The National Institute of Standards and Technology (NIST) is currently developing a photomask linewidth standard (SRM 2059) with a lower expected uncertainty of calibration than the previous NIST standards (SRMs 473, 475, 476). In calibrating these standards, optical simulation modeling has been used to predict the microscope image intensity profiles, which are then compared to the experimental profiles to determine the certified linewidths. Consequently, the total uncertainty in the linewidth calibration is a result of uncertainty components from the optical simulation modeling and uncertainty due to experimental errors or approximations (e.g., tool imaging errors and material characterization errors). Errors of approximation in the simulation model and uncertainty in the parameters used in the model can contribute a large component to the total linewidth uncertainty. We have studied the effects of model parameter variation on measurement uncertainty using several different optical simulation programs that utilize different mathematical techniques. We have also evaluated the effects of chrome edge runout and varying indices of refraction on the linewidth images. There are several experimental parameters that are not ordinarily included in the modeling simulation. For example, the modeling programs assume a uniform illuminating field (e.g., Koehler illumination), ideal optics and perfect optical alignment. In practice, determining whether Koehler illumination has been achieved is difficult, and the optical components and their alignments are never ideal. We will present some techniques for evaluating Koehler illumination and methods to compensate for scattered (flare) light. Any such experimental elements, that are assumed accurate in the modeling, may actually present significant components to the uncertainty and need to be quantitatively estimated. The present state of metrology does not permit the absolute calibration of linewidth standards to the level of uncertainty called for in the semiconductor roadmap. However, there are applications for a linewidth standard and calibration strategies which do not require a NIST certified calibration (e.g., determining measurement precision). In this paper we present various critical elements of a systematic and thorough evaluation of the key components of linewidth uncertainty as well as our methods for evaluating and reducing modeling and experimental uncertainties.