Copula-Based Bias Correction for Wind Speed Data This repository provides code to reproduce the methods and results from the paper: A Copula-Based Bivariate Bias Correction Method for Super-Resolved Physics-Based Wind Speed Data Published in IEEE Overview Accurate wind speed data is essential for applications such as renewable energy integration, power system resilience, and extreme event analysis. Physics-based and reanalysis datasets (e.g., ERA5 and MERRA-2) often exhibit systematic biases relative to observations, particularly in the tails of the distribution. This repository implements a copula-based bivariate bias correction framework designed to:

• Correct marginal distribution biases in wind speed data
• Preserve dependence structure between variables
• Improve representation of extreme wind events
• Enable consistent integration across multiple datasets Unlike univariate bias correction methods, this approach explicitly models joint dependence using copulas, leading to more physically consistent corrected data.