Subwaveform Retracker Research Articles

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.

The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast

In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.

Advances in NE-Atlantic coastal sea level change monitoring by Delay Doppler altimetry

Abstract A significant part of the World population lives in the coastal zone, which is affected by sea level rise and extreme events. Consistent and precise new measurements are needed to assess and predict these changes. New altimeter missions equipped with Synthetic Aperture Radar (SAR) mode provide more accurate sea level heights. In this work we analyse their impacts on the estimation of the coastal sea level variability in the last 10 km. First, by analysing various standard and improved SAR altimetric products it is found that SAR altimetry will reduce the minimum usable distance from five to three kilometres. The best performance is achieved with the SAR coastal retrackers SAMOSA+ and SAMOSA++. A comparable performance is obtained in low resolution Reduced SAR (RDSAR) mode with the Spatio-Temporal Altimeter sub-waveform Retracker (STAR). In both cases, sea level heights are recovered with 4 cm accuracy up to 3 km from the coast at the Helgoland station, and the accuracy does not decrease with the distance to coast. In estuaries and coastal zones with hight tidal regimes, the discrepancy between altimetry and in-situ observations remains large (40 cm standard deviation difference (stdd) with SAR-SAM+). CryoSat-2 and Sentinel-3A have similar accuracy, despite their different repeat cycle and sampling, which require a different post-processing. The monthly coastal variability from the SAR-SAM+ product agrees most favourably with the NEMO-WAM model, with stdd 3.9 and correlation 0.90 for Sentinel-3A. Instead, the maximum departure between altimeter data products is between SAR-SAM+ and RDSAR-TALES CryoSat-2 data (stdd 2.3 and correlation 0.96). An average trend of about 3 ± 1.3 mm/yr has been detected using low resolution altimetry at ninetheen in-situ stations along the German coast over time intervals longer than 15 years. The difference of the trends of altimetry and tide gauge co-located time-series (al-tg) agrees with the GNSS rates within 1.5 mm/yr at half of the co-located locations, with error of al-tg larger than the error of the GPS rate by a factor bigger than two. The larger departure between monthly tide gauge and LRM altimetric time-series as between tide gauge and SAR altimetric time-series confirms the higher accuracy of SAR data compared to LRM. Finally, the sea level trends of the merged LRM and SAR altimetry time-series are consistent with the LRM trends.

Capability of Jason-2 Subwaveform Retrackers for Significant Wave Height in the Calm Semi-Enclosed Celebes Sea

Satellite altimetry is a unique system that provides repeated observations of significant wave height (SWH) globally, but its measurements could be contaminated by lands, slicks, or calm water with smooth surface. In this study, capability of subwaveform retrackers against 20 Hz Jason-2 measurements is examined in the calm Celebes Sea. Distances between contamination sources and Jason-2 observation points can be determined using sequentially assembled adjacent waveforms (radargram). When no contamination sources are present within a Jason-2 footprint, subwaveform retrackers are in excellent agreement with the Sensor Geophysical Data Records (SGDR) MLE4 retracker that uses full-length waveforms, except that Adaptive Leading Edge Subwaveform (ALES) retracker has a positive bias in a calm sea state (SWH < 1 m), which is not unusual in the Celebes Sea. Meanwhile, when contamination sources exist within 4.5 km from Jason-2 observation points, SGDR occasionally estimates unrealistically large SWH values, although they could be partly eliminated by sigma0 filters. These datasets are then compared with WAVEWATCH III model, resulting in good agreement. The agreement becomes worse if swells from the Pacific is excluded in the model, suggesting constant presence of swells despite the semi-enclosed nature. In addition, outliers are found related with locally-confined SWH events, which could be inadequately represented in the model.

