CryoSat-2 Full Bit Rate Level 1A processing and validation for inland water applications

Moore, P.; Birkinshaw, Stephen; Ambrózio, Américo; Restano, Marco; Benvéniste, Jérôme

doi:10.1016/j.asr.2017.12.015

Cited by 9 publications

(11 citation statements)

References 29 publications

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“…Equivalent products from older satellites (CryoSat-2, Jason-2 and Saral-Altika, for instance; see Figure 1) have been used to assess the quality improvement provided by more recent Sentinel data (Wiese et al, 2018). For this purpose, the new retracker SAMOSA++ (Dinardo et al, 2020) has been assessed against coupled model simulations and in-situ observations, analyzing the under-performance over coastal waters (Moore et al, 2018;Fenoglio et al, 2021). The new retracker profits from the extra-waveform information now available out of the L1B SAR processing and conforms to a single step retracker, allowing a seamless approach between ocean and coastal domains.…”

Section: Methodsmentioning

confidence: 99%

CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

et al. 2021

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Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions.

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Section: Methodsmentioning

confidence: 99%

CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

et al. 2021

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“…The second is a fully analytical SAR SAMOSA-2 retracker (Ray et al, 2015), which fits the theoretically modeled multi-look L1B waveform to the real L1B SAR waveform by using the Levenberg-Marquardt method and retrieving the geophysical variables range, backscatter coefficient, mispointing, and quality information. In the G-POD data set, the SAR SAMOSA+ retracker (Dinardo et al, 2017) was used, which includes application of a Hamming window and thus noise reduction (Moore et al, 2018). The hooking effect is thought to be negligible in SAR due to the smaller footprint and since only across-track off ranging will contribute to this error.…”

Section: Deriving Altimetric Water Levelsmentioning

confidence: 99%

“…Tarpanelli et al (2017), for the Niger-Benue river, suggested forecasting flood discharge from altimetric water levels, MODIS river width, and rating-curve calibration, however with in situ measurements of water levels being available. Others have proposed simulating discharge using fully fledged calibrated and validated land surface modeling (Pedinotti et al, 2012;Casse et al, 2016;Fleischmann et al, 2018;Poméon et al, 2018), assimilating altimetric levels into elaborate hydrodynamic modeling (Munier et al, 2015), or interpolating discharge based on empirical dynamic models trained on gauge discharge (Tourian et al, 2017); however such models are not always available and are less straightforward to transfer to new regions. Therefore we propose combining simplified hydrological models with radar altimetry.…”

Section: Introductionmentioning

confidence: 99%

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Schröder

Springer

Kusche

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. The Niger River represents a challenging target for deriving discharge from spaceborne radar altimeter measurements, particularly since most terrestrial gauges ceased to provide data during the 2000s. Here, we propose deriving altimetric rating curves by “bridging” gaps between time series from gauge and altimeter measurements using hydrological model simulations. We show that classical pulse-limited altimetry (Jason-1 and Jason-2, Envisat, and SARAL/Altika) subsequently reproduces discharge well and enables continuing the gauge time series, albeit at a lower temporal resolution. Also, synthetic aperture radar (SAR) altimetry picks up the signal measured by earlier altimeters quite well and allows the building of extended time series of higher quality. However, radar retracking is necessary for pulse-limited altimetry and needs to be further investigated for SAR. Moreover, forcing data for calibrating and running the hydrological models must be chosen carefully. Furthermore, stage–discharge relations must be fitted empirically and may need to allow for break points.

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“…The majority of previous studies [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] focus on relatively large water bodies with a scale of several kilometers. One of the first studies employing satellite altimetry for inland water level extraction was performed by Koblinsky et al [12], who processed Geodetic Satellite (Geosat) waveforms to estimate the water levels at four sites in the Amazon basin.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Retrackers’ Performances and Water Level Retrieval over the Ebro River Basin Using Sentinel-3

et al. 2019

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Satellite altimeters have been used to monitor river and reservoir water levels, from which water storage estimates can be derived. Inland water altimetry can, therefore, play an important role in continental water resource management. Traditionally, satellite altimeters were designed to monitor homogeneous surfaces such as oceans or ice sheets, resulting in poor performance over small inland water bodies due to the contribution from land contamination in the returned waveforms. The advent of synthetic aperture radar (SAR) altimetry (with its improved along-track spatial resolution) has enabled the measurement of inland water levels with a better accuracy and an increased spatial resolution. This study aimed to retrieve water levels from Level-1B Sentinel-3 data with focus on the minimization of the land contamination over small- to middle-sized water bodies (130 m to 4.5 km), where continuous clean waveforms rarely exist. Three specialized algorithms or retrackers, together with a new waveform portion selection method, were evaluated to minimize land contamination in the waveforms and to select the nadir return associated with the water body being overflown. The waveform portion selection method, with consideration of the Digital Elevation Model (DEM), was used to fit the multipeak waveforms that arise when overflying the continental water bodies, exploiting a subwaveform-based approach to pick up the one corresponding to the nadir. The performances of the proposed waveform portion selection method with three retrackers, namely, the threshold retracker, Offset Center of Gravity (OCOG) retracker and two-step SAR physical-based retracker, were compared. No significant difference was found in the results of the three retrackers. However, waveform portion selection using DEM information great improved the results. Time series of water levels were retrieved for water bodies in the Ebro River basin (Spain). The results show good agreement with in situ measurements from the Ebro Reservoir (approximately 1.8 km wide) and Ribarroja Reservoir (approximately 400 m wide), with unbiased root-mean-square errors (RMSEs) down to 0.28 m and 0.16 m, respectively, depending on the retracker.

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CryoSat-2 Full Bit Rate Level 1A processing and validation for inland water applications

Cited by 9 publications

References 29 publications

CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Analysis of Retrackers’ Performances and Water Level Retrieval over the Ebro River Basin Using Sentinel-3

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