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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.

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.

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 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.

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.

The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days).

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.

The scope of this work is to showcase the BRAT (Broadview Radar Altimetry Toolbox) and GUT (GOCE User Toolbox) toolboxes.The Broadview Radar Altimetry Toolbox (BRAT) is a collection of tools designed to facilitate the processing of radar altimetry data from all previous and current altimetry missions, including Sentinel-3A L1 and L2 products. A tutorial is included providing plenty of use cases on Geodesy & Geophysics, Oceanography, Coastal Zone, Atmosphere, Wind & Waves, Hydrology, Land, Ice and Climate, which can also be consulted in http://www.altimetry.info/radar-altimetry-tutorial/.BRAT's last version (4.2.1) was released in June 2018. Based on the community feedback, the front-end has been further improved and simplified whereas the capability to use BRAT in conjunction with MATLAB/IDL or C/C++/Python/Fortran, allowing users to obtain desired data bypassing the data-formatting hassle, remains unchanged. Several kinds of computations can be done within BRAT involving the combination of data fields, that can be saved for future uses, either by using embedded formulas including those from oceanographic altimetry, or by implementing ad-hoc Python modules created by users to meet their needs. BRAT can also be used to quickly visualise data, or to translate data into other formats, e.g. from NetCDF to raster images.The GOCE User Toolbox (GUT) is a compilation of tools for the use and the analysis of GOCE gravity field models. It facilitates using, viewing and post-processing GOCE L2 data and allows gravity field data, in conjunction and consistently with any other auxiliary data set, to be pre-processed by beginners in gravity field processing, for oceanographic and hydrologic as well as for solid earth applications at both regional and global scales. Hence, GUT facilitates the extensive use of data acquired during GRACE and GOCE missions.In the current version (3.2), GUT has been outfitted with a graphical user interface allowing users to visually program data processing workflows. Further enhancements aiming at facilitating the use of gradients, the anisotropic diffusive filtering, and the computation of Bouguer and isostatic gravity anomalies have been introduced. Packaged with GUT is also GUT's Variance/Covariance Matrix (VCM) tool, which enables non-experts to compute and study, with relative ease, the formal errors of quantities – such as geoid height, gravity anomaly/disturbance, radial gravity gradient, vertical deflections – that may be derived from the GOCE gravity models.On our continuous endeavour to provide better and more useful tools, we intend to integrate BRAT into SNAP (Sentinel Application Platform). This will allow our users to easily explore the synergies between both toolboxes. During 2020 we will start going from separate toolboxes to a single one.BRAT and GUT toolboxes can be freely downloaded, along with ancillary material, at https://earth.esa.int/brat and https://earth.esa.int/gut.

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.

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.

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.

International audience; Low relief oceanic islands often suffer from scarcity of freshwater resources. Remote sensing has proved to be an effective tool to generate valuable data for hydrological analysis and has improved the management of ecosystems and water. However, remotely sensed data are often tested over areas with existing validation databases and not always where the need is greatest. In this paper we address the need for topographical data to understand the hydrological system of Santa Cruz Island (Galapagos archipelago) so that management of freshwater ecosystems and resources can take place. No high resolution, high accuracy topographical data exist for Santa Cruz Island, and its growing population has created an urgent need for water resource management and protection of unique and pristine ecosystems. Inaccessible National Park land covers more than 97% of Galapagos territory, which makes the use of remote sensing methods indispensable. SRTM data was insufficient in terms of grid size (90 m) to carry out the needed data analysis. We used ASAR data (ENVISAT) in VV polarization image mode for Digital Elevation Model (DEM) generation, in order to extract drainage network, watersheds, and flow characteristics from a morpho-structural analysis. Results show the high potential of these data for both interferometric and radargrammetric generation methods. Although interferometry suffered from low coherence over highly vegetated areas, it showed high precision over the rest of the island. Radargrammetry gave consistent results over the entire island, and details were enhanced by integrating the 90 m SRTM data as an external DEM. Accuracy of the SRTM and the combined radargrammetric/SRTM DEM was similar, with the radargrammetric having a finer pixel-based resolution (20 m). Validation of the extracted drainage networks and watersheds was carried out using ground-based field observations and comparison to mapped river networks visually extracted from aerial photographs and high resolution (1 m) satellite imagery available on GoogleEarth(C). For the first time, watershed characteristics and flow paths were made available for an island of the Galapagos archipelago. Furthermore, the drainage network is shown to be strongly influenced by observed and extracted structural discontinuities. Having characterized freshwater flow, water balance calculations were carried out for Pelican Bay watershed, where urban areas, agricultural land and Galapagos National Park land are concomitant.

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 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.

Soil moisture was recently included in the list of Essential Climate Variables (ECVs) that are deemed essential for IPCC (Intergovernmental Panel on Climate Change) and UNFCCC (United Nations Framework Convention on Climate Change) needs and considered feasible for global observation. ECVs data records should be as long, complete and consistent as possible, and in the case of soil moisture this means that the data record shall be based on multiple data sources, including but not limited to active (scatterometer) and passive (radiometer) microwave observations acquired preferably in the low-frequency microwave range. Among the list of sensors that can be used for this task are the C-band scatterometers on board of the ERS and METOP satellites and the multi-frequency radiometers SMMR, SSM/I, TMI, AMSR-E, and Windsat. Together, these sensors already cover a time period of more than 30 years and the question is how can observations acquired by these sensors be merged to create one consistent data record? This paper discusses on a high-level possible approaches for fusing the individual satellite data. It is argued that the best possible approach for the fusion of the different satellite data sets is to merge Level 2 soil moisture data derived from the individual satellite data records. This approach has already been demonstrated within the WACMOS project (http://wacmos.itc.nl/) funded by European Space Agency (ESA) and will be further improved within the Climate Change Initiative (CCI) programme of ESA (http://www.esa-cci.org/).

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.

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.

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.

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.

International audience; Altimetry missions in the last 16 years (TOPEX/Poseidon, ERS-1/2, GFO, Jason-1 and ENVISAT) and the recently-launched Jason-2 mission have resulted in great advances in deep ocean research and operational oceanography. However, oceanographic applications using satellite altimeter data have become very challenging over regions extending from near-shore to the continental shelf and slope (Cipollini et al. 2008). In these regions, intrinsic difficulties in the corrections (e.g., the high frequency ocean response to tidal and atmospheric loading, the mean sea level, etc.) and issues of land contamination in the radar altimeter and radiometer footprints result in systematic flagging and rejection of these data. Forthcoming altimeter missions (SARAL/AltiKa, SWOT, Sentinel-3, etc.) are designed to be better-suited for use in the coastal ocean. However, a number of studies have dealt with the problem of re-analysing, improving and exploiting the existing archive to monitor coastal dynamics. The early encouraging results (Vignudelli et al. 2005; Bouffard et al. 2008, Birol et al. submitted J Mar Syst 2009) support the need for continued research in coastal altimetry, with the opportunity of providing input and recommendations for future missions. This chapter reviews the current status of the X-TRACK processing application (Roblou et al. 2007), whose objectives are to improve both the quantity and quality of altimeter sea surface height (SSH) estimates in coastal regions by reprocessing a posteriori (the standard Geophysical Data Records) (GDR) as delivered by operational centres, i.e. by improving the post-processing stage. Latest improvements on along-track spatial resolution (high rate data streams and removal of large-scale errors) that promise improved monitoring of coastal dynamics are also detailed. In addition, with a view to integrating coastal-oriented altimeter datasets into models for coastal ocean state analysis, methodologies for matching models with observations are discussed.