Coastal Waveforms Research Articles

Coastal Waveform Retracking for Synthetic Aperture Altimeters Using a Multiple Optimization Parabolic Cylinder Algorithm

The importance of monitoring sea level in coastal zones becomes more and more obvious in the era of global climate change, because, in coastal zones, although satellite altimetry is an ideal tool in measuring sea level over open ocean, but its accuracy often decreases significantly at coast due to land contamination. Although the accuracy of waveform processing algorithms for synthetic aperture altimeters has been improved in the last decade, the computational speed is still not fast enough to meet the requirements of real-time processing, and the accuracy cannot meet the needs of nearshore areas within 1 km from the coast. To improve the efficiency and accuracy in the coastal zone, this study proposed an innovative waveform retracking scheme for the coastal zone based on a multiple optimization parabolic cylinder algorithm (MOPCA) integrated with machine learning algorithms such as recurrent neural network and Bayesian estimation. The algorithm was validated using 153-pass repeat cycle data from Sentinel-6 over Qianliyan Island and Hong Kong–Wanshan Archipelago. The computational speed of the proposed algorithm was four to five times faster than the current operational synthetic aperture radar (SAR) retracking algorithm, and its accuracy within 0–20 km from the island was comparable to the most popular SAMOSA+ algorithm, better than the official data product provided by Sentinel-6. Especially, the proposed algorithm demonstrates remarkable stability in the sense of proceeding speed. It maintains consistent performance, even when dealing with intricate wave patterns within a proximity of 1 km from the coast. The results showed that the proposed scheme greatly improved the quality of coastal altimetry waveform retracking.

A Partial Reconstruction Method for SAR Altimeter Coastal Waveforms Based on Adaptive Threshold Judgment

Due to land contamination and human activities, the sea surface height (SSH) data retrieved from altimeter coastal waveforms have poor precision and cannot provide effective information for various tasks. The along-track high-resolution characteristic of the new synthetic aperture radar (SAR) altimeter makes the retracking methods of traditional coastal waveforms difficult to apply. This study proposes a partial reconstruction method for SAR altimeter coastal waveforms. By making adaptive threshold judgments of model matching errors and repairing the contaminated waveforms based on the nearest linear prediction, the success rate of retracking and retrieval precision of SSH are significantly improved. The data from the coastal experimental areas of the Sentinel-3B satellite altimeter are processed. The results indicate that the mean proportion of waveform quality improvement brought by partial reconstruction is 80.30%, the mean retracking success rate of reconstructed waveforms is 85.60%, and the mean increasing percentage is 30.98%. The noise levels of SSH data retrieved by different methods are calculated to evaluate the processing precision. It is shown that the 20 Hz SSH precisions of the original and reconstructed coastal waveforms are 12.75 cm and 6.32 cm, respectively, and the corresponding 1 Hz SSH precisions are 2.85 cm and 1.41 cm, respectively. The results validate that the proposed partial reconstruction method has improved the SSH precision by a factor of two, and the comparison results with mean sea surface (MSS) model data further verify this conclusion.

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal using a single radar altimeter and retracking technique due to the diversity and complexity of coastal waveforms. To solve this issue, we proposed an approach of estimating water level of the coastal zone in Beibu Gulf, China, by combination of waveform classifications and multiple sub-waveform retrackers. This paper stacked Random Forest (RF), XGBoost and CatBoost algorithms for building an ensemble learning (SEL) model to classify coastal waveforms, and further evaluated the performance of three retracking strategies in refining waveforms using Cryosat-2, SARAL, Sentinel-3 altimeters. We compared the estimation accuracy of the coastal water levels between the single altimeter and synergistic multi-altimeter, and combined Breaks for Additive Season and Trend (BFAST), Mann-Kendall mutation test (MK) with Long Short-Term Memory (LSTM) algorithms to track the historical change process of coastal water levels, and predict its future development trend. This paper found that: (1) The SEL algorithm achieved high-precision classification of different coastal waveforms with an average accuracy of 0.959, which outperformed three single machine learning algorithms. (2) Combination of Threshold Retracker and ALES+ Retracker (TR_ALES+) achieved the better retracking quality with an improvement of correlation coefficient (R, 0.089~0.475) and root mean square error (RMSE, 0.008∼ 0.029 m) when comparing to the Threshold Retracker & Primary Peak COG Retracker and Threshold Retracker & Primary Peak Threshold Retracker. (3) The coastal water levels of Cryosat-2, SARAL, Sentinel-3 and multi-altimeter were in good agreement (R>0.66, RMSE<0.135m) with Copernicus Climate Change Service (C3S) water level. (4) The coastal water levels of the Beibu Gulf displayed a slowly rising trend from 2011 to 2021 with an average annual growth rate of 8mm/a, its lowest water level focused on May-August, the peak of water level was in October-November, and the average annual growth rate of water level from 2022-2031 was about 0.6mm/a. These results can provide guidance for scientific monitoring and sustainable management of coastal zones.

