Findings are presented from a research study conducted in Texas to determine the significance of seasonal variation in skid measurements. Six bituminous highway pavement sections, two each from three different climatic regions, were monitored over a period of more than 18 months. Monitoring included collection of wet pavement skid resistance data using a locked-wheel skid trailer that met the specifications of ASTM E-274. These measurements were made at biweekly intervals in two of the three climatic regions and at monthly intervals in the remaining climatic region. The necessary climatic data were obtained from nearby National Climatic Data Centers. The data obtained indicated that significant variation in skid numbers occurs from one day of measurement to another. The maximum variations observed were on the order of 10 to 12 skid numbers. Furthermore, there were strong indications that the variations occurred in response to changes in temperature and precipitation. Finally, three methods of normalizing the skid data to obtain the true mean skid number of the pavement were evaluated. The first of these was a linear regression model based on rainfall, temperature, and other variables. The second was a nonlinear regression model based on Julian calendar day only. The third approach examined the possibility of using multiple skid measurements to achieve a desired level of accuracy. The advantages and disadvantages of each method are discussed.