High-Resolution Atmospheric Modelling and the Effects on the Prediction of Wave Characteristics

Since their development in the 1970s, mesoscale atmospheric models have been used for a variety of meteorological applications. Over the years, the models have evolved and nowadays, state-of-the-art atmospheric models are capable of operating on spatial resolutions in the order of kilometres. In the hydraulic engineering community, atmospheric models are used for operational flood protection. HIRLAM is used in the Netherlands with typical spatial resolutions of 11 km. These scales are too coarse to correctly predict small scale effects such as squall-lines and convection cells. Furthermore, the resolution is too low to accurately capture the land-water boundary. The state-of-the-art models of today are capable of predicting small scale meteorological events that might be of interest for hydraulic engineers. The goal of this study was to successfully use a state-of-the-art atmospheric model at high-spatial resolutions to investigate the possible added-value of these models for hydraulic engineering purposes. The problem that was addressed concerns wave growth at short fetch. This is specifically important for wave prediction on rivers, harbour basins, and small lakes. Deltares [2013] investigated the predictive capabilities of SWAN for short fetches ( 30 m/s) was investigated. The specific event turned out to be a gust front coming from a convection cell. The simulations responded differently to the event; with increasing resolutions, higher velocities, precipitation rates, downward velocities, and other locations were found. Finally, for the highest resolution (? x = 300 m) artificial disturbances in the atmospheric pressure were found, indicating limitation to the validity of the chosen model settings. To assess the effects of the spatial resolution of the wind field in SWAN, both storms were simulated using the 2700, 1500, 900 and 500 m wind fields. The same method, using pseudo wind speeds was applied for the use of the friction velocity in SWAN. However, for the specific purpose of dealing with wave growth at short fetches, problems were found near the land water boundary. Because the resolution of the wind fields were relatively coarse compared the length scales associated with short fetches, wind field data did not accurately model the land-water boundary. Therefore, an extra preprocessing step was used to exclude land points from the WRF wind field, and to extrapolate water-based data to the land-water boundary. Time series of the results showed equal performance for all simulations, no differences due to the wind field resolution were found. Further investigation of the spatial variability of the wave field showed that the effects of the wind streaks were also shown in the SWAN results. This resulted in differences between the simulations up to 6\% near the coast. In conclusion, the results showed that the model was still able to produce results that were in agreement with observations, and simulations with other resolutions, without showing signs (in the variables: pressure, temperature, humidity, and wind) of instabilities. This suggests—in agreement with Hong and Dudhia [2012]— that the model indeed still produces reliable wind results for resolutions up to 500 m. A specific event was investigated that turned out to be a convection cell that clearly showed the different reaction to increasing resolutions, higher velocities (horizontally and vertically), higher precipitation rates, and different locations for the convection cell were found. The coarser resolutions (? x =2700 m and ? x = 1500 m) hardly showed any deviations in wind speed due the cell, while the higher resolutions showed strong surface winds of up to 32 m/s. Simulations with SWAN showed only little variation based on the resolution of the wind field. The added value of these models in relation to wave modelling can be found from the better representation of the surface features such as the land-water boundary, and land-use for the determination of the roughness, which allow for the prediction of wind above harbour basins and river, possibly leading to more accurate predictions of wave characteristics on these locations. Furthermore, the prediction of convective processes such as squall-lines and convection cells could be a valuable addition for operational wave (en wind) predictions.