievals of ice sheet elevation across a range of topographic regimes. Over the low-slope regions of the ice sheet interior, we find that the instrument achieves both an accuracy and a precision of the order of 10 cm, with ∼98 % of the data validated being within 50 cm of co-located airborne measurements. Across the steeper and more complex topography of the ice sheet margin, the accuracy decreases, although analysis at two coastal sites with densely surveyed airborne campaigns shows that ∼60 %–85 % of validated data are still within 1 m of co-located airborne elevation measurements. We then explore the utility of the Sentinel-3A Delay-Doppler altimeter for mapping ice sheet elevation change. We show that with only 2 years of available data, it is possible to resolve known signals of ice dynamic imbalance and to detect evidence of subglacial lake drainage activity. Our analysis demonstrates a new, long-term source of measurements of ice sheet elevation and elevation change, and the early potential of this operational system for monitoring ice sheet imbalance for decades to come.

The scope of this presentation is to feature and provide an update on the ESA G-POD/SARvatore family of altimetry services portfolio for the exploitation of CryoSat-2 and Sentinel-3 data from L1A (FBR) data products up to SAR/SARin Level-2 geophysical data products. At present, the following on-line & on-demand services compose the portfolio:- The SARvatore (SAR Versatile Altimetric TOolkit for Research & Exploitation) for CryoSat-2 and Sentinel-3 services developed by the Altimetry Team in the R&D division at ESA-ESRIN. These processor prototypes are versatile and allow the users to customize and adapt the processing at L1b & L2 according to their specific requirements by setting a list of configurable options. The scope is to provide users with specific processing options not available in the operational processing chains (e.g. range walk correction, stack sub-setting, extended receiving window, zero padding, high-posting rate and burst weighting at L1b & SAMOSA+, SAMOSA++ and ALES+ SAR retrackers at L2). AJoin & Share Forum (https://wiki.services.eoportal.org/tiki-custom_home.php) allows users to post questions and report issues. A data repository is also available to the Community to avoid the redundant reprocessing of already processed data (https://wiki.services.eoportal.org/tiki-index.php?page=SARvatore+Data+Repository&highlight=repository).- The TUDaBo SAR-RDSAR (Technical University Darmstadt – University Bonn SAR-Reduced SAR) for CryoSat-2 and Sentinel-3 service. It allows users to generate reduced SAR, unfocused SAR & LRMC data. Several configurable L1b & L2 processing options and retrackers (BMLE3, SINC2, TALES, SINCS) are available. The processor will be extended during an additional activity related to the ESA HYDROCOASTAL Project (https://www.satoc.eu/projects/hydrocoastal/) to account in the open ocean for the vertical motion of the wave particles (VMWP) in unfocused SAR and in a simplified form of the fully focused SAR called here Low Resolution Range Cell Migration Correction-Focused (LRMC-F). - The ALES+ SAR for CryoSat-2 and Sentinel-3 service. It allows users to process official L1b data and produces L2 NetCDF products by applying the empirical ALES+ SAR subwaveform retracker, including a dedicated SSB solution, developed by the Technische Universität München in the frame of the ESA Sea Level CCI (http://www.esa-sealevel-cci.org/) & BALTIC+ SEAL Projects (http://balticseal.eu/).- The Aresys Fully Focused SAR for CryoSat-2 service. Currently under development, it will provide the capability to produce CS-2 FF-SAR L1b products thanks to the Aresys 2D transformed frequency domain AREALT-FF1 processor prototype. Output products will also include geophysical corrections and threshold peak & ALES-like subwaveform retracker estimates.The G-POD graphical interface allows users to select, in all the services, a geographical area of interest within the time-frame related to the L1A (FBR) & L1b data products availability in the service catalogue. After the task submission, users can follow, in real time, the status of the processing. The output data products are generated in standard NetCDF format, therefore being compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info) and typical tools.Services are open, free of charge (supported by ESA) for worldwide scientific applications and available, after registration and activation (to be requested for each chosen service to eo-gpod@esa.int), at https://gpod.eo.esa.int.

Climate-related sea level changes in the world coastal zones result from the superposition of the global mean rise due to ocean warming and land ice melt, regional changes mostly caused by non-uniform ocean thermal expansion and salinity changes, and small-scale coastal processes (e.g., shelf currents, wind & waves changes, fresh water input from rivers, etc.). So far, satellite altimetry has provided global gridded sea level time series up to 10-15 km to the coast only, preventing estimation of sea level changes very close to the coast. In the context of the ESA Climate Change Initiative coastal sea level project, we have developed a complete reprocessing of high-resolution (20 Hz) Jason-1, 2 and 3 altimetry data along the world coastal zones using the ALES (Adaptative Leading Edge Subwaveform) retracker combined with the XTRACK system dedicated to improve geophysical corrections at the coast. Here we present coastal sea level trends over the period 2002-2020 along the whole African continent. Different coastal sea level trend behaviors are observed over the study period. We compare the computed coastal trends in Africa with results we previously obtained in other regions (Mediterranean Sea, Northeastern Europe, north Indian Sea, southeast Asia and Australia).

