The interannual variability of wind energy resources across China and its relationship to large‐scale circulation changes.

This study investigates the interannual variability of wind energy resources across China and how it changes with season by applying empirical orthogonal function (EOF) analyses to gridded wind data from the Climate Forecast System Reanalysis (CFSR) from January 1979 through December 2011. The first EOF mode (EOF1) represents between 22% variance for winter and 29% for summer. Spatially, the variation is largely consistent across China for summer and autumn and almost opposite between north and south for spring and winter, and the strongest variation in all seasons is found over Inner Mongolia and Tibet. The second EOF mode (EOF2) represents between 13% variance for autumn and 16% for spring, and is largely dominated by a sharp contrast between Inner Mongolia and Tibet for all seasons. The EOF1 appears to be linked statistically to the pacific decadal oscillation for summer and autumn and to the Pacific North American pattern for spring and winter, while the EOF2 seems to be connected to the Arctic Oscillation for spring and winter and to an interdecadal variability for summer and autumn. The anomalous wind fields associated with these large‐scale circulation patterns modify the climatological wind fields in different ways that lead to an increase or a decrease of the 80‐m winds in different regions of China. Understanding the low‐frequency variability of wind speeds, or how and why wind speed and wind power vary from 1 year to another, can be beneficial for seasonal outlook or long‐range forecasting of wind power generation. Using gridded wind data from a third‐generation global reanalysis, we statically identify and characterize the main modes of the interannual variability of wind speeds at the modern wind turbine level across entire China and the dominant climate forcing for these modes.Figure caption: The correlations between the 80‐m wind speed summer season anomalies across China and the Pacific Decadal Oscillation indices for 1979–2011. [ABSTRACT FROM AUTHOR]