Copernicus Marine Wave Data: From Download to Analysis (Python)

In this tutorial, you'll learn how to download, analyze, and visualize real global wave data from the Copernicus Marine Service using Python and Google Colab. We'll guide you through defining your area of interest, extracting wave parameters at a virtual buoy, and creating insightful plots like wave roses and heatmaps. 🔧 What you’ll learn: • How to access and download wave reanalysis data from Copernicus Marine Service • How to define your area of interest, site of interest, and a virtual buoy • How to extract wave parameters (Hs, Tp, wave direction) at a virtual buoy location • How to create visualizations: time series plots, wave roses, and heatmaps • How to analyze extreme wave events and estimate return periods using Gumbel and GEV distributions • How to explore temporal trends and anomalies in wave data This tutorial is ideal for students and researchers in oceanography, coastal engineering, marine science, and environmental data analysis. 📁 Software used: • Google Colab • Python libraries: copernicusmarine, windrose, cartopy, xarray, pandas, matplotlib, and others 📦 GitHub repository: 👉 https://github.com/Alerovere/CoastalH... ⸻ 👨‍🏫 For educators and students This tutorial is part of the CoastalHydrodynamics project — a collection of tools designed for teaching and research in coastal hydrodynamics and climate adaptation. It was developed by Alessio Rovere at Ca' Foscari University of Venice, with support from ChatGPT by OpenAI, as part of the WARMCOASTS project (funded by the European Research Council - grant agreement n. 802414).📍 Designed for use in Google Colaboratory – no installation required.