Identification of Best CMIP6 Climate Models for Offshore Wind Energy Assessment

Offshore wind harvesting has grown vividly in recent decades, as it is recognized as a promising source in many parts of the world. The less interaction of landmasses makes it more efficient when compared with onshore winds. The impact of climate change on the energy sector, especially changes in wind energy output, is gaining traction. As a result, determining the future of offshore wind energy is critical for developing an effective energy plan. However, how offshore wind generation will respond to rapidly intensifying global warming remains inconclusive. Wind energy is an integral part of India's energy mix. Therefore, it is essential to know how it changes as the climate changes. Consequently, global climate models (GCMs) can simulate climate change and effectively evaluate atmospheric circulation patterns. However, GCMs have systematic errors leading to improper output. Hence, the selected CMIP6 models have been evaluated with RAMA buoy data using five statistical parameters in this paper. Furthermore, the weighted multi-model ensemble is produced by the MCDM technique using the parameter's output. The model's performance is then compared to ERA5 data, which shows that when compared to uniform weighted MME, the weighted MME developed in this study for predicting future wind energy over the Indian offshore region has more notable outcomes.