Abstract
Recent work has demonstrated that surface marine winds from the Bureau of Meteorology's operational Numerical Weather Prediction (NWP) systems are typically underestimated by 5 to 10%. This is likely to cause significant bias in modelled wave fields that are forced by these winds. A simple statistical adjustment of the wind components is shown to reduce the observed bias in Significant Wave Height considerably. The impact of increasing the vertical resolution of the NWP model and assimilating scatterometer data into the model is assessed by comparing the resulting forecast wind and waves to observations. It is found that, in general, the inclusion of scatterometer observations improves the accuracy of the surface wind forecasts. However, most of the improvement is shown to arise from the increased number of vertical levels in the atmospheric model, rather than directly from the use of the observations. When the wave model is forced with surface winds from the NWP model that includes scatterometer data, it is found that the scatterometer assimilation does not reduce the systematic bias in surface wave forecasts, but that the random errors are reduced.
Keywords:
Acknowledgements
The authors would like to thank Jaan Paevere for providing the model runs from GASP used in this work. The authors appreciate useful comments on the text made by Jim Fraser and the anonymous referees.