Ocean surface currents derived from Sentinel-1 SAR Doppler shift measurements

Reliable information about ocean surface currents is crucial for operational oceanography, regulating weather development, and climate research (e.g., UN SDG 13). Upper-ocean currents are also key for monitoring life below water, including conservation of marine biodiversity at every trophic level (e.g., UN SDG 14). Locating upper ocean currents “with the right strength at the right place and time” is moreover critically needed to support the maritime transport sector, renewable marine energy, and maritime safety operations as well as for monitoring and tracking of marine pollution. In spite of this, upper ocean currents and their variability are mostly indirectly estimated and often without quantitative knowledge of uncertainties. In this thesis, Sentinel-1 Synthetic Aperture Radar (SAR) based Doppler frequency shift observations are examined for the retrievals of ocean surface current velocity in the radar line-of-sight direction. In the first study (Paper 1), Sentinel-1 A/B Interferometric Wide (IW) data acquired along the northern part of the Norwegian coastal zone from October-November 2017 at a spatial resolution of 1.5 km are compared with independent in-situ data, ocean model fields, and coastal High-Frequency Radar observations. Although only a limited dataset was available, the findings and results reveal that the strength of the meandering Norwegian Coastal Current derived from the SAR Doppler frequency shift observations are consistent with observations. However, limitations are encountered due to insufficient calibration and lack of ability to properly partition the geophysical signals into wave and current contributions. A novel approach for calibration of the attitude contribution to the Sentinel-1B Wave Mode (WV) Doppler frequency shift emerged for a test period in December 2017 - January 2018. Building on this calibrated dataset, an empirical model function (CDOP3S) for prediction of the sea state-induced contribution to the Doppler shift observations is developed for the global open ocean in Paper 2. The assessment against collocated surface drifter data are promising and suggest that the Sentinel-1B WV acquisitions can be used to study the equatorial ocean surface currents at a monthly timescale with a 20 km spatial resolution. The calibrated dataset combined with the new geophysical model function developed in Paper 2 also allowed for the study (Paper 3) of ocean surface current retrievals from the high-resolution Sentinel-1B IW swath data acquired along the coastal zone on northern Norway. In this case, the geophysical model function had to be trained and adjusted for fetch limited coastal sea state conditions. The results demonstrate that the Sentinel-1B SAR-derived ocean surface currents significantly improved, compared to the findings reported in Paper 1. Although the thesis builds on a limited period of observations, constrained by the availability of experimental attitude calibration, the results are all in all promising. Reprocessing of the full Sentinel-1 A/B SAR Doppler shift dataset using the novel attitude bias correction is therefore strongly recommended for further improvement of the empirical model function. Regular use of the Sentinel-1 A/B SAR for ocean surface current monitoring would thus be feasible, leading to advances in studies of upper ocean dynamics in support to the Copernicus Marine Environment Monitoring Service (CMEMS) program and the United Nations (UN) Decade of Ocean Sciences.Doktorgradsavhandlin

Towards Retrieving Reliable Ocean Surface Currents in the Coastal Zone From the Sentinel-1 Doppler Shift Observations

Recent developments on calibration and partitioning of the signal between the wave and current contributions significantly improve the accuracy of geophysical retrievals from Sentinel-1 Synthetic Aperture Radar-based Doppler shift measurements in the open ocean. In this study, we revise the Sentinel-1B Interferometric Wide products acquired from December 2017 to January 2018 along the coastal zone of northern Norway. We find that the satellite attitude is responsible for 30% of the variation in the Doppler shift observations, while the antenna pattern can describe an additional 15%. The residual variation after recalibration is about 3.8 Hz, corresponding to 0.21–0.15 m/s radial velocity (RVL) depending on the incidence angle. Using recalibrated Sentinel-1 observations, collocated with near-surface wind from MetCoOp-Ensemble Prediction System and sea state from MyWaveWAM, we develop an empirical function (CDOP3SiX) for estimating the sea-state-induced Doppler shift. CDOP3SiX improves the accuracy of sea state contribution estimates under mixed wind fetch conditions and demonstrates that the Norwegian Coastal Current can be detected in the Sentinel-1 derived ocean surface current RVL maps. Moreover, two anticyclonic mesoscale eddies with radial velocities of about 0.5 m/s are detected. The surface current patterns are consistent with the collocated sea surface temperature observations. The Doppler shift observations from Sentinel-1 can therefore be used to study ocean surface currents in the coastal zone with a 1.5 km spatial resolution. Key Points The Sentinel-1 Doppler shift observations are used to retrieve information about the ocean surface currents in the coastal zone Mesoscale eddies are detected in the Synthetic Aperture Radar-derived ocean surface current radial velocity fields Combination of the wind and wave information from collocated models improves the accuracy of the wave-induced contribution estimates Plain Language Summary Knowledge of ocean surface currents is crucial for studies of volume, heat and salt transport, tracking pollutants, and fisheries. The Doppler shift from Sentinel-1 Synthetic Aperture Radar (SAR) observations can be used to retrieve information about ocean surface currents. Challenging calibration and lack of algorithms for separating the wave and current contributions have limited the application of this observation-based method. Recent developments on calibration showed promising improvements in the accuracy of the signal. In this study, we apply this recent calibration method to Sentinel-1B scenes and develop an algorithm applicable for the challenging conditions in the coastal zone. We found that the signal from the Norwegian Coastal Current can be detected in the Sentinel-1 derived ocean surface current radial velocity fields. Also, we demonstrated the potential of SAR data for observing eddies with diameter of about 40–70 km. The Sentinel-1 derived surface currents express meandering structures and boundaries in consistence with the satellite-based sea surface temperature field. Comparison with the ocean model also reveals reasonable agreement, especially for the major surface current features. Therefore, given accurate calibration and new algorithm for removal of the wind and wave contribution, the Sentinel-1 observations can be used for monitoring ocean surface currents in the coastal zone with high spatial resolution.publishedVersio

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval

Spaceborne synthetic aperture radar (SAR) can provide accurate images of the ocean surface roughness day-or-night in nearly all weather conditions, being an unique asset for many geophysical applications. Considering the huge amount of data daily acquired by satellites, automated techniques for physical features extraction are needed. Even if supervised deep learning methods attain state-of-the-art results, they require great amount of labeled data, which are difficult and excessively expensive to acquire for ocean SAR imagery. To this end, we use the subaperture decomposition (SD) algorithm to enhance the unsupervised learning retrieval on the ocean surface, empowering ocean researchers to search into large ocean databases. We empirically prove that SD improve the retrieval precision with over 20% for an unsupervised transformer auto-encoder network. Moreover, we show that SD brings important performance boost when Doppler centroid images are used as input data, leading the way to new unsupervised physics guided retrieval algorithms

Satellite remote sensing of surface winds, waves, and currents: Where are we now?

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields