Renewable energy is a main avenue to reduce greenhouse gas emissions and mitigate climate change, as well as health impacts, associated with mining, refining and burning fossil fuels. Isolated locations with consistent natural energy resources patterns, such as Hawaii, have great potential to reduce their dependence on fossil fuels and generate energy locally. Using a regional atmospheric model, we explored the wind-power potential of Oahu at high resolution (1 km) and over a period (2005-2014) that allowed the assessment of variability from hourly to interannual. A validation of the model using both weather stations and wind farms showed the need for observational data at the turbine hub height to correctly estimate model errors for wind power applications because the model response can be quite different at standard near-surface wind measurement heights. The model performance at larger timescales evidences the potential for long-term assessment of wind characteristics. On the other hand, the model errors at sub-daily timescales indicated limitations of short-term planning, except for sudden changes in wind speed, which were accurately simulated. Our results identify optimal locations for wind power plants from capacity factor estimates, which include analysis of mean, variability at different timescales, ramps, and sustained periods of low generation. Published by Elsevier Ltd.
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