The ALtimetry for BIOMass (ALBIOM) project is an ESA-funded Permanent Open Call Project that aims to retrieve forest biomass using Copernicus Sentinel-3 (S3) altimeter data. The overall goal of ALBIOM is to estimate biomass with sufficient accuracy to be able to increase existing satellite data for biomass retrieval, as well as to improve the global mapping and monitoring of this fundamental variable. The project core tasks consist of 1) an analysis of the sensitivity of altimetry backscatter data on land parameters; 2) the development and validation of a Sentinel-3 altimeter backscatter simulator, including the effect of both topography and vegetation and 3) the development and validation of a machine-learning biomass estimation algorithm.Here we present a summary of the results obtained from the project. The sensitivity analysis reveals that both the altimetric waveforms and the corresponding Normalised Radar Cross Sections (NRCSs) can be sensitive to the presence of biomass in the order of 100-400 tons/ha, but they are also influenced by topography and water bodies. Different sensitivities with respect to the different frequencies and resolution modes are observed, highlighting non-linear behaviours of the NRCSs. The use of differential NRCSs, defined as the difference among those calculated over two different bandwidths, was demonstrated to be not necessarily more sensitive to vegetation, as it was instead highlighted by previous studies like [Papa et al., 2003].The tracking window often appears partly or completely misplaced, when the tracking mode is in open-loop mode prescribing a predetermined range, and its size is often not long enough when collecting data over land, especially over regions with complex topography. The length and correct positioning of the tracking window over land represent therefore critical aspects for a study like ALBIOM.The modelling work has been focused on the development of a merged model approach to simulate altimeter waveforms over vegetated areas. The merging is obtained via the simultaneous use of the modifiedTor Vergata Scattering Model (TOVSM) [Ferrazzoli and Guerriero, 1995, 1996] to simulate the waveform of a flat surface covered by forest vegetation, and the use of the Soil And Vegetation Reflection Simulator (SAVERS) [Pierdicca et al., 2014], originally conceived for GNSS-Reflectometry, and here adapted to the Altimetry system. The simulator developed within ALBIOM shows promising ability to reproduce the general characteristics of the S3 waveforms. The simulations related to forested surfaces present at least two peaks, due to the top of canopy and to the ground, but the presence of topography may introduce other peaks in the waveforms, making the identification of vegetation and topographic effects challenging.Initial results on the algorithm development using Artificial Neural Networks (ANN) highlight some promising biomass estimates over specific areas (e.g. Central Africa) but also differences in algorithm performances among different regions. The corrected “ice” backscatter coefficient showed the highest sensitivity to biomass, but its values are often invalid over land, which limits the number of meaningful retrievals. The different altimeter tracking mode of Sentinel-3 over different areas of the globe (i.e., open loop and closed loop) could also be responsible for the differences in results.

International audience; In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2-4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.

International audience; Since 2010, the CryoSat-2 satellite mission has enabled to largely improve sea ice freeboard estimations. But due to the complexity of radar echoes over sea ice, freeboard retrieval from altimetry still presents some errors and biases that further limit the potential of these observations for climate studies or for assimilation into models. Various methods have been explored, producing a large range of freeboard estimations. In this study, we analyze the main steps of the radar freeboard computation developed as part of the Cryo-SeaNice Project. The objective is to quantify the impacts of each processing method and to identify optimal strategies to improve freeboard estimations from SAR altimetry measurements. We consider two SAR processing options: the Hamming Window (HW) and with the Zero-Padding (ZP), and 2 retrackers: the Threshold First Maximum Retracker Algorithm (TFMRA) based on heuristic measurements and SAMOSA+ a retracker declined from model based analysis of the surface back-scatter. Four freeboard solutions are generated from combinations of the 2 processing options (HW and ZP or ZP only) and the 2 types of retrackers. In addition, an alternative to the Hamming Window method to filter out side-lobes errors is presented. The impacts of the different approaches to estimate freeboard are quantified from comparisons with Operation Ice Bridge (OIB) and the Beaufort Gyre Exploration project (BGEP) in situ data. Our results show that SAMOSA+ provides more precise freeboard estimations. This new time-series is available on CTOH website. We also identified some impacts of the Hamming Window for both retrackers. Finally, we present the potential of using the simpler threshold retracker but with a correction to account for the surface roughness that is calibrated against SAMOSA+.

The monitoring of rivers is not the primary objective of the Sentinel-3 mission. The first satellite of the constellation was launched in February 2016 and so far no study has investigated the joint use of altimeter, near-infrared and thermal sensors for discharge estimation. Nevertheless, similar sensors onboard other platforms have showed their ability to estimate river discharge also in scarcely gauged areas. The advantage of altimetry lies in the observation of water surface elevation, which can be proficiently used in approaches based on rating curve, empirical formulae or hydraulic modeling. Even though their use is limited, near-infrared sensors are successfully used to detect the variability of river discharge thanks to their high capacity to discriminate water from land. Thermal sensors are nearly completely unused, but the unique study that uses the difference in temperature of the river water between day and night for the estimation of water level, encourages its use for river discharge assessment as well. To improve the estimation of river discharge and foster studies that are aimed at monitoring ungauged rivers, the combination of the sensors is considered a viable path. The aim of this manuscript is to review these studies to show the limitations and the potentials of each sensor onboard the Sentinel-3 satellite and to investigate the added value of using these three sensors co-located on the same platform for river discharge monitoring.

Information on sea level and its temporal and spatial variability is of great importance for various scientific, societal, and economic issues. This article reports about a new sea level dataset for the North Sea (named North SEAL) of monthly sea level anomalies (SLAs), absolute sea level trends, and amplitudes of the mean annual sea level cycle over the period 1995–2019. Uncertainties and quality flags are provided together with the data. The dataset has been created from multi-mission cross-calibrated altimetry data preprocessed with coastal dedicated approaches and gridded with an innovative least-squares procedure including an advanced outlier detection to a 6–8 km wide triangular mesh. The comparison of SLAs and tide gauge time series shows good consistency, with average correlations of 0.85 and maximum correlations of 0.93. The improvement with respect to existing global gridded altimetry solutions amounts to 8 %–10 %, and it is most pronounced in complicated coastal environments such as river mouths or regions sheltered by islands. The differences in trends at tide gauge locations depend on the vertical land motion model used to correct relative sea level trends. The best consistency with a median difference of 0.04±1.15 mm yr−1 is reached by applying a recent glacial isostatic adjustment (GIA) model. With the presented sea level dataset, for the first time, a regionally optimized product for the entire North Sea is made available. It will enable further investigations of ocean processes, sea level projections, and studies on coastal adaptation measures. The North SEAL data are available at https://doi.org/10.17882/79673 (Müller et al., 2021).

