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... S PACE-BASED radar altimetry has become nowadays a consolidated Earth Observation technique with a wide range of applications, such as estimating water surface elevations in coastal and inland waters [1], monitoring and forecasting river discharges and extreme flood events [2], studying the changes in snow, ice height and sea-ice elevation in Antarctica [3], [4], estimating the contribution of ice melting to the sea level rise [5], or mapping ice elevation and elevation change using swath interferometry altimetry [6], among others. ...
... Specifically, this improved computational efficiency opens the door for the generation of global products in areas such as swell retrieval and sea ice, where time and precise data analysis is of importance. Also, other application such as global-scale in-land water processing, may benefit from fast algorithms [1], [18]. Finally, the almost real-time processing capability shown in Section VI with just a single CPU core opens the path for future in-flight real time processing of radar altimetry data, which holds interest for many of the applications introduced. ...
The two-dimensional frequency-based omega-K method is known to be a suitable algorithm for Fully-Focused SAR (FF-SAR) radar altimeter processors, as its computational efficiency is much higher than equivalent time-based alternatives without much performance degradation. In this paper we provide a closed-form description of a two-dimensional frequency domain omega-K algorithm specific for instruments such as Poseidon-4 onboard Sentinel-6. The processor is validated with real data from point targets and over open ocean. Applications such as ocean swell retrieval and lead detection are demonstrated, showing the potentiality of the processor for future operational global-scale products.
... Satellite altimetry missions are vital for the monitoring and forecasting of extreme weather events such as tropical cyclones and hurricanes. Near-real-time data from these missions are used to produce sea level anomaly maps, which can provide critical information for forecasting storm surges and predicting the impact of these events on coastal communities [91]. These data are used to assess and monitor the impacts of severe weather events such as hurricanes and floods and to provide critical information that can support emergency response efforts. ...
... Along with the increased number of radar altimetry missions, improved onboard instrumentation, as well as signal processing, the accuracy of altimetry-based MSS models has also improved. Nevertheless, the main drawback of radar altimetry is the degraded performance in the coastal zone due to uncertainties in range and geophysical corrections, and the size of the altimeter footprint [3][4][5]. ...
Radar satellite altimeters enable the determination of the mean sea surface to centimeter accuracy, which can be degraded in coastal areas because of the lack of valid altimetry observations due to land contamination and the altimeter footprint size. In 2018, the National Aeronautics and Space Administration launched ICESat-2, a laser altimetry mission equipped with the Advanced Topographic Laser Altimeter System, providing measurements every 0.7 m in the along-track direction. Taking into account the complexity of the Norwegian coastline, this study aims to evaluate coastal observations from ICESat-2 in order to use it to update the existing mean sea surface for Norway, NMBU18. We, therefore, determined the mean sea surface using only ICESat-2 observations and compared it with mean sea level observations from 23 permanent tide gauges along the entire coast and 21 temporary tide gauges in Norway’s largest and deepest fjord, Sognefjorden. We also included two global mean sea surface models and NMBU18 for comparison. The results have shown that ICESat-2 is indeed able to provide more valid observations in the coastal zone, which can be used to improve the mean sea surface model, especially along the coast.
... Satellite altimetry missions are vital for the monitoring and forecasting of extreme weather events such as tropical cyclones and hurricanes. Near-real-time data from these missions are used to produce sea level anomaly maps, which can provide critical information for forecasting storm surges and predicting the impact of these events on coastal communities [91]. These data are used to assess and monitor the impacts of severe weather events such as hurricanes and floods and to provide critical information that can support emergency response efforts. ...
More than 30 years of observations from an international suite of satellite altimeter missions continue to provide key data enabling research discoveries and a broad spectrum of operational and user-driven applications. These missions were designed to advance technologies and to answer scientific questions about ocean circulation, ocean heat content, and the impact of climate change on these Earth systems. They are also a valuable resource for the operational needs of oceanographic and weather forecasting agencies that provide information to shipping and fishing vessels and offshore operations for route optimization and safety, as well as for other decision makers in coastal, water resources, and disaster management fields. This time series of precise measurements of ocean surface topography (OST)-the "hills and valleys" of the ocean surface-reveals changes in ocean dynamic topography, tracks sea level variations at global to regional scales, and provides key information about ocean trends reflecting climate change in our warming world. Advancing technologies in new satellite systems allows measurements at higher spatial resolution ever closer to coastlines, where the impacts of storms, waves, and sea level rise on coastal communities and infrastructure are manifest. We review some collaborative efforts of international space agencies, including NASA, CNES, NOAA, ESA, and EUMETSAT, which have contributed to a collection of use cases of satellite altimetry in operational and decision-support contexts. The extended time series of ocean surface topography measurements obtained from these satellite altimeter missions, along with advances in satellite technology that have allowed for higher resolution measurements nearer to coasts, has enabled a range of such applications. The resulting body of knowledge and data enables better assessments of storms, waves, and sea level rise impacts on coastal communities and infrastructure amongst other key contributions for societal benefit. Although not exhaustive, this review provides a broad overview with specific examples of the important role of satellite altimetry in ocean and coastal applications, thus justifying the significant resource contributions made by international space agencies in the development of these missions.
... in which C is the speed of light [35]. The waveforms are progressively representative of the powers of the pulses reflected from the surface [8]. Over oceans, where the reflecting surface is usually homogeneous (water only), the waveform shapes are simple and usually follow the Brown model [11]. ...
... The waveforms are progressively representative of the powers of the pulses reflected from the surface [8]. Over oceans, where the reflecting surface is usually homogeneous (water only), the waveform shapes are simple and usually follow the Brown model [11]. ...
Coastal zones are challenging areas for sensing by satellite altimeters because reflected signals from non-water surfaces and from calm sea surfaces in small bays and ports inside the radar footprint lead to erroneous powers in return waveforms. Accordingly, these contaminated waveforms do not follow the so-called Brownmodel in conventional retracking algorithms and fail to derive qualified ranges. Consequently, the estimated water level is erroneous as well. Therefore, selecting an optimized retracker for post-processing waveforms is significantly important to achieve a qualified water level estimation. To find the optimized retracker, we employed a methodology tominimize the effect of erroneous powers on retracked range corrections. To this end, two new approaches were presented, one based on a waveform decontaminationmethod and the other based on a waveformmodificationmethod. We considered the first meaningful sub-waveforms in the decontaminated waveforms and in the modified waveforms to be processed with a threshold retracker. To assess their performance, we also retracked the decontaminated and modified full-waveforms. The first meaningful sub-waveform and full-waveform in the original waveforms were retracked to compare the performance of themodified and decontaminated waveform retracking with the original waveform retracking. To compare the results of our sub-waveform retracking algorithms with those of external sub-waveform retracking algorithms, the (Adaptive Leading Edge
Sub-waveform) ALES database was also used. In our retracking scenarios, we used the Sentinel-3A SRAL Altimeter to estimate the water levels over the study area within 10 km from the coastlines in both the Persian Gulf and the Bay of Biscay from June 2016 to October 2020. The water levels from processing
L2 products were estimated as well. We evaluated our retracking scenarios and L2, as well as the ALES processing results, against the tide gauges. Our analysis showed that within 0–10 km from the coast, the first meaningful sub-waveform of the decontaminated waveforms had the best performance. We reached maximum RMS improvements in this scenario of 53% and 86% over the Persian Gulf and the Bay of Biscay, respectively, in comparison with L2 processing. Over these distances from the coast, the first sub-waveform from the original waveforms and the modified waveforms stayed in the second and third order of performance. The ALES database with an RMS ranging from 13 to 51 cm had a worse performance than all of our sub-waveform retracking scenarios.
... The progress observed in the use of unmanned aerial systems and aquatic vehicles will enhance the collection of good quality data that will contribute to the increasing understanding of processes and phenomena involved and, consequently, the modelling capacity. These habitat mapping technologies can be complemented with other available cutting-edge tools, currently playing an important role in environmental monitoring, such as satellite imagery (Cazenave, 2019;Vignudelli et al., 2019), smartphone apps (Higham & Plater, 2021), acoustic-based river stage recording, among other approaches. ...
Dam construction and streamflow regulation are increasing throughout the world, with impacts in impounded aquatic ecosystems. Hydropower dams, some of them causing a phenomenon called “hydropeaking” during their operation, are known for having a variety of impacts on downstream aquatic biota, particularly fish, and respective habitat. This can result in significant changes, from the community (e.g., fish assemblage structure) to the individual level (e.g., physiological and behavioural adjustments). Researchers and managers involved in the assessment of hydropeaking impacts must be resourceful and use methods that allow their precise evaluation, from large to fine‐scale habitat and biological responses. In the last decades, technological advances allowed for the development of techniques and instrumentations that are increasingly being used in hydropeaking impact and mitigation assessments. This paper aims to provide a review, to researchers and managers interested in this field, of some of the most innovative methods and techniques, involving technology, that are available to study hydropeaking effects on downstream ecosystem, particularly from a fish perspective. We discuss the fundamentals behind such techniques, their advantages, and disadvantages, while also providing practical examples of their application and of the type of results that can be obtained. We finish by discussing some of the shortcomings of these methods and how related technology can evolve to solve current limitations.
... In this context, new resources such as a small radar altimeter operating in a constellation, can provide complementary capabilities. Constellations of radar altimetry satellites are, in fact, an emerging concept [5] that can generate more sea surface topography measurements, be a cost-effective alternative, and a complement to the large missions, providing a greater return on investment [6]. The development of constellations of small satellites, in particular micro and nano satellites (i.e. less than 100 kg and less than 10 kg, respectively), has recently grown considerably. ...
