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Extreme Wave Height Events in NW Spain: A Combined Multi-Sensor and Model Approach.

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TLDR
The results reveal the significant accuracy of IBI-WAV forecasts and prove that a combined observational and modeling approach can provide a comprehensive characterization of severe wave conditions in coastal areas and shows the benefits from the complementary nature of both systems.
Abstract
The Galician coast (NW Spain) is a region that is strongly influenced by the presence of low pressure systems in the mid-Atlantic Ocean and the periodic passage of storms that give rise to severe sea states. Since its wave climate is one of the most energetic in Europe, the objectives of this paper were twofold. The first objective was to characterize the most extreme wave height events in Galicia over the wintertime of a two-year period (2015–2016) by using reliable high-frequency radar wave parameters in concert with predictions from a regional wave (WAV) forecasting system running operationally in the Iberia-Biscay-Ireland (IBI) area, denominatedIBI-WAV. The second objective was to showcase the application of satellite wave altimetry (in particular, remote-sensed three-hourly wave height estimations) for the daily skill assessment of the IBI-WAV model product. Special attention was focused on monitoring Ophelia—one of the major hurricanes on record in the easternmost Atlantic—during its 3-day track over Ireland and the UK (15–17 October 2017). Overall, the results reveal the significant accuracy of IBI-WAV forecasts and prove that a combined observational and modeling approach can provide a comprehensive characterization of severe wave conditions in coastal areas and shows the benefits from the complementary nature of both systems.

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Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

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Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics

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How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions

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Change detection techniques for remote sensing applications: a survey

TL;DR: This study attempts to provide a comprehensive review of the fundamental processes required for change detection with a brief account of the main techniques of change detection and discusses the need for development of enhanced change detection methods.
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Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters

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References
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Journal ArticleDOI

Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation

TL;DR: In this article, the spectral dissipation of wind-generated waves is modeled as a function of the wave spectrum and wind speed and direction, in a way consistent with observations of wave breaking and swell dissipation properties.
Journal ArticleDOI

Doppler Spectrum of Sea Echo at 13.56 Mc./s.

D. D. Crombie
- 01 Apr 1955 - 
TL;DR: The frequency of the principal component (as initially obtained by measurement of the length of individual cycles on the record) is surprisingly constant at about 0.38 c/s, irrespective of wind conditions and state of the sea as discussed by the authors.
Journal ArticleDOI

Semi-empirical dissipation source functions for ocean waves: Part I, definition, calibration and validation

TL;DR: In this paper, the wave energy balance is verified in a wide range of conditions and scales, from gentle swells to major hurricanes, from the global ocean to coastal settings using in situ and remote sensing data.
Journal ArticleDOI

Climatology, variability and extrema of ocean waves: the Web-based KNMI/ERA-40 wave atlas

TL;DR: The European Centre for Medium-Range Weather Forecasts (ECMWF) has recently published ERA-40, a reanalysis covering the period September 1957 to August 2002 as discussed by the authors.
Journal ArticleDOI

Wave energy potential in Galicia (NW Spain)

TL;DR: In this paper, the potential for energy production in Galicia is assessed based on three-hourly data from a third generation ocean wave model (WAM) covering the period 1996-2005.
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