The advent of SAR (delay-Doppler) altimetry allowed the production of data with a high spatial resolution (300 m along-track). Investigations in the inland water domain clearly benefited from SAR data and future processing strategies (e.g. the fully-focused SAR, FF-SAR) are expected to improve further the quantity of data points over water bodies of a reduced size.The proposed work aims at investigating the quality of Sentinel-3 water level retrievals over three targets of different characteristics: the Ohio River, the Columbia River and the Great Salt Lake. Data are processed through the ESA G-POD SARvatore online and on-demand processing service for the exploitation of CryoSat-2 and Sentinel-3 data (https://gpod.eo.esa.int/services/SENTINEL3_SAR/) and obtained by using the SAMOSA2, SAMOSA+ & SAMOSA++ retrackers. The selected posting rate of measurements is 80 Hz to optimize the location of data points over the Ohio and Columbia River (an estimate every 80 m along-track), however a comparison with the 20 Hz posting rate is being made. Empirical retrackers outputs, available in the official 20 Hz Sentinel-3 LAN products, are also considered for comparison and water masks from (Pekel et al., 2016) are used to select data points acquired over water bodies.The main goal of this study is to analyse the key parameters characterizing both the L1b SAR waveform and the retracking (e.g. the Pulse Peakiness, the Misfit…) to define a robust error characterization method that is expected to filter out an increased number of outliers. A validation exercise using in situ data will be presented to demonstrate that the proposed method leads to the definition of a reduced, highly reliable dataset, associated with a realistic error characterization model.The study is expected to unlock possible synergies with SWOT and support the comparison of SAR estimates to FF-SAR estimates obtained at a comparable along-track resolution.

The scope of this presentation is to feature the G-POD SARvatore service to users for the exploitation of CryoSat-2 and Sentinel-3 data, which was designed and developed by the Altimetry Team in the R&D division at ESA-ESRIN. The G-POD service coined SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) is a web platform that allows any scientist to process on-line, on-demand and with user-selectable configuration CryoSat-2 SAR/SARin and Sentinel-3 SAR data, from L1A (FBR) data products up to SAR/SARin Level-2 geophysical data products. The G-POD graphical interface allows users to select a geographical area of interest within the time-frame related to the Cryosat-2 SAR/SARin FBR and Sentinel-3 L1A data products availability in the service catalogue. The processor prototype is versatile, allowing users to customize and to adapt the processing according to their specific requirements by setting a list of configurable options. Pre-defined processing configurations (Official CryoSat-2, Official Sentinel-3, Open Ocean, Coastal Zone, Inland Water (20Hz & 80Hz), Ice and Sea-Ice) are available. After the task submission, users can follow, in real time, the status of the processing. The output data products are generated in standard NetCDF format, therefore being compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info) and typical tools.Initially, the processing was designed and optimized uniquely for open ocean studies. It was based on the SAMOSA model developed for the Sentinel-3 Ground Segment. However, since June 2015, the SAMOSA+ retracker is available as a dedicated retracker for coastal zone, inland water and sea-ice/ice-sheet. A new retracker (SAMOSA++) has been recently developed and will be made available in the future. The scope is to maximize the exploitation of CryoSat-2 and Sentinel-3 data over all surfaces providing user with specific processing options not available in the default processing chains.Recent improvements include: 1) A Join & Share Forum to allow users to post questions and report issues (https://wiki.services.eoportal.org/tiki-custom_home.php); 2) A data repository to better support the growing Altimetry Community avoiding the redundant reprocessing of already processed data (https://wiki.services.eoportal.org/tiki-index.php?page=SARvatore+Data+Repository&highlight=repository); 3) A new function in the GUI allowing users to compute the geodetic distance between selected points on the map; 4) A new function in the GUI to filter the products search to a specific RON (Relative Orbit Number) and to a specific pass direction (Ascending or Descending). Furthermore, users will find in the folder SUM_RESDIR of the output data package a short summary report with information on the products that have not been processed and instructions on how to eventually try to re-process the missing data.To respond to the request of hydrologists, and simulate data that a river gauge would provide, SARvatore will soon include a post-processing service to convert water level estimates in L2 data to virtual station water level values, which are typically required by hydrologists. Validation of SARvatore data over river targets will be presented to demonstrate the potential of both the SAMOSA+/++ retrackers and the innovative processing configurations not available in the default CryoSat-2 and Sentinel-3 processing chains.

The ALtimetry for BIOMass project (ALBIOM) is ESA-funded Permanent Open Call Project that proposes to derive forest biomass using Copernicus Sentinel-3 (S3) SAR altimeter data. The project targets the need to improve our current global observations of biomass as an Essential Climate Variable (ECV) and crucial for bioenergy, risk mitigation activities, and sustainable management of forests. The overall goal is to estimate biomass with sufficient accuracy to be able to increase the existing satellite data for biomass retrieval and to improve the global mapping and monitoring of this fundamental variable.The project originates from evidence that radar altimetry backscatter over land responds to a variety of land parameters, including vegetation-related parameters, at the different bands used by past and existing altimeters.To achieve the scientific objectives, the project is structured into six conceptual tasks. After a review of the literature and of the existing user needs, a sensitivity analysis is performed to understand the relationship between SAR altimetry backscatter data and land parameters themselves. This is followed by the development of a Sentinel-3 SAR altimeter backscatter simulator over vegetated areas, and then by the development of a biomass inversion algorithm, testing different retrieval methodologies, both theoretical and empirical. A validation task for both the model and the algorithm is carried out over specific test sites of boreal and tropical forests, to finally generate a prototype of biomass product to be reviewed by potential users.The sensitivity analysis allows to understand how the S3 Level 1 backscatter power waveforms change with respect to varying biomass, but also how they are affected by other land parameters such as soil moisture, land cover, topography and roughness. This analysis is carried out considering both the single-looked and the multi-looked waveforms, and considering primarily the high-resolution SAR mode, but also the Pseudo Low Resolution Mode (PLRM). The outcome of the sensitivity analysis provides indication of what waveforms, acquisition mode, observables derived from the waveforms and characteristics of the waveforms themselves respond more strongly to biomass variations, and on the degree of influence of the other auxiliary parameters, informing on the best strategies and approaches to adopt for the development of the retrieval algorithm.Subsequent to the sensitivity analysis, the S3 altimetry backscatter simulator is developed over vegetated areas, reproducing both the coherent scattering component, which represents the echo from the ground, and incoherent scattering component arising from the forest layers between the ground and the top of canopy. The approach followed is similar to that of the SAVERS simulator, developed for GNSS-Reflectometry, with the signal backscatter attenuation introduced by branches, leaves and trunks modelled through the discrete approach of the Tor Vergata Scattering Model.Results from the sensitivity analysis and the initial stages of the simulation development will be presented and discussed at the conference, together with the foreseen approaches for the development of the biomass retrieval algorithm.