Coastal Waveform Retracking for HY-2B Altimeter Data by Determining the Effective Trailing Edge and the Low Noise Leading Edge

As an important remote sensing technology, satellite altimetry provides a large amount of observations of sea surface height over the global ocean. In coastal areas, the accuracy of satellite altimetry data decreases greatly due to issues arise in the vicinity of land, related to poorer geophysical corrections and artifacts in the altimeter reflected signals linked to the presence of land within the instrument footprint. To improve the application of HY-2B altimetry data in coastal areas, this study proposes a coastal waveform retracking strategy for HY-2B altimetry mission, which depends on the effective trailing edge and the leading edge, which are less affected by coastal ‘contamination’, to retrieve accurate waveform information. The HY-2B pass 323 and pass 196 data are reprocessed, and the accuracy of the reprocessing results in the range of 0–40 km offshore is validated against the tide gauge data and compared with the HY-2B standard SGDR data. According to the analysis conclusion, the accuracy of the reprocessed data is higher than that of the SGDR data and has good performance within 15 km offshore. For the pass 323, the mean value of correlation coefficient and RMS of the reprocessed data against the corresponding tide gauge data are 0.893 and 45.1 cm, respectively, in the range within 0–15 km offshore, and are 0.86 and 33.6 cm, respectively, in the range beyond 15 km offshore. For the pass 196, the mean value of correlation coefficient and RMS of the reprocessed data against the corresponding tide gauge data in the range within 0–12 km offshore are 0.84 and 33.0 cm, respectively, and in the range within 0–5 km offshore to the island are 0.90 and 29.3 cm, respectively, and in the range beyond 5 km offshore to the island are 0.92 and 36.2 cm, respectively, which are all better than the corresponding values of the SGDR data, especially in the range closed to the land. The results indicate that the proposed coastal waveform retracking strategy for HY-2B altimetry greatly improves the quality of HY-2B altimetry data in coastal areas.

Quantifying the precision of retracked Jason-2 sea level data in the 0–5 km Australian coastal zone

This paper aims to quantify the precision of retracked Jason-2 altimeter sea level data (2008–2016) in the 0–5 km Australian coastal zone. A new retracking strategy has been developed to achieve the highest possible precision of coastal sea-level data. Coastal waveforms were classified into four groups according to the adaptability of dedicated coastal retrackers, from which each group was reprocessed using an optimal retracker. A modified Brown model was introduced to reprocess the quasi-specular waveforms over calm waters. A seamless transition of sea surface heights from different retrackers was achieved by estimating and removing the significant wave height dependent height differences. In order to generate the 20-Hz sea level anomaly (SLA) and total water level envelope (TWLE) at the coast, the regional along-track mean sea surface (MSS) with a high spatial resolution (~300 m) was estimated. Compared to the global MSS model, the use of the along-track MSS has dramatically reduced the SLA variance by 140 cm2 in the 0–15 km coastal strip.The results from the evaluation of data precision for Jason-2 ground tracks and the validation against tide gauges show that this new retracking strategy can retrieve more reliable sea level data nearshore. The precision of 20-Hz sea level data in the 0–5 km Australian coastal strip ranges typically from 5 cm to 6 cm in most coastal areas, which is only ~1 cm lower than that beyond 5 km off the coastline. However, in Northwest Australian and some coastal regions, the data precision drops to ≥7 cm due partly to the specific coastal sea states and topography. In addition, it is found that the altimeter and tide gauge TWLE time series have a high correlation (>0.8) in the 0–5 km distance band, indicating that coastal sea-level data are useful for applications such as estimation of river plumes, long-term variation of water level in lakes and rivers, and the analysis of storm surges.

