Potential evapotranspiration (PET) and reference evapotranspiration (RET) data are usually critical components of hydrologic analysis. Many different equations are available to estimate PET and RET. Most of these equations, such as the Priestley-Taylor and Penman- Monteith methods, rely on detailed meteorological data collected at ground-based weather stations. Few weather stations collect enough data to estimate PET or RET using one of the more complex evapotranspiration equations. Currently, satellite data integrated with ground meteorological data are used with one of these evapotranspiration equations to accurately estimate PET and RET. However, earlier than the last few decades, historical reconstructions of PET and RET needed for many hydrologic analyses are limited by the paucity of satellite data and of some types of ground data. Air temperature stands out as the most generally available meteorological ground data type over the last century. Temperature-based approaches used with readily available historical temperature data offer the potential for long period-of-record PET and RET historical reconstructions. A challenge is the inconsistency between the more accurate, but more data intensive, methods appropriate for more recent periods and the less accurate, but less data intensive, methods appropriate to the more distant past. In this study, multiple methods are harmonized in a seamless reconstruction of historical PET and RET by quantifying and eliminating the biases of the simple Hargreaves-Samani method relative to the more complex and accurate Priestley-Taylor and Penman-Monteith methods. This harmonization process is used to generate long-term, internally consistent, spatiotemporal databases of PET and RET.