Analysis of Meteorological climatic parameters using wavelet an‎d data mining: a case study of northern IranN

1/30/2026 12:00:00 AM

This study was conducted to investigate the effects of large-scale climatic indices, including the El Niño–Southern Oscillation (ENSO) an‎d Sunspot Number (SSN), on the climatic variability of Gilan Province an‎d to provide a framework for rainfall classification. Precipitation, temperature, an‎d dew point data were extracted from the ERA5 reanalysis for the period 1951–2023, while ENSO an‎d SSN indices were obtained from NOAA an‎d SIDC. Continuous Wavelet Transform (CWT) an‎d Wavelet Coherence (WTC) were applied to analyze time–frequency cycles. The results showed that ENSO exhibited 2–8-year cycles an‎d SSN exhibited 10–12-year cycles, both exerting significant effects on precipitation, temperature, an‎d humidity in the region, sometimes with several months of delay. Subsequently, rainfall data were divided into three classes (“low,” “moderate,” an‎d “high”), an‎d four data mining algorithms—Decision Tree, Ran‎dom Forest, Naïve Bayes, an‎d K-Nearest Neighbor—were used for climatic classification. Model performance was eva‎luated using five-fold cross-validation, an‎d the metrics Precision, Recall, an‎d F1-Score were calculated. The results indicated that Ran‎dom Forest achieved the best performance, with an average Precision of about 79.5%, Recall of 78.8%, an‎d F1 of 79%, while Naïve Bayes produced the weakest results. A common limitation across all models was observed in classifying the moderate class, reflecting the natural overlap of the data in this range. These findings suggest that the combination of wavelet analysis an‎d data mining can serve as an effective tool for rainfall prediction an‎d for the management of water resources an‎d agriculture in northern Iran.

نوسان جنوبي ال‌نينو (ENSO) , لكه‌هاي خورشيدي (SSN) , استان گيلان , تبديل موجك , داده كاوي

El Niño–Southern Oscillation (ENSO) , Sunspot Number (SSN) , Gilan Province , Wavelet Analysis , Data Mining

Sara Eskandari

Mahboube Molavi Arabshahi