Phenology is the study of seasonal events in plants and animals. Disturbances in plant phenology due to global warming have been reported in many locations around the world. As with external phenomena, such as flowering and leaf fall, gene function is also thought to be seasonally controlled in plant cells. It is necessary, therefore, to improve the prediction methods of plant phenology by incorporating gene expression analyses. The most prominent data set from my project is a two-year seasonal transcriptome of Arabidopsis covering 20,000 genes. The data it provides allows us to model many genes against meteorological data. The method we have developed can be applied to various technologies, enabling early reports of plant phenology, predictions of plant responses to global warming, designed breeding of crops, and other functions.