Aplicación de los métodos de Cressman y Fast Barnes en la interpolación de variables meteorológicas: recursos clave para estudiantes de Matemática en la ESPOCH

Abstract

The interpolation of meteorological variables, such as temperature and precipitation is crucial for understanding and predicting climate in areas with missing data. In Chimborazo, the loss of data in meteorological station records negatively impacts future projections of these variables. This research is intended to compare and analyze two interpolation methods widely used in the field of meteorology: the Cressman method and the Fast Barnes method to determine which is more suitable for filling in missing temperature data in Chimborazo. The study adopts a qualitative approach with a descriptive scope and a documentary research design, focusing on the bibliographic review of the methods mentioned above and their implementation in Python. The accuracy and influence of the terrain on the predictions are evaluated using data collected from meteorological stations at different altitudes and topographies within the province of Chimborazo. The results show that although the Barnes and Fast Barnes methods generate smoother and visually continuous surfaces, the Cressman method offers greater accuracy in capturing local variations, reflected in a lower RMS error. This research concludes that the Cressman method is the most accurate for capturing local temperature variations, while the Barnes and Fast Barnes methods are preferable for smoother surfaces. The choice of interpolation method should be based on the characteristics of the dataset and the objectives of the analysis. This study provides a solid foundation for the effective application of interpolation techniques in meteorological and climatic studies in regions such as Chimborazo.