Influence of synoptic patterns (NAO vs. WeMO) on rainfall isotopic composition in SE Iberia: A machine learning approach

This repository contains the full computational workflow supporting the manuscript:

“Influence of synoptic patterns (NAO vs. WeMO) on rainfall isotopic composition in SE Iberia: A machine learning approach”

The framework integrates precipitation-isotope observations from the Sierra de Segura monitoring network, large-scale atmospheric circulation indices (NAO and WeMO), station metadata, and trajectory-based atmospheric diagnostics to quantify the seasonal hierarchy of controls on rainfall isotopic composition in southeastern Iberia.

The repository includes the workflows for WeMOi reconstruction, isotope-data preprocessing and monthly aggregation, statistical and multivariate analyses, Random Forest and SHAP modelling, HYSPLIT trajectory post-processing, transport-regime clustering, figure generation, and the computational environment required for reproducibility.

All processed datasets, derived products, and scripts required to reproduce the analyses and figures presented in the manuscript are included in this repository.

Given the provided files and environment specification, the main results of the study can be reproduced.