Significant wave height (SWH) and surface wind speed (WS) products from the CryoSat-2 Delay-Doppler, which is commonly known as Synthetic Aperture Radar (SAR), Mode are validated against operational ECMWF atmospheric and wave model results in addition to available observations from buoys, platforms and Jason-2 altimeter. The CryoSat-2 SAR Mode data are processed from Level 1A (also known as Full Bit Rate, FBR, in the CryoSat-2 terminology) up to L1B in accordance to the Delay-Doppler algorithm, and then retracked using SAMOSA (SAR Altimetry MOde Studies and Applications) SAR return waveform model, as implemented in the Grid Processing on Demand (G-POD) service called SAR Versatile Altimetric Toolkit for Ocean Research and Exploitation (SARvatore). The data cover two geographic boxes: one in the northeast Atlantic Ocean (NE Atlantic Box) for the period from 6 September 2010 to 30 June 2014 and the other is in the eastern Pacific (Pacific Box) for the period from 7 May 2012 to 30 June 2014. The amount of data is limited by the CryoSat-2 SAR Mode acquisition mask over ocean but is large enough to ensure robustness and significance of the results. The results show that the quality of both CryoSat-2 SAR SWH and WS products is very high when compared to typical altimetry mission requirements. When compared against model and in-situ data, the correlation coefficients are as high as 0.98 for SWH and 0.95 for WS while the bias and standard deviation of the difference is less than 5% and 0.3 m, respectively, for SWH and less than 0.3 m/s and 1.3 m/s, respectively for WS. The results show that the quality of both CryoSat-2 SAR SWH and WS products is in line with Jason-2 performances and satisfies the typical altimetry mission requirements.

Water level from sea ice-covered oceans is particularly challenging to retrieve with satellite radar altimeters due to the different shapes assumed by the returned signal compared with the standard open ocean waveforms. Valid measurements are scarce in large areas of the Arctic and Antarctic Oceans, because sea level can only be estimated in the openings in the sea ice (leads and polynyas). Similar signal-related problems affect also measurements in coastal and inland waters. This study presents a fitting (also called retracking) strategy (ALES+) based on a subwaveform retracker that is able to adapt the fitting of the signal depending on the sea state and on the slope of its trailing edge. The algorithm modifies the existing Adaptive Leading Edge Subwaveform retracker originally designed for coastal waters, and is applied to Envisat and ERS-2 missions. The validation in a test area of the Arctic Ocean demonstrates that the presented strategy is more precise than the dedicated ocean and sea ice retrackers available in the mission products. It decreases the retracking open ocean noise by over 1 cm with respect to the standard ocean retracker and is more precise by over 1 cm with respect to the standard sea ice retracker used for fitting specular echoes. Compared to an existing open ocean altimetry dataset, the presented strategy increases the number of sea level retrievals in the sea ice-covered area and the correlation with a local tide gauge. Further tests against in-situ data show that also the quality of coastal retrievals increases compared to the standard ocean product in the last 6 km within the coast. ALES+ improves the sea level determination at high latitudes and is adapted to fit reflections from any water surface. If used in the open ocean and in the coastal zone, it improves the current official products based on ocean retrackers. First results in the inland waters show that the correlation between water heights from ALES+ and from in-situ measurement is always over 0.95.

Present-day global mean sea level rise is caused by ocean thermal expansion, ice mass loss from glaciers and ice sheets, as well as changes in terrestrial water storage. For that reason, sea level is one of the best indicators of climate change as it integrates the response of several components of the climate system to internal and external forcing factors. Monitoring the global mean sea level allows detecting changes (e.g., in trend or acceleration) in one or more components. Besides, assessing closure of the sea level budget allows us to check whether observed sea level change is indeed explained by the sum of changes affecting each component. If not, this would reflect errors in some of the components or missing contributions not accounted for in the budget. Since the launch of TOPEX/Poseidon in 1992, a precise 27-year continuous record of sea level change is available. It has allowed major advances in our understanding of how the Earth is responding to climate change. The last two decades are also marked by the launch of the GRACE satellite gravity mission and the development of the Argo network of profiling floats. GRACE space gravimetry allows the monitoring of mass redistributions inside the Earth system, in particular land ice mass variations as well as changes in terrestrial water storage and in ocean mass, while Argo floats allow monitoring sea water thermal expansion due to the warming of the oceans. Together, satellite altimetry, space gravity, and Argo measurements provide unprecedented insight into the magnitude, spatial variability, and causes of present-day sea level change. With this observational network, we are now in a position to address many outstanding questions that are important to planning for future sea level rise. Here, we detail the network for observing sea level and its components, underscore the importance of these observations, and emphasize the need to maintain current systems, improve their sensors, and supplement the observational network where gaps in our knowledge remain.