MAGAL lays the foundations for a future constellation of small satellites carrying radar altimeters aiming to improve the understanding of ocean circulation variability at local, regional, and global scales. All necessary tools will be developed, including a new small, low-power altimeter payload and a miniaturized satellite platform, grounded on the Space 4.0 industry, to be manufactured inseries, minimizing production, operational and launch costs. To implement a collaborative constellation, and better tackle the gaps of large radar altimeter programmes, MAGAL will use a Data Analysis Centre, based on cloud services, for storage and process of data, based on known and improved algorithms, including overlay of layers from multiple sources (e.g. meteorology and opensource data). As a constellation of six satellites, MAGAL increases the density of sea surface topography measurements, enabling more data for altimetry products, when used in synergy with other missions, in coastal areas and over mesoscale features. This results in scientific and commercial information aggregated into a single platform, displayed in various graphical interfaces, allowing overlaid correlations. MAGAL is aligned with the insights from the EU agenda for sustainable development, adding value, alongside the underlying technology development, bringing together the sea's economy and its sustainable growth.
... Altimeters send pulses at recurring points in time towards the earth's surface. Onboard trackers gather echoes that are scattered back, which are then accumulated under a power distribution function over time known as "waveform" [13]. Waveforms obtained over open water are accurately processed to obtain the satellite ranges (distance to the water) by estimating their "epoch" [30] with algorithms named "Retrackers" [31,32]. ...
Surface water availability is a fundamental environmental variable to implement effective climate adaptation and mitigation plans, as expressed by scientific, financial and political stakeholders. Recently published requirements urge the need for homogenised access to long historical records at a global scale, together with the standardised characterisation of the accuracy of observations. While satellite altimeters offer world coverage measurements, existing initiatives and online platforms provide derived water level data. However, these are sparse, particularly in complex topographies. This study introduces a new methodology in two steps (1) teroVIR, a virtual station extractor for a more comprehensive global and automatic monitoring of water bodies, and (2) teroWAT, a multi-mission, interoperable water level processor, for handling all terrain types. L2 and L1 altimetry products are used, with state-of-the-art retracker algorithms in the methodology. The work presents a benchmark between teroVIR and current platforms in West Africa, Kazakhastan and the Arctic: teroVIR shows an unprecedented increase from 55% to 99% in spatial coverage. A large-scale validation of teroWAT results in an average of unbiased root mean square error ubRMSE of 0.638 m on average for 36 locations in West Africa. Traditional metrics (ubRMSE, median, absolute deviation, Pearson coefficient) disclose significantly better values for teroWAT when compared with existing platforms, of the order of 8 cm and 5% improved respectively in error and correlation. teroWAT shows unprecedented excellent results in the Arctic, using an L1 products-based algorithm instead of L2, reducing the error by almost 4 m on average. To further compare teroWAT with existing methods, a new scoring option, teroSCO, is presented, measuring the quality of the validation of time series transversally and objectively across different strategies. Finally, teroVIR and teroWAT are implemented as platform-agnostic modules and used by flood forecasting and river discharge methods as relevant examples. A review of various applications for miscellaneous end-users is given, tackling the educational challenge raised by the community.
... Considering the period of the monitoring and the indispensable temporal resolution, Jason satellite altimetry series can be appropriate for monitoring and modeling the lake WL. The Jason satellite series is a joint project between NASA and the French Space Agency (CNES) (Vignudelli et al. 2019). In contrast to imaging satellites, altimeters only receive data along their track. ...
In this study, Urmia lake and its basin, which are vital regions in the northwest of Iran, were monitored using satellite data and modeling methods. Monthly precipitation was computed using TRMM satellite dataset. Terrestrial Water Storage (TWS), evaporation, temperature, and TWS Anomaly (TWSA) were estimated from GLDAS dataset and GRACE missions. Moreover, Jason satellite altimetry series and MODIS were used to assess the lake Water Level (WL) and area variations. These seven parameters were estimated from April 2002 to June 2019. This study adopted and evaluated four deep-learning methods based on feed-forward and recurrent architectures for data modeling, and, subsequently, predicting the water area variations. According to the obtained results, Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) models had some malfunctions in predicting lake area, while Multi-Layer Perceptron (MLP) and Long Short-Term Memory (LSTM) acquired results close to real variations of Urmia lake area. Taking Mean Absolute Error, Mean Relative Error, Root Mean Squared Error (RMSE), and correlation coefficient (r) as evaluation parameters, LSTM achieved the superior quantities, 175.07 km2, 18.87%, 231.7 km2, and 0.83, respectively. Results also indicate that LSTM is more accurate while predicting the variation of critical situations.
... . (Cipollini et al., 2017;Vignudelli, Scozzari, et al., (Brown, 1977) . . (Raney, 1998 (Dinardo, 2020;Idris et al., 2021) . ...