Sea Surface Heights and Marine Gravity Determined from SARAL/AltiKa Ka-band Altimeter Over South China Sea

SARAL/AltiKA (SRL) is the first altimetry satellite with a Ka-band altimeter. To validate the advantages of the Ka-band altimeter over traditional Ku-band altimeters in marine geodetic applications, a comprehensive analysis is carried out over the South China Sea (SCS) (0–30° N, 105–125° E) from three aspects, namely the influence of load on waveforms, the precision of sea surface heights (SSHs), and the precision of altimeter-derived marine gravity field. Coastal waveforms of SRL, Jason-2, and CryoSat-2 are separately compared with corresponding ocean-type waveforms. The radius of coastal influence on SSHs of SRL/exact repeat mission (SRL/ERM) is the smallest, being about 3 km. Crossover discrepancies, global mean sea surface models, and tide gauge data are used to assess the precision of altimetric SSHs. Compared with the SSH precision of Ku-band Jason-2/ERM, the SSH precision of Ka-band SRL/ERM is 4.6% higher over the SCS and 10% higher in offshore areas. Gridded gravity anomalies are derived from measurements of SRL/drifting phase (SRL/DP) and CryoSat-2 through the inverse Vening-Meinesz formula, respectively. According to the assessment by shipborne gravity data and global marine gravity models, the precision of SRL/DP-derived gravity is higher than that of CryoSat-2-derived gravity over the SCS, especially in offshore areas. In some cycles, ground tracks of SRL/ERM have large drifting of more than 10 km from nominal tracks. The results show that the Ka-band altimeter of SRL has better precision in SSHs and marine gravity recovery than the Ku-band altimeter over the SCS, particularly in offshore areas.

Coastal Waveform Retracking in the Slick-Rich Sulawesi Sea of Indonesia, Based on Variable Footprint Size with Homogeneous Sea Surface Roughness

Waveforms of radar altimeters are often corrupted due to heterogeneous sea surface roughness within footprints, such as slicks. In past studies, subwaveform retrackers such as the adaptive leading edge subwaveform retracker (ALES) which use only a section of the waveform have been proposed. However, it is difficult to choose a reasonable estimation window from an individual waveform. In the present study, a post-processed subwaveform retracker is proposed which identifies the waveforms of surrounding along-track points. The size of the estimation window is variable and is determined to keep the sea surface roughness within the corresponding footprint homogeneous. The method was applied to seven years of 20 Hz Jason-2 altimeter data over the slick-rich Sulawesi Sea of Indonesia and compared with ALES and sensor geophysical data record (SGDR) products. The standard deviation of the sea surface dynamic heights was around 0.13 m, even without spatial smoothing or some geophysical corrections. This is only 75% and 25% of the ALES and SGDR results, respectively. Moreover, all retrievals of the range, SWH, and sigma0 include less outliers than the other products. These results indicate that the variable estimation windows determined in the present study can adapt well to the variation of sea surface roughness.