Coastal zones are highly dynamical systems affected by a variety of natural and anthropogenic forcing factors that include sea level rise, extreme events, local oceanic and atmospheric processes, ground subsidence, etc. However, so far, they remain poorly monitored on a global scale. To better understand changes affecting world coastal zones and to provide crucial information to decision-makers involved in adaptation to and mitigation of environmental risks, coastal observations of various types need to be collected and analyzed. In this white paper, we first discuss the main forcing agents acting on coastal regions (e.g., sea level, winds, waves and currents, river runoff, sediment supply and transport, vertical land motions, land use) and the induced coastal response (e.g., shoreline position, estuaries morphology, land topography at the land-sea interface and coastal bathymetry). We identify a number of space-based observational needs that have to be addressed in the near future to understand coastal zone evolution. Among these, improved monitoring of coastal sea level by satellite altimetry techniques is recognized as high priority. Classical altimeter data in the coastal zone are adversely affected by land contamination with degraded range and geophysical corrections. However, recent progress in coastal altimetry data processing and multi-sensor data synergy, offers new perspective to measure sea level change very close to the coast. This issue is discussed in much detail in this paper, including the development of a global coastal sea-level and sea state climate record with mission consistent coastal processing and products dedicated to coastal regimes. Finally, we present a new promising technology based on the use of Signals of Opportunity (SoOp), i.e., communication satellite transmissions that are reutilized as illumination sources in a bistatic radar configuration, for measuring coastal sea level. Since SoOp technology requires only receiver technology to be placed in orbit, small satellite platforms could be used, enabling a constellation to achieve high spatio-temporal resolutions of sea level in coastal zones., Part of this work has been carried out with the financial support of the following research projects: Spanish research grant ESP2015-70014-C2-2-R (MINECO/FEDER) and Spanish Ministry of Science, Innovation and Universities: RTI2018-099008-B-C22, ESA contract Sea_Level_cci (No. 4000126561/19/I-NB).

Satellite radar altimetry provides a unique sea level data set that extends over more than 25 years back in time and that has an almost global coverage. However, when approaching the coasts, the extraction of correct sea level estimates is challenging due to corrupted waveforms and to errors in most of the corrections and in some auxiliary information used in the data processing. The development of methods dedicated to the improvement of altimeter data in the coastal zone dates back to the 1990s, but the major progress happened during the last decade thanks to progress in radar technology [e.g., synthetic aperture radar (SAR) mode and Ka-band frequency], improved waveform retracking algorithms, the availability of new/improved corrections (e.g., wet troposphere and tidal models) and processing workflows oriented to the coastal zone. Today, a set of techniques exists for the processing of coastal altimetry data, generally called “coastal altimetry.” They have been used to generate coastal altimetry products. Altimetry is now recognized as part of the integrated observing system devoted to coastal sea level monitoring. In this article, we review the recent technical advances in processing and the new technological capabilities of satellite radar altimetry in the coastal zone. We also illustrate the fast-growing use of coastal altimetry data sets in coastal sea level research and applications, as high-frequency (tides and storm surge) and long-term sea level change studies.

By convention the absolute bias in sea surface height (SSH) is the difference between the altimeter and the in-situ reference SSH heights above the Earth ellipsoid. Both the absolute and the relative bias of the CryoSat-2 and Sentinel-3A missions are derived in this study at four stations along the German coasts.

Floods are one of the most dramatic natural disasters, in terms of casualties and economic damage. Remote sensing offers an efficient and reliable tool for detecting the inundation extent over the affected areas and for monitoring the water level within the river channel. The latter is important for forecasting flood extreme events and 25 years of satellite radar altimetry, even if not properly designed for inland water, provide an important instrument for monitoring rivers and floods. This chapter investigates the use of altimetry and its synergy with other satellite sensors for monitoring water surface elevation and river discharge with particular attention to estimating and forecasting floods.

This chapter provides an overview of the satellite altimetry measurement system, how it works and how the water surface elevation is derived. Satellite altimetry had originally been designed for open ocean studies, however a decade of progress has significantly improved the retrieval of data in coastal zones and inland waters. Advances in observational techniques (Ka-band and delay-Doppler/SAR-mode), revisited data processing, and improved corrections led to a higher accuracy in water surface elevation retrieval in these challenging areas. The available data sets with consistent coastal processing as well as the existing products dedicated to inland waters are presented including their potential accuracy for exploitation. The latest developments and capabilities of the various altimetric missions around coasts and inland are illustrated, with an emphasis on describing the benefits to studies of extreme events (heavy river discharge and storm surges). The future satellite altimetry missions such as Sentinel-3 and Sentinel-6/Jason-CS are expected to increase capabilities and coverage and represent a great opportunity to stimulate further exploitation of altimeter data in coastal and inland water targets.

A regional cross-calibration between the first Delay-Doppler altimetry dataset from Cryosat-2 and a retracked Envisat dataset is here presented, in order to test the benefits of the Delay-Doppler processing and to expand the Envisat time series in the coastal ocean. The Indonesian Seas are chosen for the calibration, since the availability of altimetry data in this region is particularly beneficial due to the lack of in-situ measurements and its importance for global ocean circulation. The Envisat data in the region are retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker, which has been previously validated and applied successfully to coastal sea level research.The study demonstrates that CryoSat-2 is able to decrease the 1-Hz noise of sea level estimations by 0.3 cm within 50 km of the coast, when compared to the ALES-reprocessed Envisat dataset. It also shows that Envisat can be confidently used for detailed oceanographic research after the orbit change of October 2010. Cross-calibration at the crossover points indicates that in the region of study a sea state bias correction equal to 5% of the significant wave height is an acceptable approximation for Delay-Doppler altimetry.The analysis of the joint sea level time series reveals the geographic extent of the semiannual signal caused by Kelvin waves during the monsoon transitions, the larger amplitudes of the annual signal due to the Java Coastal Current and the impact of the strong La Niña event of 2010 on rising sea level trends.

This chapter provides some basics of the interpretation of satellite altimetry measurements and explains how to use altimetry for hydrology. Satellite altimetry has been extensively used over the last two decades to calculate the water height variations over the Earth's lakes, rivers, reservoirs, and floodplains. Time series of altimetry-based water levels can be used to detect the signature of climate variability and extreme climatic events on the surface water storage. Echoes are acquired due to a tracking system placed on board the satellite known as "trackers". In the nominal tracking mode, the Jason-2 Poseidon-3 altimeter uses the "median tracker" concept, which again ensures the independence of shape pulse power weighting similar to the Free Model Tracker design on board Envisat. A dry tropospheric correction must be applied to the ranges in order to account for the delay of propagation of the radar pulse through the atmosphere.

