Impacts of Climate Oscillation on Offshore Wind Resources in China Seas

The long-term stability and sustainability of offshore wind energy resources are very important for exploration. In this study, the Cyclostationary Empirical Orthogonal Function (CSEOF) method, which can determine time varying spatial distributions fluctuations in cyclostationary geophysical process, was adopted to investigate geographical temporal variability China Seas. CSEOF analysis performed on speeds at 70 m height above sea surface from a validated combined Quick Scatterometer (QuikSCAT) Advanced (ASCAT) product (2000–2016) with high resolution 12.5 km, Climate Forecast System Reanalysis (CFSR) data (1979–2016) grid size 0.5° × 0.5°. decomposition results two datasets indicate that first mode represents annual cycle signal contributes 77.7% 76.5% variability, respectively. principal component series (PCTS) shows an interannual period 3–4 years. second accounts 4.3% 4.7% total speed respectively, captures spatiotemporal contribution El Niño Southern Oscillation (ENSO) regional variability. correlations between mode-2 PCTS scatterometer or CFSR winds Index (SOI) greater than 0.7, illustrating ENSO has significant impact China’s resources. Moreover, mode-1 pattern is basically consistent data, but underestimates changes related ENSO. Compared reanalysis always demonstrate finer structure due their higher resolution. For events different intensities, varies space. general, reduced most regions Seas except Bohai Sea Beibu Bay, while La Niña strengthened areas southern South Sea.