6,780 research outputs found

    A Marine Radar Wind Sensor

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    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

    Satellite observations of mesoscale features in lower Cook Inlet and Shelikof Strait, Gulf of Alaska

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    The Seasat satellite launched in Summer 1978 carried a synthetic aperture radar (SAR). Although Seasat failed after 105 days in orbit, it provided observations that demonstrate the potential to examine and monitor upper oceanic processes. Seasat made five passes over lower Cook Inlet and Shelikof Strait, Alaska, during Summer 1978. SAR images from the passes show oceanographic features, including a meander in a front, a pair of mesoscale eddies, and internal waves. These features are compared with contemporary and representative images from a satellite-borne Advanced Very High Resolution Radiometer (AVHRR) and Coastal Zone Color Scanner (CZCS), with water property data, and with current observations from moored instruments. The results indicate that SAR data can be used to monitor mesoscale oceanographic features

    Analysis of Sea Surface Features by Using X-Band Radar Data Sets

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    En este trabajo se recoge el estudio de algunos de los fenómenos que ocurren en el océano debido al oleaje mediante técnicas de teledetección en el rango de las microondas. Estos fenómenos están relacionados con los diferentes mecanismos de formación de la imagen radar en banda X y en condiciones de incidencia tangente. Dichos mecanismos permiten detectar fenómenos en dichas imágenes radar (conocidas como “clutter” marino para propósitos de navegación), como son la relación de dispersión del oleaje, sus armónicos superiores y la contribución espectral conocida en la literatura científica como “group line”. Para el estudio de estos fenómenos se emplean los espectros de las imágenes proporcionadas por diferentes estaciones que utilizan tecnología basadas en radar de navegación en banda X. Los sistemas radar proporcionan una secuencia de imágenes en el dominio del tiempo que, gracias a la descomposición tridimensional de Fourier, permite obtener dichos espectros correspondientes de la secuencia de imágenes radar para su posterior análisis. Así, el espectro de la secuencia de imágenes de radar marino proporciona información sobre la distribución de la energía del oleaje, haciendo visible todos los fenómenos relacionados con el oleaje, el viento local, etc. El estudio del “clutter”, o del ruido de fondo del espectro, también es importante ya que permite la estimación de la altura significativa de las olas. En este trabajo se recoge un estudio detallado de la detección del “group line” y de la relación de dispersión del oleaje en función de la dirección de los diferentes ángulos de azimut que barren la imagen del radar, así como para diferentes alcances a partir de la ubicación del radar, además, de un estudio de la relación señal ruido considerando los fenómenos anteriores, así como de la máscara de iluminación de la superficie del mar, debida al efecto de ensombrecimiento de la antena radar, que también contiene las principales contribuciones del espectro de la imagen. A partir del análisis de las diferentes contribuciones del espectro de la imagen radar, y utilizando diversas técnicas de inteligencia artificial, se desarrollan algoritmos que mejoran la estima de parámetros oceanográficos, como la altura significativa del oleaje y las corrientes superficiales

    Developing a remote sensing system based on X-band radar technology for coastal morphodynamics study

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    New data processing techniques are proposed for the assessment of scopes and limitations from radar-derived sea state parameters, coastline evolution and water depth estimates. Most of the raised research is focused on Colombian Caribbean coast and the Western Mediterranean Sea. First, a novel procedure to mitigate shadowing in radar images is proposed. The method compensates distortions introduced by the radar acquisition process and the power decay of the radar signal along range applying image enhancement techniques through a couple of pre-processing steps based on filtering and interpolation. Results reveal that the proposed methodology reproduces with high accuracy the sea state parameters in nearshore areas. The improvement resulting from the proposed method is assessed in a coral reef barrier, introducing a completely novel use for X-Band radar in coastal environments. So far, wave energy dissipation on a coral reef barrier has been studied by a few in-situ sensors placed in a straight line, perpendicular to the coastline, but never been described using marine radars. In this context, marine radar images are used to describe prominent features of coral reefs, including the delineation of reef morphological structure, wave energy dissipation and wave transformation processes in the lagoon of San Andres Island barrier-reef system. Results show that reef attenuates incident waves by approximately 75% due to both frictional and wave breaking dissipation, with an equivalent bottom roughness of 0.20 m and a wave friction factor of 0.18. These parameters are comparable with estimates reported in other shallow coral reef lagoons as well as at meadow canopies, obtained using in-situ measurements of wave parameters.DoctoradoDoctor en Ingeniería Eléctrica y Electrónic

    Bathymetry Determination via X-Band Radar Data: A New Strategy and Numerical Results

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    This work deals with the question of sea state monitoring using marine X-band radar images and focuses its attention on the problem of sea depth estimation. We present and discuss a technique to estimate bathymetry by exploiting the dispersion relation for surface gravity waves. This estimation technique is based on the correlation between the measured and the theoretical sea wave spectra and a simple analysis of the approach is performed through test cases with synthetic data. More in detail, the reliability of the estimate technique is verified through simulated data sets that are concerned with different values of bathymetry and surface currents for two types of sea spectrum: JONSWAP and Pierson-Moskowitz. The results show how the estimated bathymetry is fairly accurate for low depth values, while the estimate is less accurate as the bathymetry increases, due to a less significant role of the bathymetry on the sea surface waves as the water depth increases

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

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    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

    Selection of the key earth observation sensors and platforms focusing on applications for Polar Regions in the scope of Copernicus system 2020-2030

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    An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.Peer ReviewedPostprint (published version

     Ocean Remote Sensing with Synthetic Aperture Radar

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    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

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

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    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

    Phase-Resolved Wave Field Simulation Calibration of Sea Surface Reconstruction Using Noncoherent Marine Radar

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    The possibility of reconstructing sea surface wave fields from a noncoherent X-band marine radar return has much potential for maritime operations and ocean engineering. The existing reconstruction method extracts the signal associated with gravity waves that satisfy the dispersion relationship. The process involves parameters related to how the radar signal is modulated by waves of different lengths, propagation directions, amplitudes, and phases. In the absence of independent wave measurements, these reconstruction parameters cannot be rationally adjusted according to wave field conditions, and the predictions are generally of uneven accuracy and reliability. A new reconstruction method based on concurrent phase-resolved wave field simulations is proposed. By maximizing the correlation between the reconstructed and simulated wave fields over time, optimal values of the reconstruction parameters are obtained that are found to vary appreciably with the wave field properties and with the location and size of the subdomain being sensed and reconstructed. With this phase-resolved simulation calibrated (PRSC) approach, the correlation between the evolving reconstructed wave field and that based on phase-resolved simulation, which measures the consistency and fidelity of the reconstruction, is improved significantly (by up to a factor of 2) and is obtained in a substantially broader range of sea states compared to existing methods.United States. Office of Naval Researc
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