Calibrated climate-based lighting simulation models of buildings have the capacity to perform an essential role in postoccupancy evaluations, such as annual frequency assessments of daylighting quality and visual discomfort. However, in most postoccupancy case studies the role of lighting analysis is temporally limited by instantaneous measurements or limited in scale by requiring constant monitoring with expensive sensors. It is challenging to build calibrated models based on point-in-time measurements due to the presence of electric lighting, transient use of dynamic shades, limited information on the material specifications, and short durations of accessibility to the spaces being studied. The authors propose and present a calibration process for annual daylighting and electric lighting simulation models based on one-time field measurements of large daylit and electrically lit spaces exemplified through a data set of 540 individual office desks across 10 office spaces. The calibration process includes measuring lighting, physical, and material data during a one-time visit that are used to calibrate high dynamic range images and lighting simulation models using actual weather data. The calibration accuracy is validated based on measured and simulated luminance and illuminance data. Comparing measured and simulated illuminance, relative root mean squared error (RMSE) values were 25.8% and 45.5% for horizontal and vertical measurements, respectively. When tracking errors using log10(illuminance), approximating human perceptual differences, errors of 4.3% and 6.8% were achieved. Vertical illuminance was found to vary more with measured data due to the uncertainty of monitor screen luminances. The authors aim to achieve calibrated lighting models that are reliable enough to be used in assessing the relationship of annualized lighting metrics to participants' long-term perceptions of lighting quality, thereby enabling simulation models to be used in the postoccupancy evaluation process of building lighting. This article demonstrates that measured data through one-time visits can be utilized to build reliable calibrated lighting simulation models to integrate long-term annual lighting results in postoccupancy evaluations.