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ABSTRACT The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33-year (1979-2011) wind data from the Climate Forecast System Reanalysis ( CFSR) that has many improvements including higher spatial resolution over previous global reanalysis products. Mean 80-m wind speeds are consistently higher over China Seas and the ocean areas than over land, and inside China high winds are found in areas of Inner Mongolia and the Tibetan Plateau. There is a considerable seasonal variability that reflects primarily the influence of East and Southeast Asia Monsoon with generally higher speeds in winter followed by summer, and weaker winds in autumn, followed by spring. There is also a strong interannual variability, and regions of larger amplitude of variability coincide with regions of higher mean winds. A decreasing trend, dominated by a sharp decline beginning in 2005, is seen across China and the surrounding seas in summer and autumn, and the summer trends over land and over ocean appear to be related respectively to the Pacific Decadal Oscillation ( PDO) and the East Asian summer monsoon. Trends are not consistent across the region in spring and winter, however, with positive trends over some areas in northeastern and northwestern China, Mongolia and tropical oceans whereas negative trends in other regions. Nearly all areas of China experience mean annual 80-m wind speed less than 6.9 m s−1 (wind power classes of 1-2) except for some areas of Inner Mongolia where mean annual 80-m wind speeds exceed 6.9 m s−1 (Classes 3 or higher, suitable for wind energy development). China Seas and ocean areas generally fall in Class 3 or above, with the Taiwan and Luzon Straights reaching the highest Class 7. [ABSTRACT FROM AUTHOR]

Irregular oscillations of Equatorial Pacific sea surface temperatures known as El Niño-Southern Oscillation (ENSO) has been shown to affect air pollution in China by altering atmospheric circulations. In this study, we use hourly PM2.5 data from nearly 1500 monitoring stations across entire China to further explore the connection between ENSO and China's haze pollution by comparing PM2.5 concentrations for the two most recent ENSO events, the 2015–2016 El Niño and the 2017–2018 La Niña. The PM2.5 concentrations show significant differences between the two events and the differences are larger in winter and smaller in summer. In summer, the PM2.5 concentrations are higher across China during El Niño. However in winter, higher concentrations are found at most stations in northern China during El Niño, but at majority of stations in southern China during La Niña. Spring and autumn show a transitional pattern between summer and winter. Dividing the country into nine regions with similar geographical conditions, the relationship between the monthly PM2.5 concentration anomalies and the Niño3.4 indices, as revealed by linear regression, is generally positive at stations in North, Northeast and the northern parts of Central and East China, but generally negative in South, Southwest and the southern parts of Central and East China. No difference is found in the oscillation periods of the PM2.5 concentrations between the two events, except that the seasonal and intra-seasonal oscillatory signals appear to be slightly stronger during El Niño than La Niña. The regional and seasonal differences in PM2.5 concentrations between El Niño and La Niña can be partially explained by the differences in the anomalous atmospheric circulation patterns, particularly the low-level wind and surface precipitation patterns. • The influence of El Niño and La Niña on PM2.5 concentrations across China is explored. • The influence of El Niño-La Niña on PM2.5 in China differ by region and season. • The relationship between PM2.5 and Niño indices is opposite in north and south China. • PM2.5 seasonal and intra-seasonal oscillations are stronger with El Niño than La Niña. • The ENSO-PM2.5 connection is consistent with anomalous circulation and precipitation. [ABSTRACT FROM AUTHOR]