Improving Jason-2 Sea Surface Heights within 10 km Offshore by Retracking Decontaminated Waveforms

It is widely believed that altimetry-derived sea surface heights (SSHs) in coastal zones are seriously degraded due to land contamination in altimeter waveforms from non-marine surfaces or due to inhomogeneous sea state conditions. Spurious peaks superimposed in radar waveforms adversely impact waveform retracking and hence require tailored algorithms to mitigate this problem. Here, we present an improved method to decontaminate coastal waveforms based on the waveform modification concept. SSHs within 10 km offshore are calculated from Jason-2 data by a 20% threshold retracker using decontaminated waveforms (DW-TR) and compared with those using original waveforms and modified waveforms in four study regions. We then compare our results with retracked SSHs in the sensor geophysical data record (SGDR) and with the state-of-the-art PISTACH (Prototype Innovant de Système de Traitement pour les Applications Côtières et l’Hydrologie) and ALES (Adaptive Leading Edge Subwaveform) products. Our result indicates that the DW-TR is the most robust retracker in the 0–10 km coastal band and provides consistent accuracy up to 1 km away from the coastline. In the four test regions, the DW-TR retracker outperforms other retrackers, with the smallest averaged standard deviations at 15 cm and 20 cm, as compared against the EGM08 (Earth Gravitational Model 2008) geoid model and tide gauge data, respectively. For the SGDR products, only the ICE retracker provides competitive SSHs for coastal applications. Subwaveform retrackers such as ICE3, RED3 and ALES perform well beyond 8 km offshore, but seriously degrade in the 0–8 km strip along the coast.

Coastal Waveform Retracking for Jason-2 Altimeter Data Based on Along-Track Echograms around the Tsushima Islands in Japan

Although the Brown mathematical model is the standard model for waveform retracking over open oceans, due to heterogeneous surface reflections within altimeter footprints, coastal waveforms usually deviate from open ocean waveform shapes and thus cannot be directly interpreted by the Brown model. Generally, the two primary sources of heterogeneous surface reflections are land surfaces and bright targets such as calm surface water. The former reduces echo power, while the latter often produces particularly strong echoes. In previous studies, sub-waveform retrackers, which use waveform samples collected from around leading edges in order to avoid trailing edge noise, have been recommended for coastal waveform retracking. In the present study, the peaky-type noise caused by fixed-point bright targets is explicitly detected and masked using the parabolic signature in the sequential along-track waveforms (or, azimuth-range echograms). Moreover, the power deficit of waveform trailing edges caused by weak land reflections is compensated for by estimating the ratio of sea surface area within each annular footprint in order to produce pseudo-homogeneous reflected waveforms suitable for the Brown model. Using this method, altimeter waveforms measured over the Tsushima Islands in Japan by the Ocean Surface Topography Mission (OSTM)/Jason-2 satellite are retracked. Our results show that both the correlation coefficient and root mean square difference between the derived sea surface height anomalies and tide gauge records retain similar values at the open ocean (0.9 and 20 cm) level, even in areas approaching 3 km from coastlines, which is considerably improved from the 10 km correlation coefficient limit of the conventional MLE4 retracker and the 7 km sub-waveform ALES retracker limit. These values, however, depend on the topography of the study areas because the approach distance limit increases (decreases) in areas with complicated (straight) coastlines.

Coastal Altimetry Products in the Strait of Gibraltar

This paper analyzes the availability and accuracy of coastal altimetry sea level products in the Strait of Gibraltar. All possible repeats of two sections of the Envisat and AltiKa ground-tracks were used in the eastern and western portions of the strait. For Envisat, along-track sea level anomalies (SLAs) at 18-Hz posting rate were computed using ranges from two sources, namely, the official Sensor Geophysical Data Records (SGDRs) and the outputs of a coastal waveform retracker, the Adaptive Leading Edge Subwaveform (ALES) retracker; in addition, SLAs at 1 Hz were obtained from the Centre for Topographic studies of the Ocean and Hydrosphere (CTOH). For AltiKa, along-track SLA at 40 Hz was also computed both from SGDR and ALES ranges. The sea state bias correction was recomputed for the ALES-retracked Envisat SLA. The quality of these altimeter products was validated using two tide gauges located on the southern coast of Spain. For Envisat, the availability of data close to the coast depends crucially on the strategy followed for data screening. Most of the rejected data were due to the radar instrument operating in a low-precision nonocean mode. We observed an improvement of about 20% in the accuracy of the Envisat SLAs from ALES compared to the standard (SGDR) and the reprocessed CTOH data sets. AltiKa shows higher accuracy, with no significant differences between SGDR and ALES. The use of products from both missions allows longer times series, leading to a better understanding of the hydrodynamic processes in the study area.

