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Many studies have indicated that structural strain will be significantly influenced by temperature variations, and a good understanding of the effect of temperature on structural strain is essential. A structural health monitoring system has been installed in a typical Tibetan timber building to measure the structural strains and ambient temperature since 2012. This paper presents the correlation between temperature and strain data from the monitored structure. A method combining singular spectrum analysis and polynomial regression is proposed for modeling the temperature induced strains in the structure. Singular spectrum analysis is applied to smooth the temperature data, and the correlation between the resulting temperature time series and the measured strains is obtained by polynomial regression. Parameters of the singular spectrum analysis and the regression model are selected to have the least regression error. Results show that the proposed method has both good reproduction and prediction capabilities for temperature induced strains, and that the method is accurate and effective for eliminating the effect of temperature from the measured strain. A standardized Novelty Index based on the residual strain is also used for the condition assessment of the structure. [ABSTRACT FROM AUTHOR]