The German Bight: A validation of CryoSat-2 altimeter data in SAR mode

Fenoglio-Marc, Luciana; Dinardo, Salvatore; Scharroo, Remko; Roland, Aron; Sikirić, Mathieu Dutour; Lucas, Bruno; Becker, Matthias; Benvéniste, Jérôme; Weiß, R.

doi:10.1016/j.asr.2015.02.014

Cited by 60 publications

(33 citation statements)

References 20 publications

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“…Users can easily submit processing jobs via an handy graphic user interface, follow up the jobs status remotely and download the output package on own archiving platforms (via ftp or direct link). This service tool is going to be extensively exploited in the ESA-funded Ocean Altimetry SEOM (Scientific Exploitation for Operational Missions) Project and already provided scientific community with valuable dataset [14]. More details on the service and user manual are available here:…”

Section: S-3 Stm Simulator (Sps) Test Data Set and Resultsmentioning

confidence: 99%

Sentinel-3 STM SAR ocean retracking algorithm and SAMOSA model

Dinardo

Lucas

Benvéniste

2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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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 LeastSquares 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 specificati...

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Section: S-3 Stm Simulator (Sps) Test Data Set and Resultsmentioning

confidence: 99%

Sentinel-3 STM SAR ocean retracking algorithm and SAMOSA model

Dinardo

Lucas

Benvéniste

2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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“…Moreover, DDA has an enhanced signal-to-noise ratio to retrieve fine-scale oceanographic features. In open ocean both accuracy and precision are higher in DDA than in Pseudo LRM (PLRM), or Reduced SAR (RDSAR) (Fenoglio-Marc et al, 2015a;Buchhaupt et al, 2017). PLRM/RDSAR are derived from the Full Bit Rate (FBR) data by processing the pulse-limited echoes incoherently, like in the conventional LRM concept (Smith and Scharroo, 2015).…”

Section: Retracking Conventional and Sar Mode Altimetrymentioning

confidence: 99%

Requirements for a Coastal Hazards Observing System

et al. 2019

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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 Frontiers in Marine Science | www.frontiersin.org 1 July 2019 | Volume 6 | Article 348Benveniste et al.Requirements for a Coastal Zone Observing System 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 multisensor 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.

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“…This retracker uses a look-up table to mitigate the effect of the model's approximation of the squared PTR (point target response) with a Gaussian curve, it implements a stack masking for the Doppler beams padded to zero and has in principle no enhancement in the coastal zone. SAMOSA+ retracker (the SAMOSA2 model tailored for inland water, sea ice and the coastal zone domain): in the case of SAMOSA+, the open ocean SAMOSA [11] model and retracker [13] has been implemented in the retracking scheme with two significant additions [12]: The first one concerns the selection of the first-guess epoch. This is not selected as the position of the waveform peak but as the position of the moving correlation peak in 20 consecutive waveforms (after aligning them for tracker shift).…”

Section: Sentinel-3amentioning

confidence: 99%

“…The second concerns the treatment of land-contaminated waveforms. In case waveforms are not contaminated by land, the SAMOSA model was used with the mean square slope set to zero, i.e., as in [13], whereas in the case of land contaminated waveforms, we used a dual step retracking: in the first step, the SWH is still estimated as in [13], while in the second step, the SWH was set to zero and the third free parameter in the retracking becomes the mean square slope. The output of this second step is the range and the amplitude Pu (retracked waveform amplitude, see Equation (22) in [12]).…”

Section: Sentinel-3amentioning

confidence: 99%

Calibrating the SAR SSH of Sentinel-3A and CryoSat-2 over the Corsica Facilities

et al. 2018

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Initially developed to monitor the performance of TOPEX/Poseidon and to follow the Jason legacy satellite altimeters at Senetosa Cape, Corsica, this calibration/validation site has been extended to include a new location at Ajaccio. This addition enables the site to monitor Envisat and ERS missions, CryoSat-2 and, more recently, the SARAL/AltiKa mission and Sentinel-3A satellites. Sentinel-3A and CryoSat-2 carry altimeters that use a synthetic aperture radar (SAR) mode that is different to the conventional pulse-bandwidth limited altimeters often termed "low resolution mode" (LRM). The aim of this study is to characterize the sea surface height (SSH) bias of the new SAR altimeter instruments and to demonstrate the improvement of data quality close to the coast. Moreover, some passes of Sentinel-3A and CryoSat-2 overfly both Senetosa and Ajaccio with only a few seconds time difference, allowing us to evaluate the reliability and homogeneity of both ground sites in term of geodetic datum. The Sentinel-3A and CryoSat-2 SSH biases for the SAR mode are respectively +22 ± 7 mm and −73 ± 5 mm (for CryoSat-2 baseline C products). The results show that the stability of the SAR SSH bias time series is better than standard LRM altimetry. Moreover, compared to standard LRM data, for which the measurements closer than~10 km from the coast were generally unusable, SAR mode altimeters provide measurements that are reliable at less than few hundred meters from the coast.

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The German Bight: A validation of CryoSat-2 altimeter data in SAR mode

Cited by 60 publications

References 20 publications

Sentinel-3 STM SAR ocean retracking algorithm and SAMOSA model

Sentinel-3 STM SAR ocean retracking algorithm and SAMOSA model

Requirements for a Coastal Hazards Observing System

Calibrating the SAR SSH of Sentinel-3A and CryoSat-2 over the Corsica Facilities

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