The short-wavelength infrared bands of the Thermal And Near-infrared Sensor for carbon Observation (TANSO)-Fourier transform spectrometer (FTS) instrument onboard the Greenhouse gases Observing SATellite (GOSAT) have degraded that affects the retrieval of data for CO2 and CH4. Herein, a new algorithm that uses principal component analysis (PCA) to evaluate these degradations from on-orbit solar calibration spectra has been developed. The datasets of the spectra were decomposed using PCA, and the temporal variations of their components were fitted using the appropriate functions. Our results show that PCA is effective to construct a suitable degradation model for TANSO-FTS. Comparisons of CO2 data retrieved using the new degradation model with that using the ground-based FTS indicate that the new model improves the measurement biases.