10th Coastal Altimetry Workshop; Florence, Italy, 21–24 February 2017

For early satellite altimeters, the retrieval of geophysical information (e.g., range, significant wave height) from altimeter ocean waveforms was performed on board the satellite, but this was restricted by computational constraints that limited how much processing could be performed. Today, ground-based retracking of averaged waveforms transmitted to the earth is less restrictive, especially with respect to assumptions about the statistics of ocean waves. In this paper, a theoretical maximum likelihood estimation (MLE) ocean waveform retracker is applied tothe Envisat Radar Altimeter system (RA-2) 18-Hz averaged waveforms under both linear (Gaussian) and nonlinear ocean wave statistics assumptions, to determine whether ocean wave skewness can be sensibly retrieved from Envisat RA-2 waveforms. Results from the MLE retracker used in nonlinear mode provide the first estimates of global ocean wave skewness based on RA-2 Envisat averaged waveforms. These results show for the first time geographically coherent skewness fields and confirm the notion that large values of skewness occur primarily in regions of large significant wave height. Results from the MLE retracker run in linear and nonlinear modes are compared with each other and with the RA-2 Level 2 Sensor Geophysical Data Records (SGDR) products to evaluate the impact of retrieving skewness on other geophysical parameters. Good agreement is obtained between the linear and nonlinear MLE results for both significant wave height and epoch (range), except in areas of high-wave-height conditions.

The SRAL Radar Altimeter, on board of the ESA Mission Sentinel-3 (S-3), has the capacity to operate either in the Pulse-Limited Mode (also known as LRM) or in the novel Synthetic Aperture Radar (SAR) mode. Thanks to the initial results from SAR Altimetry obtained exploiting CryoSat-2 data, lately the interest by the scientific community in this new technology has significantly increased and consequently the definition of accurate processing methodologies (along with validation strategies) has now assumed a capital importance. In this paper, we present the algorithm proposed to retrieve from S-3 STM SAR return waveforms the standard ocean geophysical parameters (ocean topography, wave height and sigma nought) and the validation results that have been so far achieved exploiting the CryoSat-2 data as well as the simulated data. The inversion method (retracking) to extract from the return waveform the geophysical information is a curve best-fitting scheme based on the bounded Levenberg-Marquardt Least-Squares Estimation Method (LEVMAR-LSE). The S-3 STM SAR Ocean retracking algorithm adopts, as return waveform's model, the “SAMOSA” model [Ray et al, 2014], named after the R&D project SAMOSA (led by Satoc and funded by ESA), in which it has been initially developed. The SAMOSA model is a physically-based model that offers a complete description of a SAR Altimeter return waveform from ocean surface, expressed in the form of maps of reflected power in Delay-Doppler space (also known as stack) or expressed as multilooked echoes. SAMOSA is able to account for an elliptical antenna pattern, mispointing errors in roll and yaw, surface scattering pattern, non-linear ocean wave statistics and spherical Earth surface effects. In spite of its truly comprehensive character, the SAMOSA model comes with a compact analytical formulation expressed in term of Modified Bessel functions. The specifications of the retracking algorithm have been gathered in a technical document (DPM) and delivered as baseline for industrial implementation. For operational needs, thanks to the fine tuning of the fitting library parameters and the usage of look-up table for Bessel functions computation, the CPU execution time was accelerated over 100 times and made the execution in par with real time. In the course of the ESA-funded project CryoSat+ for Ocean (CP4O), new technical evolutions for the algorithm have been proposed (as usage of PTR width look up table and application of a stack masking). One of the main outcomes of the CP4O project was that, with these latest evolutions, the SAMOSA SAR retracking was giving equivalent results to CNES CPP retracking prototype, which was built with a totally different approach, which enforces the validation results. Work actually is underway to align the industrial implementation with the last new evolutions. Further, in order to test the algorithm with a dataset as realistic as possible, a set of simulated Test Data Set (generated by S-3 STM End-to-End Simulator) has been created by CLS following the specifications as described in a test data set requirements document drafted by ESA. In this work, we will show the baseline algorithm details, the evolutions, the impact of the evolutions and the results obtained processing the CryoSat-2 data and the simulated test data set.

The annual cycle is a major contribution to the non-tidal variability in sea level. Its characteristics can vary substantially even at a regional scale, particularly in an area of high variability such as the coastal ocean. This study uses previously validated coastal altimetry solutions (from ALES dataset) and the reference ESA Sea Level Climate Change Initiative dataset to improve the understanding of the annual cycle during the Envisat years (2002-2010) in the North Sea - Baltic Sea transition area. This area of study is chosen because of the complex coastal morphology and the availability of in-situ measurements.To our knowledge, this is the first time that the improvements brought by coastal satellite altimetry to the description of the annual variability of the sea level have been evaluated and discussed. The findings are interpreted with the help of a local climatology and wind stress from a reanalysis model.The coastal amplitude of the annual cycle estimated from ALES altimetry data is in better agreement with estimations derived from in-situ data than the one from the reference dataset. Wind stress is found to be the main driver of annual cycle variability throughout the domain, while different steric contributions are responsible for the differences within and among the sub-basins.We conclude that the ALES coastal altimetry product is a reliable dataset to study the annual cycle of the sea level at a regional scale and the strategy described in this research can be applied to other areas of the coastal ocean where the coverage from the tide gauges is not sufficient.

