Combining wind and solar power generation has potential to make renewable energy less variable. This is done to take advantage of the fact that it tends to be cloudy when it’s windy and calm when it’s sunny  . Preliminary site assessment for wind and solar
power generation is commonly done by making use of reanalysis data. A reanalysis is a dataset generated using weather observations and a modified forecast model to produce a gridded representation of past weather events. In this study, the correlation between wind speed and solar radiation from two popular reanalysis datasets, ERA- Interim and MERRA2 , have been compared to correlations based on observed data from four Irish weather stations, along with mast observations from Cabauw, Netherlands.
Correlation coefficients were calculated between daily mean values of wind speed and shortwave radiation. The magnitude of the anticorrelation between 10m wind speed and radiation was found to be greater in both reanalyses, compared to observations, at all Irish stations. When considering monthly correlations of daily means, differences also emerge in how the correlations vary through the year in the two reanalyses. This is particularly apparent during summer, where the anticorrelation is generally greater in ERA-Interim, compared to MERRA2.
To begin analysing winds at heights closer to wind turbine hub heights, observations from Cabauw Experimental Site for Atmospheric Research (CESAR), Netherlands were also compared to reanalysis data. Reanalysis wind speeds at a greater height were also analysed (50m wind for MERRA2 and 60m wind for ERA-Interim). Observed correlations were found to vary more so with height than in reanalysis. Additionally the differences between the individual datasets are greater than the differences between heights within the same dataset.
Future work will look to use mast observations over Ireland to continue the analysis of the correlations between shortwave radiation and wind speeds closer to wind turbine hub heights.
 P. E. Bett and H. E. Thornton, The climatological relationships between wind and solar
energy supply in Britain. Renewable Energy 87:96-110, 2016.
 Y. He, A. H. Monahan and N.A. McFarlane. Diurnal variations of land surface wind speed
probability distributions under clearsky and lowcloud conditions. Geophysical Research
Letters 40(12):3308-3314, 2013.