Estimates of daily lake evaporation based on energy-budget data are poor because of large errors associated with quantifying change in lake heat storage over periods of less than about 10 days. Energy-budget evaporation was determined during approximately biweekly periods at a northern Minnesota, USA, lake for 5 years. Various combinations of shortwave radiation, air temperature, wind speed, lake-surface temperature, and vapour-pressure difference were related to energy-budget evaporation using linear-regression models in an effort to determine daily evaporation without requiring the heat-storage term. The model that combined the product of shortwave radiation and air temperature with the product of vapour-pressure difference and wind speed provided the second best fit based on statistics but provided the best daily data based on comparisons with evaporation determined with the eddy-covariance method. Best-model daily values ranged from −0.6 to 7.1 mm/day over a 5-year period. Daily averages of best-model evaporation and eddy-covariance evaporation were nearly identical for all 28 days of comparisons with a standard deviation of the differences between the two methods of 0.68 mm/day. Best-model daily evaporation also was compared with two other evaporation models, Jensen–Haise and a mass-transfer model. Best-model daily values were substantially improved relative to Jensen–Haise and mass-transfer values when daily values were summed over biweekly energy-budget periods for comparison with energy-budget results.