Abstract.A technique for the assimilation of spectral wave observations in wave models is presented and tested. The method uses the concept of spectral partitioning to project, the entire wave spectrum onto a few essential mean parameters. Model and observed partition parameters are assimilated using an optimal interpolation (OI) technique. After data reduction, obtained by the partitioning, the cost of the assimilation is negligible compm'ed to the cost of the model run itself. Therefore the optimal interpolation of partitions (OI-P) method is a very attractive assimilation technique tbr operational wave Ibmcasting. The paper focuses on the assimilation of pitch-and-roll buoy spectra in a North Sea version of the WAM wave model. Treatment of the (non-fully two-dimensional) buoy spectra is discussed. Appropriate choices for the OI weight fimctions are made. The problem of correlating wave partitions in different spectra is addressed, which is essential for obtaining a robust and e•cient system. In order to assess the influence of spectral wave observations on the analysis of the sea state, the method is compared to a second scheme, optimal interpolation of integral parameters (OI-I), which can only be used to assimilate observations of significant wave height and mean wave period. First, tests with synthetic data are described, which illustrate advantages of the partitioning method over the OI-I scheme. Also, t, he inherent, limitations of OI are shown in both methods. Experiments with buoy observations for actual North Sea conditions show the benefits of the system, especially when several wave systems are present at the same time.

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Abstract. Wave spectra that are retrieved from ERS-1/2 synthetic aperture radar (SAR) wave mode observations with two different algorithms are validated against 6 years of buoy observations. The Max-Planck Institut fiir Meteorologie (MPIM) algorithm, which runs operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF), is found to deteriorate the quality of the WAM spectrum which is used as a first guess. The Semi-Parametric Retrieval Algorithm (SPRA) does not use a first-guess spectrum. For wavelengths which are observed by the SAR, it has a skill comparable to WAM. Several causes for the poor performance of the MPIM scheme are suggested. First, despite the fact that the SAR generally does not resolve the wind sea peak, the MPIM scheme allows for independent adjustment of its energy and peak frequency. Second, by using the quasi-linear approximation in the inversion, the scheme is inclined to interpret the SAR signal at low wave numbers as swell, whereas often it is generated by waves at higher wave numbers via nonlinearities in the SAR mapping. Third, the MPIM scheme is not able to adjust the spectral width of wave systems. The SPRA scheme retrieves swell information only up to a 180 ø directional ambiguity, and the SPRA retrievals often contain a spectral gap between the shortest waves observed by the SAR and the parameterized wind sea. In conclusion, the retrieval scheme performing best is the SPRA scheme, which has an accuracy comparable to WAM model output for the longer-swell waves.

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