Spectral wave data are required in many engineering applications such as the design of coastal defence and offshore platforms. As such, numerical wave models have been developed to estimate these wave data at locations where observed records are not available. In the published literature, the model results are often validated using sea-state parameters like significant wave height, peak wave period, mean wave period and mean wave direction. However, in some cases these parameters are not sufficient to describe the entire wave spectrum. In theory, the sea-state values could have a good agreement while the wave spectrums diverge from each other. Therefore, the main aim of this research work is to develop a new, robust approach for validating wave models by applying new parameterisation to the frequency wave spectrum.A series of parameters from wave mechanics and other disciplines have been reviewed to better define wave spectrums. These parameters are tested over a range of JONSWAP wave spectrum idealized scenarios to analyse their sensitivity and performance. The result shows that a family of seven parameters including significant wave height, peak frequency, peak energy density, squared Euclidean distance, skewness, kurtosis and mean width deviation are required to best describe the characteristic differences between an observed and predicted spectrum. Parallel analysis of the parameters reveals more qualitative information about the two spectrums, in contrast to the individual assessment of each parameter.The feasibility of the new approach developed here has been proven through the validation of a hindcast spectral wave model at three nearshore sites around the UK. The result shows that the model performance varies in both the temporal and spatial domains. Two-dimensional validation matrices have also been applied to illustrate the relationship between the various parameters with the relative magnitude, shape and position of the wave spectrums