8th Coastal Altimetry Workshop; Konstanz, Germany, 23–24 October 2014

The retrieval of the three geophysical parameters – sea surface height above the reference ellipsoid (SSH), significant wave height (SWH) and wind speed at 10 m above the sea surface (U10) – is the main goal of satellite altimetry and of primary importance for climate research. The Synthetic Aperture Radar (SAR) altimetry is expected to provide improved precision and along-track resolution compared to the conventional low-resolution mode (LRM) radar altimetry. CryoSat-2 enables a quantitative comparison of SAR and Pseudo-LRM (PLRM) data derived respectively from a coherent and an incoherent processing of the same SAR echoes. In this paper we perform their cross-validation and validation against in situ and model data to derive precision and accuracy at 1 Hz in open ocean, at distances larger than 10 km from the coast. The analysis is performed in the German Bight during 2011 and 2012. Both the PLRM and the SAR scheme include waveform zero-padding and identical environmental, geophysical, and atmospheric attenuation corrections. A Look Up Table is additionally used in SAR to correct for approximations of the Point Target Response (PTR) applied in the retracking procedure. The regional cross-validation analysis proves the good consistency between PLRM and SAR data, with no bias and rms differences of 3 cm, 21 cm, and 0.26 m/s for SSH, SWH, and U10, respectively. The precision of SSH and SWH is higher in SAR than in PLRM (by a factor of 2), while the precision of U10 is 1.4 times better in PLRM than in SAR. At 2 m waveheight, the SAR precision is 0.9 cm for SSH, 6.6 cm for SWH. and 5.8 cm/s for U10. The in situ analysis shows that SSH and U10 have comparable accuracy in SAR and PLRM, while SWH has a significantly higher accuracy in SAR. With a maximum distance of 20 km between altimeter and in situ data, the minimum values obtained for their rms differences are 7 cm, 14 cm, and 1.3 m/s for SAR and 6 cm, 29 cm, and 1.4 m/s for PLRM.

Sea level is one of the 50 Essential Climate Variables (ECVs) listed by the Global Climate Observing System (GCOS) in climate change monitoring. In the last two decades, sea level has been routinely measured from space using satellite altimetry techniques. In order to address a number of important scientific questions such as: "Is sea level rise accelerating?", "Can we close the sea level budget?", "What are the causes of the regional and interannual variability?", "Can we already detect the anthropogenic forcing signature and separate it from the internal/natural climate variability?", and "What are the coastal impacts of sea level rise?", the accuracy of altimetry-based sea level records at global and regional scales needs to be significantly improved. For example, the global mean and regional sea level trend uncertainty should become better than 0.3 and 0.5 mm year−1, respectively (currently of 0.6 and 1–2 mm year−1). Similarly, interannual global mean sea level variations (currently uncertain to 2–3 mm) need to be monitored with better accuracy. In this paper, we present various respective data improvements achieved within the European Space Agency (ESA) Climate Change Initiative (ESA CCI) project on "Sea Level" during its first phase (2010–2013), using multi-mission satellite altimetry data over the 1993–2010 time span. In a first step, using a new processing system with dedicated algorithms and adapted data processing strategies, an improved set of sea level products has been produced. The main improvements include: reduction of orbit errors and wet/dry atmospheric correction errors, reduction of instrumental drifts and bias, inter-calibration biases, intercalibration between missions and combination of the different sea level data sets, and an improvement of the reference mean sea surface. We also present preliminary independent validations of the SL_cci products, based on tide gauges comparison and sea level budget closure approach, as well as comparisons with ocean re-analyses and climate model outputs.

In this chapter we review the history of coastal altimetry. We illustrate the challenges associated with data processing, improvement and exploitation, including: (1) what altimeter data are available today and what are the issues in coastal zones; (2) what efforts are underway to fill the gaps in coastal altimetry and what still needs to be done; (3) how coastal altimetry can be used in support of coastal oceanography. After nearly two decades of data collection near coasts, the planned reprocessing of the multi-mission global record now appears to be necessary for full exploitation of satellite altimetry for coastal oceanography. We will focus on the European research efforts, in particular the main outcomes of the COASTALT project, by showcasing improved corrections (with special emphasis on the wet tropospheric effect), waveform analysis and novel retracking techniques, as well as the structure of the new processor for Envisat RA-2 coastal records. This is of interest to a broad range of data integrators who will be able to use the improved altimeter data in their operational products or services.

Since the launch of the Radar Altimeters on-board ERS-1 and TOPEX/POSEIDON 19 years ago, significant advances in all facets of Radar Altimetry have resulted in a high accuracy over the open ocean to the centimeter level. Over inland water bodies such as rivers, lakes and reservoirs, the measurements are tenfold less precise, however it is recognized by the scientific community that, with special processing algorithms which are constantly being improved, useable results are obtained to support observations of watershed systems. This paper reports upon the strategic outlook for exploiting the current and future potential of Radar Altimetry missions and other space-borne data products to monitor surface water storage. The scope of this technique is to monitor thousands of river and lake heights worldwide, with the access to almost two decades of historical data now permitting analysis of trends and identification of climate signatures.

In this paper, we will showcase the main outcomes of the COASTALT project, including improved corrections (with special emphasis on the tropospheric effect) and novel re-tracking techniques built on established research results and the processing chain development with the generation and validation of ENVISAT test data sets over a selection of regional sites. We will also dive in further and explore how coastal altimetry might be exploited to its full potential in the coastal zone. This should be of interest to a broad range of data integrators that have an interest in using these improved altimeter data in their operational products or services.

Satellite altimetry has proved successful as a global tool for monitoring sea surface height, significant wave height and wind speed. Nevertheless, a global archive of 17 years of raw data from a series of missions is presently unexploited around the world coastline. This huge amount of unused data can be re-analyzed, improved and more intelligently exploited, possibly promoting coastal altimetry to the rank of operational service. Operational users interested in monitoring sea level change and wave conditions in the coastal zone (e.g. for coastal erosion, sediment/pollutant transport applications) still rely on sparse (and expensive) in situ monitoring stations or poor models. In this work we present a new approach in the exploitation of altimeter data in the coastal zone (currently impeded by unsuitable waveform retracking scheme and coarse along-track spatial sampling in the coastal zone, among others). The objective of this paper is to show how a new, robust, retracking algorithm is able to retrieve with high accuracy physical ocean parameters from altimeter waveforms in the coastal zone. The main focus lies on retrieving sea surface height in the coastal zone with the same precision as is achieved in the open ocean. In addition, the retrieval of more accurate altimeter-derived wave products in the coastal zone is also important as waves are more directly relevant to many operational applications in the coastal zone.

