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This study investigates the accuracy of the wave products retrieved by a 12-MHz high-frequency (HF) phased-array radar, and establishes their potential to characterise wave-current interactions. The two stations composing the system were deployed in 2011 to overlook the Wave Hub, a test site for marine renewable energy devices located on the south-western coast of the United Kingdom. The system was conceived and configured to reduce the inaccuracies introduced by short time averaging and minimal overlap between stations, both associated with the most traditional HF radar deployments, whose primary activity is current measurement. Wave spectra were retrieved by two independent inversion algorithms, which were evaluated both independently and relative to each other. This process helped determining the errors associated to the algorithm used, and differentiated them from those inherent to the radar technology itself. The first method investigated was a semi-empirical algorithm distributed with Wellen Radars (WERA), which was calibrated using in situ measurements collected within the radar footprint. Evaluated through comparison against measurements acquired by three in situ devices, the results revealed estimates of significant wave height with biases below 9 cm, Pearson correlations higher than 0.9, and RMS errors that range from 29 to 44 cm. The relative error of wave energy period comparisons was within 10% for periods between 8 and 13 s, while both under- and overestimations were observed above and below that range, respectively. The validation demonstrated that when locally calibrated, the algorithm performs better than in its original form in all metrics considered. Observed discrepancies were mainly attributable to single-site estimations, antenna sidelobes, and the effect of the second-harmonic peaks of the Doppler spectrum. As opposed to the semi-empirical inversion, the second method evaluated in this work provides estimates of the full directional spectrum. Compared against the in situ measurements, the radar spectra were more spread over frequencies and directions, and had a lower energy content at the peak of the spectrum. In terms of parameter estimation, this was generally translated in a slight underestimation of wave periods, but accurate estimates of significant wave heights. Pearson correlations between these parameters and the in situ measurements for the bulk of the spectrum were higher than 0.9, and both types of measurements resulted in similar standard deviations. The inversion algorithm showed a high skill estimating mean wave directions, which revealed linear correlations higher than 0.8, when compared to the in situ devices. Overall, the inversion algorithm has shown to be capable of providing accurate estimates of directional spectra and the parameters derived from them, and at present the main drawback of the method is the data return, which due to the high data quality requirements of the algorithm, did not exceed 55% over the 8-month period studied here. In the second part of this work, the validated measurements were examined to determine their ability to reproduce the effects of wave-current interactions. The fine structure of the surface current was first evaluated, and revealed a circulation dominated by tides. The residual flow was seen to respond to the wind, as well as to the stratification present in the area during the spring and summer months. These data were then used to assess their contribution to wave refraction over the radar domain. The results show modulations in the wave phase parameters, which resulted from both the temporal and spatial derivatives of the surface current velocities. The evaluation of HF radar wave measurements provided in this work has shown that, properly configured, this technology can produce accurate estimates of several statistical descriptors of the wave field. Together with the highly accurate surface currents also measured by this device, the spatial wave data obtained has proved to have great potential for studying wave-current interactions; a skill that can be of support to coastal wave modelling. MaRINET - FP7 Infrastructures School of Marine Science and Engineering