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Land-based high-frequency (HF) radars have the unique capability of continuously monitoring ocean surface environments at ranges up to 200 km off the coast. They provide reliable data on ocean surface currents and under slightly stricter conditions can also give information on ocean waves. Although extraction of wind direction is possible, estimation of wind speed poses a challenge. Existing methods estimate wind speed indirectly from the radar derived ocean wave spectrum, which is estimated from the second-order sidebands of the radar Doppler spectrum. The latter is extracted at shorter ranges compared with the first-order signal, thus limiting the method to short distances. Given this limitation, we explore the possibility of deriving wind speed from radar first-order backscatter signal. Two new methods are developed and presented that explore the relationship between wind speed and wave generation at the Bragg frequency matching that of the radar. One of the methods utilizes the absolute energy level of the radar first-order peaks while the second method uses the directional spreading of the wind generated waves at the Bragg frequency. For both methods, artificial neural network analysis is performed to derive the interdependence of the relevant parameters with wind speed. The first method is suitable for application only at single locations where in situ data are available and the network has been trained for while the second method can also be used outside of the training location on any point within the radar coverage area. Both methods require two or more radar sites and information on the radio beam direction. The methods are verified with data collected in Fedje, Norway, and the Ligurian Sea, Italy using beam forming HF WEllen RAdar (WERA) systems operated at 27.68 and 12.5 MHz, respectively. The results show that application of either method requires wind speeds above a minimum value (lower limit). This limit is radar frequency dependent and is 2.5 and 4.0 m/s for 27.68 and 12.5 MHz, respectively. In addition, an upper limit is identified which is caused by wave energy saturation at the Bragg wave frequency. Estimation of this limit took place through an evaluation of a year long database of ocean spectra generated by a numerical model (third generation WAM). It was found to be at 9.0 and 11.0 m/s for 27.68 and 12.5 MHz, respectively. Above this saturation limit, conventional second-order methods have to be applied, which at this range of wind speed no longer suffer from low signal-to-noise ratios. For use in operational systems, a hybrid of first- and second-order methods is recommended

High-frequency (HF) surface wave radars provide the unique capability to continuously monitor the coastal environment far beyond the range of conventional microwave radars. Bragg-resonant backscattering by ocean waves with half the electromagnetic radar wavelength allows ocean surface currents to be measured at distances up to 200 km. When a tsunami propagates from the deep ocean to shallow water, a specific ocean current signature is generated throughout the water column. Due to the long range of an HF radar, it is possible to detect this current signature at the shelf edge. When the shelf edge is about 100 km in Responsible Editor: Aida Alvera-Azcárate This article is part of the Topical Collection on Multiparametric observation and analysis of the Sea.front of the coastline, the radar can detect the tsunami about 45 min before it hits the coast, leaving enough time to issue an early warning. As up to now no HF radar measurements of an approaching tsunami exist, a simulation study has been done to fix parameters like the required spatial resolution or the maximum coherent integration time allowed. The simulation involves several steps, starting with the Hamburg Shelf Ocean Model (HAMSOM) which is used to estimate the tsunami-induced current velocity at 1 km spatial resolution and 1 s time step. This ocean current signal is then superimposed to modelled and measured HF radar backscatter signals using a new modulation technique. After applying conventional HF radar signal processing techniques, the surface current maps contain the rapidly changing tsunami-induced current features, which can be compared to the HAMSOM data. The specific radial tsunami current signatures can clearly be observed in these maps, if appropriate spatial and temporal resolution is used. Based on the entropy of the ocean current maps, a tsunami detection algorithm is described which can be used to issue an automated tsunami warning message.