Fifteen years of global altimetry data over the coastal ocean lie, largely unexploited, in the data archives, simply because intrinsic difficulties in the corrections and issues of land contamination in the footprint. These data would be invaluable for studies of coastal circulation, sea level change and impact on the coastline. Amongst some initiatives, we describe here the COASTALT Project, funded by ESA. The main objective of the COASTALT Project is to contribute towards making the status of pulse-limited coastal altimetry operational. In this paper we will first illustrate the first project phase, based on the assessment of user requirements, and summarize those requirements. Then we will describe the COASTALT methodology and objectives. Finally, we will illustrate and discuss the various options for coastal waveform retracking, and present a plan for the validation of the retracked data. The first results in the radar altimeter waveform analysis show the complexity of the coastal signals due to land contamination and calm/rough waters.

This paper provides a brief overview of the objectives and methodology of the ESA funded project SAMOSA: "Development of SAR Altimetry Studies and Applications over Ocean, Coastal zones and Inland waters", and mainly concentrates on the development of a theoretical model for the mean return echo from a synthetic aperture radar (SAR) altimeter (also know as a delay doppler altimeter or DDA) observations over water surfaces, in the same spirit set by conventional altimeters.

A NEW SET OF TOOLS FOR ALL ALTIMETRY USERS The field of satellite radar altimetry has matured to a point where it is now time to encourage a multimission approach and conceive an "all-altimeter" toolbox including a tutorial. Such an integrated approach and view is vital not only for assessing the current status of what offers altimeter products but also to show the system and consistency with the past. The Basic Radar Altimetry Toolbox (BRAT) is a collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data for altimetry users, experienced as well as beginners, and particularly the users of the upcoming CryoSat mission. It is able to read most distributed radar altimetry data, from ERS-1 & 2, TOPEX/Poseidon, Geosat Follow-on, JASON-1, Envisat, and the future Cryosat missions, to perform some processing, data editing and statistic and to visualise the results. A version 2 is being developed with additional visualisation features such as waveform viewing. Also, a release for the MacOS is planned. As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data.

We have used the first three years of ERS-2 altimeter data (May 1995 - June 1998) in order to analyse the space-temporal ocean response to atmospheric pressure variations in the three main ocean world basins: Atlantic, Indian and Pacific. We have also quantified the magnitude of the departures of this response from the hypothetical barometric factor (-0.995 cm/mbar), commonly applied to altimeter data records to eliminate the effect of the atmospheric pressure variations in the ocean (Inverse Barometer Correction). From the results obtained, we have found a different behaviour in the Atlantic Ocean with respect to the other two basins, as far as the magnitude of the barometric factor is concerned. Considering that we have estimated the meridional response to atmospheric pressure variations by applying the collinear track and the crossover track methods, the Atlantic Ocean response is quite similar to the one deduced from the isostatic assumption at all latitudinal bands. Nonetheless, Indian and Pacific Oceans show important departures from the hypothetical value at low latitudes. In order to understand why the Atlantic Ocean response is different from the one obtained in the others two, we can infer some explanations but it seems that the different climatology in the basins could be explaining the results obtained, especially the effect of winds.

Within the ESA Ground Segment, all the Radar Altimeter (RA-2) and Microwave Radiometer (MWR) received data will be systematically processed to Level 1B (geolocated and calibrated engineering parameters) and to Level 2 (geophysical data record). All data will be processed in near real time (availability to users within three hours from data take), then reprocessed as Intermediate GDR (within 3 days) and later in off-line (few weeks after data take). The three version of the Level 2 product have the same layout and provide the typical information of the classical GDR altimeter product. The main difference among them is constituted by the increasing quality of the used orbit. Another main feature of the Level 2 RA-2 product is that every received waveform is processed in parallel by four different algorithms (each one optimised for a particular type of surface: ocean, sea ice, ice 1, ice 2). The Level 2 product (in all its versions) contains the results of the four retracking processes. The Level 1b product NRT and Off-line and the Level 2 NRT products are generated in the ESA station, while the IGDR and the Off-line GDR are produced for ESA by the French Processing and Archiving Centre. Concerning the geophysical corrections, it is important to note that the corresponding MWR measurements are used to correct for the wet tropospheric component, while the dry tropospheric component is corrected making use of the pressure field predicted or reconstructed by ECMWF (European Centre for Medium-Range Weather Forecast).

The Altimetry mission on ENVISAT will extend the time series of observations started by ERS-1 and ERS-2. The new features of the RA2 mission will improve the quality of the measurements in many aspects. The new on-board algorithms for tracking the surface, the larger range window and the extra low resolution mode will all improve data acquisition over the important ice sheet margins and over most land and wetland surfaces. New, in-situ ionospheric corrections from the dual frequency radar will be a significant improvement on the model-based corrections used in previous missions. The more precise DORIS orbit will improve the precision of all measurements, particularly in near real-time. The near real-time products are built with the same algorithms than the off-line final precision products, only some auxiliary input data may differ, thus providing already in 3 hours near-high quality Geophysical Data Record Products to support near real-time oceanography.

The ocean response to pressure variations is subtracted from altimeter records using the standard Inverse Barometer Correction (IBC), based on the hypothetical isostatic assumption. Previous analyses have demonstrated that this assumption has to be applied with care when the high frequency pressure variations are considered, as is the case of using the crossover track method. Using ERS-2 radar altimeter data, we study the response of the Atlantic Sea Level (ASL) to pressure forcings at different ranges of frequency, in order to determine the validity of the isostatic assumption. We have also determined this response when using the outputs of a Global Ocean Model (GOM) forced by pressure and wind fields. From the comparison between both results we have observed that data errors could be underestimating our estimations of the response of the ocean to pressure variations; this underestimation could represent more than 20 percent of the values obtained in equatorial and tropical zones, being insignificant out of the latitudinal band.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Synthetic aperture radar (SAR) altimetry is rapidly becoming the most efficient way to measure small-scale changes in elevations of ice, land, and water surfaces as well as sea ice thickness. This new generation altimeter, first launched on board the CryoSat-2 satellite, fires 10 times more radar pulses per second than the previous generation and exploits the motion of the spacecraft to achieve a 20-fold increase in along-track resolution and twofold improvement in its accuracy.