Large-scale estimation of evapotranspiration (ET) remains challenging because no direct remote sensing estimates of ET exist and because most data-driven estimation approaches require assumptions about the impact of moisture conditions and biogeography on ET. The surface flux equilibrium (SFE) approach offers an alternative, deriving ET directly from atmospheric temperature and humidity under the assumption that conditions in the atmospheric boundary layer reflect ET’s land boundary condition. We present a 4  km resolution, continental United States-wide, daily ET dataset spanning from 1979 to 2024 using the SFE method. The Bowen ratio is first calculated using the SFE method solely based on temperature and specific humidity estimates from gridMET and then converted to ET using net radiation and ground heat fluxes from ERA5-Land. We evaluate its performance using extended triple collocation to estimate the standard deviation of the random error and the correlation coefficient of SFE ET compared to true ET, as well as those of three widely used alternative ET datasets: GLEAM, FluxCom, and ERA5-Land. Despite its extreme simplicity, SFE ET achieves performance comparable to or exceeding the other datasets across large portions of CONUS, particularly in the Western U.S., while requiring no information about land surface, vegetation, or soil properties and no assumptions about ET’s response to environmental and climate drivers. Our results support the use of SFE as a scalable, observation-driven method for estimating ET.