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PabloTassi/Marine-Energy-South-Africa

Domaine:

environment and energy
Créateur:
Pab
Hôte:
Marine energy and offshore wind farm assessment - South Africa # Marine Energy and Offshore Wind Farm Assessment - South Africa This Jupyter Notebook provides a comprehensive analysis of oceanographic conditions for offshore wind farm site assessment in South African coastal waters. ## 📚 Course Information **Institution:** École des Ponts **Project:** Marine Energy 2025-2026 **Region:** South Africa (40°S to 29°S, 14°E to 34°E) ## 🎯 Learning Objectives - Analyze oceanographic data from Copernicus Marine Service - Understand major current systems (Agulhas and Benguela currents) - Assess sediment transport processes and scour hazards - Evaluate offshore wind farm site suitability - Visualize ocean dynamics through animations and plots ## 🔧 Prerequisites - Python 3.8 or higher - Jupyter Notebook or JupyterLab - Required Python packages (see Installation section) ## 📦 Installation on Windows ### Method 1: Using Anaconda/Mamba (Recommended) Anaconda is **highly recommended for Windows users** as it handles complex dependencies (especially cartopy) much better than pip. #### Step 1: Download and Install Anaconda 1. Visit anaconda.com 2. Download the Windows installer (64-bit recommended) 3. Run the installer: - ✅ Check "Add Anaconda to my PATH environment variable" (optional but helpful) - ✅ Check "Register Anaconda as my default Python" 4. Complete the installation #### Step 2: Open Anaconda Prompt - Search for "Anaconda Prompt" in the Start menu - Right-click and select "Run as administrator" (recommended) #### Step 3: Create a new environment ```bash conda create -n copernicus_env python=3.12 -y ``` Type `y` to proceed if prompted. #### Step 4: Activate the environment ```bash conda activate copernicus_env ``` Your prompt should now show `(copernicus_env)`. #### Step 5: Install conda packages ```bash conda install -c conda-forge numpy pandas xarray matplotlib cartopy netCDF4 jupyter ipykernel scipy -y ``` This may take a few minutes. Conda will handle all dependencies automatically. #### Step …

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