A Marine Radar Wind Sensor

A new method for retrieving the wind vector from radar-image sequences is presented. This method, called WiRAR, uses a marine X-band radar to analyze the backscatter of the ocean surface in space and time with respect to surface winds. Wind direction is found using wind-induced streaks, which are very well aligned with the mean surface wind direction and have a typical spacing above 50 m. Wind speeds are derived using a neural network by parameterizing the relationship between the wind vector and the normalized radar cross section (NRCS). To improve performance, it is also considered how the NRCS depends on sea state and atmospheric parameters such as air–sea temperature and humidity. Since the signal-to-noise ratio in the radar sequences is directly related to the significant wave height, this ratio is used to obtain sea state parameters. All radar datasets were acquired in the German Bight of the North Sea from the research platform FINO-I, which provides environmental data such as wind measurements at different heights, sea state, air–sea temperatures, humidity, and other meteorological and oceanographic parameters. The radar-image sequences were recorded by a marine X-band radar installed aboard FINO-I, which operates at grazing incidence and horizontal polarization in transmit and receive. For validation WiRAR is applied to the radar data and compared to the in situ wind measurements from FINO-I. The comparison of wind directions resulted in a correlation coefficient of 0.99 with a standard deviation of 12.8°, and that of wind speeds resulted in a correlation coefficient of 0.99 with a standard deviation of 0.41 m s^−1. In contrast to traditional offshore wind sensors, the retrieval of the wind vector from the NRCS of the ocean surface makes the system independent of the sensors’ motion and installation height as well as the effects due to platform-induced turbulence

Retrieval of Ocean Surface Currents and Winds Using Satellite SAR backscatter and Doppler frequency shift

Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill drift and search and rescue. In-situ observations of the ocean are sparse and costly. Satellites provide a useful complement to these observations. Synthetic aperture radar (SAR) is particularly attractive due to its high spatial resolution and its capability to extract both sea surface winds and currents day and night and almost independent of weather.The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions

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

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

Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to in situ measurements. This study examines satellite synthetic aperture radar (SAR) images from ENVISAT advanced SAR (ASAR) for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard deviation (SD) of 1.99 m/s and correlation coefficient of R = 0.67. The model wind directions, which are used as input for the SAR wind speed retrieval, show a high correlation coefficient (R = 0.89) but a large standard deviation (SD = 42.3°) compared to in situ observations. The Weibull probability density functions are compared at one meteorological station. The SAR-based results appear not to estimate the mean wind speed, Weibull scale and shape parameters and wind power density from the full in situ data set so well due to the lower number of satellite samples. Distributions calculated from the concurrent 81 SAR and in situ samples agree well

Data Requirements for Oceanic Processes in the Open Ocean, Coastal Zone, and Cryosphere

The type of information system that is needed to meet the requirements of ocean, coastal, and polar region users was examined. The requisite qualities of the system are: (1) availability, (2) accessibility, (3) responsiveness, (4) utility, (5) continuity, and (6) NASA participation. The system would not displace existing capabilities, but would have to integrate and expand the capabilities of existing systems and resolve the deficiencies that currently exist in producer-to-user information delivery options

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