Validation and Intercomparison of SARAL/AltiKa and PISTACH-Derived Coastal Wave Heights Using <i>In-Situ</i> Measurements

Hithin, N. K.; Remya, P. G.; Nair, T. M. Balakrishnan; Harikumar, R.; Kumar, Raj; Nayak, Shailesh

doi:10.1109/jstars.2015.2418251

Cited by 24 publications

(17 citation statements)

References 17 publications

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“…Many recent studies have focussed on improving performance of traditional nadir altimetry over coastal regions by developing and assessing dedicated coastal retracking algorithms [6,17,18]. There is the potential that some of these algorithms could be adapted to improve wave height estimates from S3A PLRM in the coastal zone, making use of appropriate quality control of the data.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, under very calm conditions, sheltered bays may provide an almost mirror-like surface, generating specular returns in the waveforms [15,16]. To overcome such limitations, several studies have developed and assessed dedicated coastal retracking algorithms [6,17,18]. These have shown an overall improved accuracy of SWH from LRM altimetry in coastal regions, although performances on a case-by-case basis remain dependent on the specific coastal morphology and the angle between the satellite track and the coastline.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Sentinel-3A Wave Height Observations Near the Coast of Southwest England

Nencioli

Quartly

2019

Remote Sensing

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Due to the smaller ground footprint and higher spatial resolution of the Synthetic Aperture Radar (SAR) mode, altimeter observations from the Sentinel-3 satellites are expected to be overall more accurate in coastal areas than conventional nadir altimetry. The performance of Sentinel-3A in the coastal region of southwest England was assessed by comparing SAR mode observations of significant wave height against those of Pseudo Low Resolution Mode (PLRM). Sentinel-3A observations were evaluated against in-situ observations from a network of 17 coastal wave buoys, which provided continuous time-series of hourly values of significant wave height, period and direction. As the buoys are evenly distributed along the coast of southwest England, they are representative of a broad range of morphological configurations and swell conditions against which to assess Sentinel-3 SAR observations. The analysis indicates that SAR observations outperform PLRM within 15 km from the coast. Within that region, regression slopes between SAR and buoy observations are close to the 1:1 relation, and the average root mean square error between the two is 0.46 ± 0.14 m. On the other hand, regression slopes for PLRM observations rapidly deviate from the 1:1 relation, while the average root mean square error increases to 0.84 ± 0.45 m. The analysis did not identify any dependence of the bias between SAR and in-situ observation on the swell period or direction. The validation is based on a synergistic approach which combines satellite and in-situ observations with innovative use of numerical wave model output to help inform the choice of comparison regions. Such an approach could be successfully applied in future studies to assess the performance of SAR observations over other combinations of coastal regions and altimeters.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Sentinel-3A Wave Height Observations Near the Coast of Southwest England

Nencioli

Quartly

2019

Remote Sensing

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“…Typically, LRM altimetry performs poorly at distances up to 20 km from the coast (Passaro et al, 2015). The smaller footprint of SAR altimetry and SARAL-Altika reduces this problem (Hithin et al, 2015;Dinardo et al, 2018). As for noise, it can be reduced by improving on the tracking methods (Passaro et al, 2015;Ardhuin et al, 2017a) and filtering the data (Quilfen et al, 2018).…”

Section: Significant Wave Height From Altimetersmentioning

confidence: 99%

Observing Sea States

et al. 2019

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Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

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“…To overcome the problem, numerous state-of-the-art retracking algorithms have been developed to improve altimeter SWHs at the coast. The performance of retrackers has been validated through comparisons of retracked altimeter SWHs with in situ waverider buoy's wave data [2,5,10]. Among these work, the adaptive leading edge subwaveform retracker (ALES) by Passaro et al [11], originally designed to retrieve high quality sea surface heights (SSHs) in coastal regions, shows great superiority in estimation of the SWH data [5].…”

Section: Introductionmentioning

confidence: 99%

“…Among these work, the adaptive leading edge subwaveform retracker (ALES) by Passaro et al [11], originally designed to retrieve high quality sea surface heights (SSHs) in coastal regions, shows great superiority in estimation of the SWH data [5]. Other coastal projects, such as Coastal Altimetry (COASTALT) and Processing Innovative System Prototype for Coastal and Hydrology Applications (PISTACH), also make contributions to minimize the wave data gaps within 50 km to the coast [2,10].…”

Section: Introductionmentioning

confidence: 99%

Validation of Improved Significant Wave Heights from the Brown-Peaky (BP) Retracker along the East Coast of Australia

Peng¹,

Deng²

2018

Remote Sensing

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Improved significant wave heights (SWHs) along the east coast of Australia have been estimated using the parameters resolved by a Brown-peaky (BP) retracker through reprocessing of three years of Jason-1 altimetric waveforms. The BP-estimated SWHs are validated against eight waverider buoys along the coast, and compared with the SWHs estimated by the standard four-parameter maximum likelihood estimator (MLE4). When assessing 1 Hz coastal SWHs for distances from 12 km to the coast, mean standard deviations (STDs) of BP SWHs vary from ca. 0.5 m to 0.9 m, while those of MLE4 SWHs increase from ca. 0.6 m to ca. 2.3 m, indicating a dramatically drop in the quality of MLE4-derived SWHs at the coast. The BP retracker has retrieved ca. 80% of 1 Hz coastal SWHs, which are more than those (ca. 50%) by the standard MLE4. The validation of 1 Hz SWHs is performed by calculating the along-altimeter-track pointwise bias, STD and correlation coefficient between altimetry and buoys. The results show that within 30 km off the coast the BP dataset has better agreement with buoy's wave heights than the SGDR MLE4 dataset in terms of the BP's small absolute biases and STDs, as well as high correlation coefficients.

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Validation and Intercomparison of SARAL/AltiKa and PISTACH-Derived Coastal Wave Heights Using In-Situ Measurements

Cited by 24 publications

References 17 publications

Evaluation of Sentinel-3A Wave Height Observations Near the Coast of Southwest England

Evaluation of Sentinel-3A Wave Height Observations Near the Coast of Southwest England

Observing Sea States

Validation of Improved Significant Wave Heights from the Brown-Peaky (BP) Retracker along the East Coast of Australia

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