Towards Analysing Climate Change Temperature Patterns through Stream Clustering Methods

Climate change has an effect on the environmental conditions of different regions. Being able to track these changes is a powerful tool for adapting to evolving conditions. Weather data is continuously generated across multiple stations around the world, providing valuable information on climate time-varying patterns. Studying this data stream enables us to understand the new climate patterns better. This paper explores, through a stream clustering algorithm, the potential of employing weather data in different geographical locations to track the change in climate patterns in the Spanish region of Navarre over the last 20 years. The case study showed the applicability of stream methods to the incremental segmentation of geographical regions based on their climatology factors. In this study, we have found that the climate of Navarre is homogenising into the particular climate of southwestern regions, which is expanding. This particular finding may raise concerns about the time-varying impact that climate change is having on Navarre regions, where large parts of its geography can be grouped into a single climate.