  In recent years there has been considerable interest in using photonic
thermometers such as Fiber Bragg grating (FBG) and silicon ring resonators as
an alternative technology to resistance-based legacy thermometers. Although FBG
thermometers have been commercially available for decades their metrological
performance remains poorly understood, hindered in part by complex behavior at
elevated temperatures. In this study we systematically examine the temporal
evolution of the temperature response of 14 sensors that were repeatedly cycled
between 233 K and 393 K. Data exploration and modelling indicate the need to
account for serial-correlation in model selection. Utilizing the coupled-mode
theory treatment of FBG to guide feature selection we evaluate various
calibration models. Our results indicates that a dynamic regression model can
effectively reduce measurement uncertainty due to hysteresis by up to $\approx
70 \%$
