Abstract. Inverted wave spectra from ERS-1 synthetic aperture radar (SAR) image and wave mode products have been assimilated in the operational wave model for the ocean wave forecast service at the Norwegian Meteorological Institute. Elements of the operational system are explained briefly, and the impact of including the SAR wave data in the operational wave model runs is shown both for individual cases and as overall statistics. Although individual cases clearly show that the satellite observations are able to influence the forecast in a generally positive way, the average improvement is minor for the areas covered by the wave model. Reasons for this are the intermittency of the data, on the average small differences between inverted SAR and model first-guess wave spectra, and to some extent, limitations in the analysis method. . These more sophisticated techniques are computationally more expensive and so far not commonly in operational use at the wave forecast centers. A further development in the assimilation of satellite wave data is to utilize the full spectral information from the synthetic aperture radar (SAR). A method for assimilation of twodimensional wave spectra by dividing the full spectrum into separate partitions suitable for optimal interpolation has been developed by Hasselman et al. [1994, 1996] and demonstrated in an operational framework by Voorrips et al. [1997]. In the present study we apply a simpler sequential method for assimilation of full two-dimensional SAR wave spectra.Unfortunately, the currently inverted SAR wave spectra are not completely independent from the wave model spectra since the SAR inversion algorithm depends on a priori information from the wave model itself. Previous studies [Breivik et al., 1995] have shown that there is nearly full correlation between a priori and inverted SAR wave spectrum parameters in the wind sea part. This is actually to be expected since the SAR information is confined to frequencies below ---0.15 Hz. However, the SAR spectra usually cover the swell part and therefore have a potential for improving the model results by data assimilation. Very high average impact cannot be expected in the present case since the model is known to produce reliable results. However, in special situations, e.g., with poor wind history and correspondingly poorly defined swell, more significant improvement might be expected.In order to assess the impact of the SAR data an additional operational wave model routine including assimilation of the inverted SAR spectra was run parallel to the regular operational wave model forecasts for 4 months during the fall and winter of 1995-1996.The results from these runs have been compared to independent measurements from North Sea platforms and the ERS-1/2 altimeter. The evaluation of the fore-7887

SUMMARYModi cations of numerical potential vorticity (PV) elds according to features in water vapour (WV) images are combined with singular-vector dynamics in an attempt to improve the numerical analysis in the study of a severe winter storm. The apparent mismatch between features in the WV images and upper-level PV anomalies in the numerical analysis is corrected at levels indicated as sensitive by the fastest growing singular vectors. Model reruns, based on the inverted PV elds, are then carried out. Though numerical weather prediction (NWP) re-runs are highly successful in improving the simulation of the storm, they produce a degraded simulation of a second wave which followed rapidly in the wake of the rst one. Some success is achieved by enhancing its associated upperlevel PV anomaly at sensitive levels. The impact on the large-scale ow arising from localized PV modi cations is discussed and may point to a reason why the NWP runs based on PV modi cation occasionally fail to improve the simulation, e.g. the second wave in this case.

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