Upper-tail correction of multivariate synthetic environmental series using annual maxima

This repository contains the complete code for the Upper-tail correction technique described in this brief report published in Stochastic Environmental Research and Risk Assessment. The notebooks folder contains the examples used in the paper.

The code is also implemented in the Bluemath Python package developed by GeoOcean.

Repository Structure

• src: This folder contains the core implementation of the Upper-tail correction technique and other utils functions employed in the code. The provided class performs the correction without stratification.

• Notebooks: These notebook demonstrates the application of the correction technique for Santoña, Spain in two different variables, significant wave height ($H_s$) and wave peak period ($T_p$). The step-by-step process illustrates how the method refines extreme value estimates.

Example Workflow

The correction process typically involves the following steps:

• Load your dataset (e.g., Hs data).
• Initiate the ExtremeCorrection class.
• Fit the model to the data and apply the correction.
• Generate and analyze the corrected figures, which will be saved automatically in the selected folder.

Citation

If you use Upper-tail correction technique in your research, please cite it using the following BibTeX entry:

@article{Collado2026,
  author    = {Víctor Collado and Fernando J. Méndez and Roberto Mínguez},
  title     = {Upper-tail correction of multivariate synthetic environmental series using annual maxima},
  journal   = {Stochastic Environmental Research and Risk Assessment},
  year      = {2026},
  month     = apr,
  day       = {1},
  volume    = {40},
  number    = {4},
  pages     = {92},
  issn      = {1436-3259},
  doi       = {10.1007/s00477-026-03215-0},
  url       = {https://doi.org/10.1007/s00477-026-03215-0}
}