Year: 2026
Type: preprint
Abstract: The assessment of wind energy resources in large regions presents a substantial challenge for energy system operators due to the intricacies involved in accurately describing all atmospheric circulation patterns and, even more so, modeling their inherent dynamics. This research primarily aimed to identify the prevailing synoptic weather patterns over continental Mexico and its surrounding regions. The study utilized ERA5 Reanalysis daily mean sea level pressure anomaly data and two widely recognized clustering techniques, k-means and self-organizing maps, to achieve this objective. Research findings indicate that four weather patterns, estimated using k-means clustering, are sufficient to explain daily atmospheric variability over continental Mexico. However, the fifteen weather patterns identified through the self-organizing-maps technique suggest that the k-means-determined patterns can be complemented by interconnected transition patterns, which represent a more intricate dynamics within the tropical and subtropical atmosphere. The second primary objective of this research is to assess and analyze the impact of weather patterns on the wind velocity field and energy availability across continental Mexico. This assessment employed a probabilistic methodology grounded in the L-moments theory and the inference of a regional wind-speed model, which was supported by the Weibull and Kappa distributions. The findings indicate that fluctuations in large-scale weather patterns across the continental Mexican influence the potential wind energy production significantly. For instance, in the Oaxaca region, the potential wind energy fluctuates between 189 and 734 W/m^2. These results emphasize the crucial influence of these weather patterns on energy production and highlight the need for a comprehensive study within a forecasting framework to enhance the current operation of the Mexican electrical system.
DOI: 10.31223/x5mb8g
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7214317828