Modal properties are widely used for structural model updating and damage detection, yet their sensitivity to environmental conditions, particularly temperature can complicate interpretation. This paper investigates how seasonal temperature variations affect structural identification based on modal properties, using a falsification-based approach. A railway bridge in service is used as a case study, with data from both forced vibration testing and long-term monitoring. Freezing temperatures are found to increase overall stiffness by up to 90%, including a significant rise in boundary stiffness, an increase in ballast modulus of up to 10 GPa, and the activation of rail continuity stiffness. The set of plausible physical models shifts between winter and summer, demonstrate that structural behaviour varies seasonally and that identification results are not directly transferable across temperature ranges. Compared to traditional residual minimisation, model falsification provides a more comprehensive and robust set of plausible models and avoids unreliable parameter estimates. These findings underscore the need for temperature-sensitive identification strategies and adaptive models to support accurate interpretation, damage detection, and seasonally informed maintenance decisions in structural health monitoring.