Space‐Time Evolution of Greenland Ice Sheet Elevation and Mass From Envisat and GRACE Data

AbstractPrecise measurements of height changes (HCs) are important for improved estimates of mass balance of the Greenland Ice Sheet (GrIS). Here we determine 10 years of precise, high‐resolution HCs of the GrIS from Envisat radar altimeter using a subwaveform retracker and a modified repeat‐track method. The HCs show clear seasonal changes and monotonic declines over glaciers on the coasts such as Zachariae Isstrøm. We enhance mass change estimates from Gravity Recovery and Climate Experiment (GRACE) data using HCs and densities from interannual correlations between GRACE‐derived mass changes and HCs. We estimate the mass changes of eight drainage basins with our combined mass change. The largest mass change between 2002 and 2012 occurred in the northwest basin and the smallest in the northeast basin. We separate the ice and snow HC rates to derive a ratio (f) between them to characterize the relative importance of ice or snow to mass change. The snow HC rates are mostly positive over the GrIS, except on the margins of the west coast and Zachariae Isstrøm. The mean ice HC rate is −6.6 ± 3.9 cm/year over 2002–2006, which accelerated to −13.9 ± 2.4 cm/year over 2007–2012. The f factors show a clear post‐2006 ice dominance in the GrIS mass loss, particularly on the west coast, with a mean 91.4% ice contribution over 2002–2006, increasing to 94.5% over 2007–2012. This indicates increasing mass loss after 2006. A coincident radar altimeter and gravimetry mission is important for studying mass balance and separating snow and ice contributions over space and time.

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.

Altimetry-based sea level trends along the coasts of Western Africa

We present results of contemporary coastal sea level changes along the coasts of Western Africa, obtained from a dedicated reprocessing of satellite altimetry data done in the context of the ESA ‘Climate Change Initiative’ sea level project. High sampling rate (20 Hz) sea level data from the Jason-1 and Jason-2 missions over a 14-year-long time span (July 2002 to June 2016) are considered. The data were first retracked using the ALES adaptative leading edge subwaveform retracker. The X-TRACK processing system developed to optimize the completeness and accuracy of the corrected sea level time series in coastal ocean areas was then applied. From the 14-year long sea level time series finally obtained, we estimate sea level trends along the Jason-1 & 2 tracks covering the study region. We analyze regional variations in sea level trends, with a focus on the changes observed between the open ocean to the coastal zone. Compared to the conventional 1 Hz sea level products dedicated to open ocean applications, the retracked 20 Hz measurements used in this study allow us to retrieve valid sea level information much closer to the coast (less than 3–4 km to the coast, depending on the satellite track location). The main objective of this study is twofold: (1) provide sea level products in the coastal areas from reprocessed altimetry data and (2) check whether sea level changes at the coast differ from that reported in the open ocean with conventional altimetry products. In the selected region, results show that over the study period, sea level trends observed near the coast of Western Africa are significantly different than offshore trends. In order to assess the robustness of the results, detailed analyses are performed at several locations to discriminate between possible drifts in the geophysical corrections and physical processes potentially able to explain the sea level changes observed close to the coast.

Wind-induced cross-strait sea level variability in the Strait of Gibraltar from coastal altimetry and in-situ measurements

Coastal altimetry products are available and are being extensively validated. Their accuracy has been assessed in many coastal zones around the world and they are ready for exploitation near the shore. This opens a variety of applications of the sea level data obtained from the specific reprocessing of radar altimeter signals in the coastal strip. In this work, we retracked altimeter waveforms of the European Space Agency satellites: ERS-2 RA and Envisat RA-2 from descending track (#0360) over the eastern side of the Strait of Gibraltar using the Adaptive Leading Edge Sub-waveform (ALES) retracker. We estimated along-track Sea Level Anomaly (AT_SLA) profiles (RA-2) at high posting rate (18 Hz) using improved range and geophysical corrections. Tides were removed with a global model (DTU10) that displays a good performance in the study area: the mean root square sum (RSS) of the main constituents obtained with DTU10 and 11 tide gauge stations was 4.3 cm in agreement with the RSS using a high-resolution local hydrodynamic model (UCA2.5D) (4.2 cm). We also estimated a local mean sea surface by reprocessing ERS-2/Envisat waveforms (track #0360) with ALES. The use of this local model gave more realistic AT_SLA than the values obtained with the global model DTU15MSS. Finally, the along-track Absolute Dynamic Topography (AT_ADT) was estimated using a local Mean Dynamic Topography obtained with the local hydrodynamic model UCA2.5D. We analysed the cross-strait variability of the sea level difference between the African/Spanish coasts along the selected track segment. This was compared to the sea level cross-strait difference from the records of two tide gauges located in the African (Ceuta) and Spanish (Tarifa) coasts. The sea level differences from altimetry and tide gauges were linked to the zonal component of the wind. We found a positive and significant (>95% c.l.) correlation between easterlies/westerlies and positive/negative cross-strait sea level differences between the southern and northern coasts of the Strait in both datasets (altimetry: r = 0.54 and in-situ: r = 0.82).

ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters

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.

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.

Improved Sea Surface Height From Satellite Altimetry in Coastal Zones: A Case Study in Southern Patagonia

High-resolution 20-Hz Jason-2 satellite altimetry data obtained from crossing tracks numbered 52 and 189 in San Matias Gulf, Argentina, are compared with a 22-month-long time series of sea level measured by a bottom pressure recorder. It was deployed 1.3 km from the nominal intersection of the two tracks and 0.9 km from the coast. Results show that by improving retracking and tidal modeling, satellite altimetry data become more accurate close to the coast. Indeed, a larger number of reliable data are obtained up to 1.6 km from the coast when satellite data are retracked using adaptive leading edge subwaveform retracker (ALES) rather than using the classic Brown model. The tidal model that showed the lowest root sum square (RSS) of the difference between the in situ and the modeled tidal amplitude and phase is TPXO8 (RSS 4.8 cm). Yet, the lowest difference from in situ tidal constituents is obtained by harmonic analysis of the available 23-year-long 1-Hz altimetry dataset (RSS 4.1 cm), highlighting the potential of altimetry data to compute tides. Considering ALES retracking and TPXO8 tidal correction for the 20-Hz Jason-2 data, we finally show that it is possible to retrieve 70% more data and to improve correlation with in situ measurements from 0.79 to 0.95. The sea level anomaly obtained this way has a root mean square difference from in situ data of only 13 cm as close as 4 km from the coast. Overall, the analysis performed indicates that satellite altimetry data can be greatly improved, even in complex macrotidal coastal regions.

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.

Development of water level estimation algorithms using SARAL/Altika dataset and validation over the Ukai reservoir, India

Water level was estimated, using AltiKa radar altimeter onboard the SARAL satellite, over the Ukai reservoir using modified algorithms specifically for inland water bodies. The methodology was based on waveform classification, waveform retracking, and dedicated inland range corrections algorithms. The 40-Hz waveforms were classified based on linear discriminant analysis and Bayesian classifier. Waveforms were retracked using Brown, Ice-2, threshold, and offset center of gravity methods. Retracking algorithms were implemented on full waveform and subwaveforms (only one leading edge) for estimating the improvement in the retrieved range. European Centre for Medium-Range Weather Forecasts (ECMWF) operational, ECMWF re-analysis pressure fields, and global ionosphere maps were used to exactly estimate the range corrections. The microwave and optical images were used for estimating the extent of the water body and altimeter track location. Four global positioning system (GPS) field trips were conducted on same day as the SARAL pass using two dual frequency GPS. One GPS was mounted close to the dam in static mode and the other was used on a moving vehicle within the reservoir in Kinematic mode. In situ gauge dataset was provided by the Ukai dam authority for the time period January 1972 to March 2015. The altimeter retrieved water level results were then validated with the GPS survey and in situ gauge dataset. With good selection of virtual station (waveform classification, back scattering coefficient), Ice-2 retracker and subwaveform retracker both work better with an overall root-mean-square error <15 cm. The results support that the AltiKa dataset, due to a smaller foot-print and sharp trailing edge of the Ka-band waveform, can be utilized for more accurate water level information over inland water bodies.

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.

Cross-calibrating ALES Envisat and CryoSat-2 Delay–Doppler: A coastal altimetry study in the Indonesian Seas

A regional cross-calibration between the first Delay–Doppler altimetry dataset from CryoSat-2 and a retracked Envisat dataset is here presented, in order to test the benefits of the Delay–Doppler processing and to expand the Envisat time series in the coastal ocean. The Indonesian Seas are chosen for the calibration, since the availability of altimetry data in this region is particularly beneficial due to the lack of in situ measurements and its importance for global ocean circulation. The Envisat data in the region are retracked with the Adaptive Leading Edge Subwaveform (ALES) retracker, which has been previously validated and applied successfully to coastal sea level research.The study demonstrates that CryoSat-2 is able to decrease the 1-Hz noise of sea level estimations by 0.3cm within 50km of the coast, when compared to the ALES-reprocessed Envisat dataset. It also shows that Envisat can be confidently used for detailed oceanographic research after the orbit change of October 2010. Cross-calibration at the crossover points indicates that in the region of study a sea state bias correction equal to 5% of the significant wave height is an acceptable approximation for Delay–Doppler altimetry.The analysis of the joint sea level time series reveals the geographic extent of the semiannual signal caused by Kelvin waves during the monsoon transitions, the larger amplitudes of the annual signal due to the Java Coastal Current and the impact of the strong La Niña event of 2010 on rising sea level trends.

