Skip to main content

A tool to convert ERA5/ECMWF data to EnergyPlus Weather (EPW) format

Project description

tests PyPI - Version PyPI - Downloads GitHub License

ERA5 to EPW Converter

A tool that fetches ERA5 data and generates a full year AMY (Actual Meteorological Year) EnergyPlus Weather file (EPW).

The tool takes care of fetching the necessary data from the Copernicus Climate Data Store (CDS) and the Copernicus Atmosphere Data Store (CAMS), processing it, and formatting it into the EPW format. It's designed for fast and efficient data retrieval.

Installation

Prerequisites

Make sure to register for an API key and validate licences at:

Then create the file ~/.cdsapirc with the following content:

url: https://cds.climate.copernicus.eu/api/v2
key: <your_api_key>

Note: the URL will be dynamically managed by the script depending on the data source. The API key doesn't vary, it's the same for both ERA5 and CAMS data.

Moreover, before proceeding, it is required to accept all the licenses in the section "Your profile" in the website of Copernicus.

Install the package

From PyPI

pip install era5epw

From source

Clone the current repository and install the required dependencies using Poetry:

git clone https://github.com/airboxlab/era5epw.git
poetry install

Usage

[!NOTE] When running in a Jupyter notebook, to make progress bars and interactive widgets work, make sure to install ipywidgets and to enable the widgets extension.

pip install ipywidgets
# optional, not needed with Jupyter Notebook 7+
jupyter nbextension enable --py widgetsnbextension

Generating EPW Files

Command line interface

Example usage:

# using poetry, execute in local repository
poetry run era5epw_download --year 2024 --latitude 49.4 --longitude 0.1 --city-name "Le Havre" --elevation 0 --time-zone 1

# using installed binary, after pypi package installation
era5epw_download --year 2024 --latitude 49.4 --longitude 0.1 --city-name "Le Havre" --elevation 0 --time-zone 1

By default, the time-zone argument is used only to populate the LOCATION header and data time is UTC. Use --apply-time-zone-to-data to apply it to the date and time fields (this will shift the UTC time by the provided time zone offset).

Use --help to have a list of available options.

Python API

Example usage:

from era5epw.main import download_and_make_epw

download_and_make_epw(
    year=2025,
    latitude=48.8,
    longitude=2.4,
    city_name="Paris",
    time_zone=1,
    elevation=0,
    output_file="/tmp/era5epw_paris_2025.epw",
    apply_time_zone_to_data=True,
)

Visualizing EPW Files

The package includes an interactive visualization tool for EPW files that supports three types of plots: 2D line charts, 3D surface plots, and radar (polar) plots.

Command line interface

# List available weather series in an EPW file
era5epw_visualize path/to/file.epw --list-series

# Create a 2D line plot (default)
era5epw_visualize path/to/file.epw --series "Dry Bulb Temperature" --type 2D

# Create a 3D surface plot
era5epw_visualize path/to/file.epw --series "Wind Speed" --type 3D

# Create a radar plot showing daily min/max values
era5epw_visualize path/to/file.epw --series "Global Horizontal Radiation" --type radar

# Save visualization to HTML file
era5epw_visualize path/to/file.epw --series "Dry Bulb Temperature" --output visualization.html

Python API

Use in Jupyter notebooks or Python scripts:

from era5epw.visualize import visualize_epw

# Create interactive 2D plot
fig = visualize_epw(
    epw_file_path="path/to/file.epw",
    series_name="Dry Bulb Temperature",
    plot_type="2D",
    show=True  # Display immediately in Jupyter
)

# Create 3D surface plot
fig = visualize_epw(
    epw_file_path="path/to/file.epw",
    series_name="Wind Speed",
    plot_type="3D",
    show=True
)

# Create radar plot
fig = visualize_epw(
    epw_file_path="path/to/file.epw",
    series_name="Global Horizontal Radiation",
    plot_type="radar",
    show=True
)

# Save to HTML file
fig.write_html("visualization.html")

EPW Visualization

Documentation

ERA5
CAMS
EPW format
Earthkit

Datasets home pages:

View your API requests and download responses at:

CDS Requests
ADS Requests

Check CDS API status at CDS Live, it provides information about congestion for each dataset.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

era5epw-0.6.0.tar.gz (21.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

era5epw-0.6.0-py3-none-any.whl (22.9 kB view details)

Uploaded Python 3

File details

Details for the file era5epw-0.6.0.tar.gz.

File metadata

  • Download URL: era5epw-0.6.0.tar.gz
  • Upload date:
  • Size: 21.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.1 CPython/3.10.12 Linux/6.8.0-101-generic

File hashes

Hashes for era5epw-0.6.0.tar.gz
Algorithm Hash digest
SHA256 e4b05d406fe61ba6ea8127d6c19c6789c4428ab21d1f0316edf5a3b51da32b22
MD5 8095a9767ba48a508f9428a1bac34e8b
BLAKE2b-256 0d71c3a8dbbdbe7c9bf45ef2e18df69ccf5b211b5836cc37e6f4d0b6f90f2171

See more details on using hashes here.

File details

Details for the file era5epw-0.6.0-py3-none-any.whl.

File metadata

  • Download URL: era5epw-0.6.0-py3-none-any.whl
  • Upload date:
  • Size: 22.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.1 CPython/3.10.12 Linux/6.8.0-101-generic

File hashes

Hashes for era5epw-0.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 714e7cebdc853e5adb5137d5a27e02e061ce88ff9a86c77b50ca102057dc881c
MD5 85f7e4afa79a13b0d30aa057ea6dd8f5
BLAKE2b-256 f97dbd3adeeaa88f1fce15ba7a56fa3f0a6150fcc6f5707d8e53f10d0f4c4f83

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page