ALES: A multi-mission adaptive subwaveform retracker for coastal and open ocean altimetry

Satellite altimetry has revolutionised our understanding of ocean dynamics thanks to frequent sampling and global coverage. Nevertheless, coastal data have been flagged as unreliable due to land and calm water interference in the altimeter and radiometer footprint and uncertainty in the modelling of high-frequency tidal and atmospheric forcing.Our study addresses the first issue, i.e. altimeter footprint contamination, via retracking, presenting ALES, the Adaptive Leading Edge Subwaveform retracker. ALES is potentially applicable to all the pulse-limited altimetry missions and its aim is to retrack both open ocean and coastal data with the same accuracy using just one algorithm.ALES selects part of each returned echo and models it with a classic “open ocean” Brown functional form, by means of least square estimation whose convergence is found through the Nelder–Mead nonlinear optimisation technique. By avoiding echoes from bright targets along the trailing edge, it is capable of retrieving more coastal waveforms than the standard processing. By adapting the width of the estimation window according to the significant wave height, it aims at maintaining the accuracy of the standard processing in both the open ocean and the coastal strip.This innovative retracker is validated against tide gauges in the Adriatic Sea and in the Greater Agulhas System for three different missions: Envisat, Jason-1 and Jason-2. Considerations of noise and biases provide a further verification of the strategy. The results show that ALES is able to provide more reliable 20-Hz data for all three missions in areas where even 1-Hz averages are flagged as unreliable in standard products. Application of the ALES retracker led to roughly a half of the analysed tracks showing a marked improvement in correlation with the tide gauge records, with the rms difference being reduced by a factor of 1.5 for Jason-1 and Jason-2 and over 4 for Envisat in the Adriatic Sea (at the closest point to the tide gauge).

The Improved Retrieval of Coastal Sea Surface Heights by Retracking Modified Radar Altimetry Waveforms

Measuring sea surface height (SSH) using satellite altimetry in coastal ( from coasts) and shallow water region has long been a challenge since the radar altimeter waveforms are often contaminated by complex coastal topography and do not conform to theoretical Brown waveform shapes. The land contamination or surface variation due to ocean dynamics induce spurious peaks in altimeter waveforms that deviate from Brown's theoretical model as the altimeter footprint approaches or leaves the shoreline. These spurious peaks should be mitigated to minimize the error in the determination of the leading edge and associated track offset in the waveform retracking process. Here, we introduce a novel algorithm to modify coastal waveforms (0.5-7 km from coasts, using 20 Hz altimetry data), thus improving coastal data coverage and accuracy. We apply our processing algorithm and use various retrackers to compare retrieved coastal SSHs in four study regions in North America, using both Envisat and Jason-2 altimetry. The retrieved altimetry data in the 1-7 km coastal zone indicate that the 20% Threshold retracker with modified waveform has a RMSE of 21 cm as compared with in situ tide gauge data, which corresponds to a 63% improvement in accuracy compared to the use of the original deep-ocean waveform retracker.

Neural network for tsunami and runup forecast

This paper examines the use of neural network to model nonlinear tsunami processes for forecasting of coastal waveforms and runup. The three‐layer network utilizes a radial basis function in the hidden, middle layer for nonlinear transformation of input waveforms near the tsunami source. Events based on the 2006 Kuril Islands tsunami demonstrate the implementation and capability of the network. Division of the Kamchatka‐Kuril subduction zone into a number of subfaults facilitates development of a representative tsunami dataset using a nonlinear long‐wave model. The computed waveforms near the tsunami source serve as the input and the far‐field waveforms and runup provide the target output for training of the network through a back‐propagation algorithm. The trained network reproduces the resonance of tsunami waves and the topography‐dominated runup patterns at Hawaii's coastlines from input water‐level data off the Aleutian Islands.