The formation and intensification of typhoons is a complex process where energy and mass exchanges happen between the ocean and the atmosphere. In most typhoon numerical studies, a static ocean and a dynamic atmosphere are used to reduce the complexity of modeling. Using the COAWST model, we studied the air-sea interactions of Typhoon Mujigae in 2015, Typhoon Merbok in 2017, and Typhoon Hato in 2017 over the South China Sea. With different translation speeds, track shapes, and intensities between these cyclones, they act as an excellent case study to analyze the air-sea coupling in the models. The inclusion of coupling between the ocean and atmosphere is found to improve the typhoon track simulation significantly. The bias in the cyclone tracks is reduced by 10%–40% in the coupled model. The upper ocean response to the typhoon was also analyzed using the coupled model output. The coupled simulations show that the major energy extraction occurs to the right of the track, which is consistent with satellite observation and latent heat release analysis. The coupling process shows the air-sea interactions and exchanges in the upper ocean along with the energy released during the passage of typhoons. The heat budget analysis shows that the cooling of the upper ocean is mainly attributed to the advection associated with the typhoon forcing. This study shows that it is necessary to include ocean feedback while analyzing a typhoon, and the application of coupled models can improve our understanding as well as the forecasting capability of typhoons.
As the world is moving toward greener forms of energy, to mitigate the effects of global warming due to greenhouse gas emissions, wind energy has risen as the most invested-in renewable energy. China, as the largest consumer of world energy, has started investing heavily in wind energy resources. Most of the wind farms in China are located in Northern China, and they possess the disadvantage of being far away from the energy load. To mitigate this, recently, offshore wind farms are being proposed and invested in. As an initial step in the wind farm setting, a thorough knowledge of the wind energy potential of the candidate region is required. Here, we conduct numerical experiments with Weather Research and Forecasting (WRF) model forced by analysis (NCEP-FNL) and reanalysis (ERA-Interim and NCEP-CFSv2) to find the best choice in terms of initial and boundary data for downscale in the South China Sea. The simulations are validated by observation and several analyses. Specific locations along China’s coast are analyzed and validated for their wind speed, surface temperature, and energy production. The analysis shows that the model forced with ERA-Interim data provides the best simulation of surface wind speed characteristics in the South China Sea, yet the other models are not too far behind. Moreover, the analysis indicates that the Taiwan Strait along the coastal regions of China is an excellent region to set up wind farms due to possessing the highest wind speeds along the coast.
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