Reanalysis data such as MERRA and MERRA-2 are commonly used to derive solar and wind power generationtime series, and to estimate their resource potentials. However, the spatial resolution of the reanalysis data (0.5° latitude x 0.625° longitude for MERRA-2) is not sufficient for small-scale energy system models (e.g. statesand cities), nor for siting potential projects. This paper uses the MERRA-2 reanalysis data in combination withadditional data sources for land-use, topography, and protected areas, in order to obtain accurate global resourcepotential maps with a spatial resolution of 15 arcseconds. We also generate time series for individual cells of therasters and identify the best locations for future wind and solar projects. The results are validated against measuredhourly generation data of wind and photovoltaic power plants in Europe.     «

Reanalysis data such as MERRA and MERRA-2 are commonly used to derive solar and wind power generationtime series, and to estimate their resource potentials. However, the spatial resolution of the reanalysis data (0.5° latitude x 0.625° longitude for MERRA-2) is not sufficient for small-scale energy system models (e.g. statesand cities), nor for siting potential projects. This paper uses the MERRA-2 reanalysis data in combination withadditional data sources for land-use, topography, and protecte...     »