This study presents a new gridded dataset providing absolute monthly mean temperatures across the Greater Alpine Region (GAR) of Europe at a spatial resolution of 5 arcmin (6 × 9 km in the region) from 1780 to 2008. The starting point was a set of long-term homogenized station time series. To assure the quality of the analyses back in time, when the station density decreases, missing measurements were reconstructed by an Empirical Orthogonal Function analysis that can deal with gappy data. It is shown that the reconstructed values comprise similar statistical features to the observations and that the method produces no breaks between the reconstructions and the observations. The compound anomaly dataset was then interpolated separately for two different altitude ranges to preserve anomaly gradients between high and low elevations. This allowed for the derivation of individual anomalies at each grid point in GAR. Finally, these smooth anomalies were blended with the highly resolved monthly mean absolute temperature fields, provided by a project of the European Climate Support Network. The added value of this new high resolution and long-term temperature dataset is shown and discussed using the examples of the height of the 0 °C altitude and vertical lapse rates. For the first time, these and other features are now available for more than two centuries in a topographically complex region like GAR.