Download any data from https://cds.climate.copernicus.eu/datasets faster using parallel processing. Climate Data Store/ Copernicus website/ Climate change service dataset. This article introduces a parallelized Python workflow that allows you to download ERA5 data significantly faster and HPC-compatible.
Find the scrip here parallel-ERA5-data-download.ipynb
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Downloading ERA5 data serially can be extremely slow when working with:
- Long time periods
- Multiple variables
- Large spatial domains
- Parallelizing independent CDS API requests
- Maximizing I/O throughput
- Maintaining a clean, reproducible research workflow
- 🚀 Faster downloads using parallel processing
- 🔁 Multiple CDS requests sent simultaneously
- 🖥️ HPC-compatible (SLURM / PBS / compute nodes)
- ⚙️ Uses the official CDS API
- 📦 Modular, readable, and easy to extend