UFLR is one of an evolving set of FLIR performance prediction programs used at sea to predict the ranges for detection, classification, and identification of target ships. One aid in the validation of such a program is a sensitivity analysis of the program parameters. Sensitivity analyses indicate that the ranges for detection, classification, and identification are strongly sensitive to target areas, target-to-background, temperature difference and atmospheric conditions such as windspeed, visibility, humidity, and vertical temperature, humidity, and pressure profiles. One uncontrollable parameter is the noncontiguity in space and time of the radiosonde and FLIR measurements. This problem was investigated by dithering the radiosonde data, input to UFLR, with a random number generator to generate variations in the pressure, temperature, and relative humidity in the atmospheric profile. Results indicate that noncontiguity of measurements can lead to 50% error in range predictions.