A proposal for a fuzzy climate classification index for Colombia
Una propuesta de un índice difuso de clasificación climática para Colombia
DOI:
https://doi.org/10.22517/23447214.25894Keywords:
climate change, climate classification, climate, fuzzy logic, temperatureAbstract
This study developed a fuzzy logic-based climate classification index for Colombia, integrating hydroclimatic, air quality, and topographic variables through a three-phase methodology. In Phase 1 (2010-2022), multisource data acquisition processed precipitation (600-8000 mm/year), temperature (14-32°C), humidity (28-95%), PM₂.₅ (6-35 µg/m³), and NO₂ (10-60 ppb) using IDEAM's DHIME portal and NASA Giovanni products, with quality-controlled interpolation. Phase 2 implemented a Mamdani-type fuzzy inference system in FisPro, creating 127 "If-Then" rules through nonlinear correlation analysis (Spearman >0.65) and expert knowledge, using MIN-MAX operators and adaptive weights (0.3 rural/0.5 urban pollution coefficients). Phase 3 geospatial implementation achieved 84.5% cross-validation accuracy (MAE=1.2, RMSE=1.8), generating vulnerability maps (0-10 scale) through QGIS processing. Results revealed extreme climate variability: precipitation gradients (600 mm/year in Riohacha to 8000 mm in Quibdó), urban heat islands (Neiva 30°C vs. Bogotá 16°C), and pollution hotspots (Barranquilla 30 µg/m³ PM₂.₅ vs. Leticia 6 µg/m³). The fuzzy index outperformed traditional methods (Köppen, Thornthwaite) by capturing nonlinear interactions, showing 15% agricultural yield reductions in high-NO₂ zones and identifying vulnerability thresholds for coffee rust outbreaks (>80% humidity) and urban heat stress (85% RH = 41°C felt temperature). The model's adaptive structure effectively addressed Colombia's climatic heterogeneity while overcoming rigid classification limitations, providing a robust tool for climate risk assessment under anthropogenic change scenarios, though future work should incorporate higher-resolution pollution data to reduce the 15% uncertainty in industrial zones.
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