Initial Examination of AltiKa's Individual Echoes

The AltiKa altimeter records the reflection of Ka-band radar pulses from the Earth's surface, with the commonly used waveform product involving the summation of 96 returns to provide average echoes at 40 Hz. Occasionally there are one-second recordings of the complex individual echoes (IEs), which facilitate the evaluation of on-board processing and offer the potential for new processing strategies. Our investigation of these IEs over the ocean confirms the on-board operations, whilst noting that data quantization limits the accuracy in the thermal noise region. By constructing average waveforms from 32 IEs at a time, and applying an innovative subwaveform retracker, we demonstrate that accurate height and wave height information can be retrieved from very short sections of data. Early exploration of the complex echoes reveals structure in the phase information similar to that noted for Envisat's IEs.

Validation of Significant Wave Height From Improved Satellite Altimetry in the German Bight

Significant wave height (SWH) is mapped globally through satellite altimetry. SWH estimation is possible because the shape of a pulse-limited altimetric waveform depends on the sea state. The algorithm for SWH also depends on the width of the point target response (PTR) function. Particularly challenging for SWH detection are coastal data, due to land and calm water interference in the altimeter footprint, and low sea states, due to an extremely sharp leading edge in the waveform that is consequently poorly sampled. Here, Adaptive Leading Edge Subwaveform Retracker (ALES), a new algorithm for reprocessing altimetric waveforms, will be validated for SWH estimation in the German Bight. This challenging region presents both low sea state and coastal issues, and an extended network of buoys of the Bundesamt fuer Seeschiffahrt und Hydrographie is available for the in situ validation. Reprocessed data from Envisat, Jason-1, and Jason-2 missions are validated against the three offshore buoys. The in situ validation is applied both at the point nearest to the buoy and at all other points along track. The skill metrics is based on bias, standard deviation, slope of regression line, and number of cycles with correlation larger than 90%. We also tested the impact of the inclusion of two additional waveform samples that are provided in the Envisat Sensor Geophysical Data Records and the adoption of different values for the width of the PTR. Results show that near coast ALES estimations of SWH are generally better correlated with buoy data than standard processed products.

Waveform Retracking for Improving Level Estimations From TOPEX/Poseidon, Jason-1, and Jason-2 Altimetry Observations Over African Lakes

Estimating accurate water heights from complex radar return waveforms, as observed by satellite altimeters over inland water bodies, requires the application of postprocessing algorithms known as retrackers. This study introduces a new retracking algorithm, the Institute for Theoretical Geodesy Retracker (ITGR), which is applied to TOPEX/Poseidon (T/P), Jason-1, and Jason-2 waveforms over African lakes. The ITGR algorithm first analyzes the pattern of returned waveforms to identify retrackable waveforms. To provide range corrections, it then applies a maximum-likelihood estimator to a flexible waveform model, which is constructed based on the number of identified peaks and their position in the waveform. ITGR also adopts an adjustable peak model to deal with both symmetric and asymmetric shaped peaks. As a result, the introduced method exhibits some skill in mitigating the impact of peaks in the waveform pattern. We validated our retracked lake level heights (LLHs) over Lake Volta by comparing them to daily tide gauge and LLHs derived from various retracking algorithms, as well as to LLHs from the Global Reservoir and Lake Monitoring database. Our results over Lake Volta indicate that ITGR LLHs can be obtained with a standard deviation of 33 cm from T/P, 10 cm from Jason-1, and 8 cm from the Jason-2 altimeter; this represents an improved performance when compared to existing retrackers. Investigations over a land-contaminated region of Lake Victoria confirm the superior performance of subwaveform retrackers such as ITGR. Over Lake Naivasha, where mostly specular peak waveform patterns were observed, the performance of these retrackers was found similar to that of conventional threshold retrackers.

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).