edilia12380/era5-daily-weather-western-europe

ERA5 Daily Weather Data - Western Europe

This dataset contains 630 NetCDF files of ERA5 reanalysis data covering Western Europe, curated for climate research and weather forecasting applications.

This work uses ERA5 reanalysis data from the Copernicus Climate Change Service (C3S), accessed via the Climate Data Store. We acknowledge the European Commission and ECMWF for producing and making available this dataset.

📄 Associated Research

This dataset was curated for and used in the following article:

Spatial Predictor Selection for Next-Day Minimum Temperature Forecasting: An Automated Machine Learning Framework Applied Across European Climate Regimes
Eric Duhamel, 2026 DOI: 10.31223/X55758 (preprint)

If you use this dataset, please cite both the article above and the original Copernicus data source (see ACKNOWLEDGMENTS.md).

Dataset Description

Variables

The variables were selected based on the research objective: forecasting next-day minimum temperatures (Tmin at D+1).

Variable	Description	Unit
10m_u_component_of_wind_daily_mean	Zonal wind at 10 m (daily mean) m/s	m/s
10m_v_component_of_wind_daily_mean	North-south wind component at 10 m (daily mean)	m/s
10m_wind_gust_since_previous_post_processing_daily_max	Maximum wind gust at 10 m	m/s
2m_temperature_daily_minimum / maximum	Air temperature at 2 m (daily min / max)	K
2m_dewpoint_temperature_daily_minimum	Minimum dewpoint temperature at 2 m	K
boundary_layer_height_daily_minimum / maximum	Boundary layer height (daily min / max)	m
evaporation_daily_sum	Surface evaporation (daily accumulated)	m
low_cloud_cover_daily_mean	Low cloud cover (daily mean)	0-1
medium_cloud_cover_daily_mean	Medium cloud cover (daily mean)	0–1
high_cloud_cover_daily_mean	High cloud cover (daily mean)	0–1
total_cloud_cover_daily_mean	Total cloud cover (daily mean)	0-1
mean_sea_level_pressure_daily_mean	Mean sea level pressure (daily mean)	Pa
sea_surface_temperature_daily_mean	Sea surface temperature (daily mean)	K
skin_temperature_daily_minimum	Minimum surface skin temperature	K
soil_temperature_level_1_daily_minimum	Minimum soil temperature (layer 1)	K
soil_temperature_level_2_daily_minimum	Minimum soil temperature (layer 2)	K
surface_latent_heat_flux_daily_sum	Latent heat flux (daily accumulated)	J/m²
surface_sensible_heat_flux_daily_sum	Sensible heat flux (daily accumulated)	J/m²
surface_net_thermal_radiation_daily_sum	Net thermal radiation at surface (daily sum)	J/m²
surface_solar_radiation_downwards_daily_sum	Downward solar radiation at surface (daily sum)	J/m²
surface_thermal_radiation_downwards_daily_mean	Downward thermal radiation at surface (daily mean)	W/m²
total_column_water_vapour_daily_mean	Total column water vapour (daily mean)	kg/m²
total_precipitation_daily_sum	Total precipitation (daily accumulated)	m
volumetric_soil_water_layer_1_daily_mean	Volumetric soil water content (layer 1)	m³/m³
snow_depth_daily_mean	Snow depth (daily mean)	m

Spatial Coverage

• Bounding box: [63.16, -15.19, 36.45, 18.44] (North, West, South, East)
• Resolution: 0.25° × 0.25° (ERA5 native)
• Region: Western Europe

Temporal Coverage

• Period: 2004-01-01 to 2024-12-31 (21 years)
• Frequency: 1-hourly
• Time zone: UTC
• Aggregation: Daily statistics (min, max, mean)

File Format

• Format: NetCDF4 (.nc)
• Total files: 630
• Total size: ~7.55 GB

File Naming Convention

{variable}_{aggregation}_{year}.nc

Where:

• {variable}: meteorological variable name (e.g., 2m_dewpoint_temperature, surface_pressure)
• {aggregation}: daily statistic type (daily_mean, daily_max, or daily_min)
• {year}: four-digit year (2004–2024)

Example: 2m_dewpoint_temperature_daily_mean_2012.nc

Quick Start

Loading the data

import xarray as xr

# Load a single file
ds = xr.open_dataset("data/filename.nc")

# Load all files
ds = xr.open_mfdataset("data/*.nc", combine='by_coords')

Using the analysis script

A utility script is provided to quickly inspect NetCDF files:

python scripts/nc_analysis.py <nc_file_name>

This script displays:

• Variable names and dimensions
• Coordinate ranges (lat, lon, time)
• Basic statistics

Dataset Structure

era5-daily-weather-western-europe/
├── README.md
├── ACKNOWLEDGMENTS.md
├── data/
│   ├── file_001.nc
│   ├── file_002.nc
│   └── ... (630 files)
└── scripts/
    └── nc_analysis.py

Download Parameters

These files were retrieved from the Copernicus Climate Data Store using the following parameters (example for 2m_temperature_daily_minimum):

import cdsapi

dataset = "derived-era5-single-levels-daily-statistics"
request = {
    "product_type": "reanalysis",
    "variable": ["2m_temperature"],
    "year": "2012",
    "month": [
        "01", "02", "03",
        "04", "05", "06",
        "07", "08", "09",
        "10", "11", "12"
    ],
    "day": [
        "01", "02", "03",
        "04", "05", "06",
        "07", "08", "09",
        "10", "11", "12",
        "13", "14", "15",
        "16", "17", "18",
        "19", "20", "21",
        "22", "23", "24",
        "25", "26", "27",
        "28", "29", "30",
        "31"
    ],
    "daily_statistic": "daily_minimum",
    "time_zone": "utc+00:00",
    "frequency": "1_hourly",
    "area": [63.16, -15.19, 36.45, 18.44]
}

client = cdsapi.Client()
client.retrieve(dataset, request).download()

Citation

If you use this dataset, please cite:

1. This dataset and associated research:

@article{duhamel2026,
  author    = {Duhamel, Eric},
  title     = {Spatial Predictor Selection for Next-Day Minimum Temperature Forecasting: An Automated Machine Learning Framework Applied Across European Climate Regimes},
  journal   = {EarthArXiv (preprint)},
  year      = {2026},
  doi       = {10.31223/X55758},
  url       = {https://doi.org/10.31223/X55758}
}

2. Original data source: See ACKNOWLEDGMENTS.md

License

• Dataset curation, scripts, documentation: CC BY Attribution 4.0 International
• ERA5 data: CC-BY 4.0 (Copernicus Climate Change Service)
• Link to the license: Creative Commons Attribution 4.0 International (CC-BY 4.0)

Contact

• Author: Eric Duhamel
• Email: edilia12380@gmail.com
• Issues: Use the Community tab on this repository