Climate scenarios CH2025

info

For CH2018 data, see the NCCS website.

The localized Climate CH2025 datasets consist of 30-year daily time series for different Global Warming Levels (GWLs) and the reference period 1991–2020 for several climate variables at individual Swiss stations (DAILY-LOCAL) and on a regular 1 km grid covering the area of Switzerland (DAILY-GRIDDED). All datasets were produced by bias-adjusting and downscaling regional climate model data, including data for the 1991-2020 reference period. They do not directly reflect observations. This data is primarily useful for research purposes or professional consulting.

A detailed description of the localized Climate CH2025 datasets is available on the MeteoSwiss Website: Climate CH2025 datasets

Data download

The Open Data from MeteoSwiss may be used without restriction; the source must be cited when reproducing or redistributing ("Source: MeteoSwiss & ETH Zurich (2025): Climate CH2025 - Daily Datasets. Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, https://doi.org/10.18751/climate/scenarios/ch2025/data/1.0/").

✅ By using 'Open Data' from MeteoSchweiz, you confirm that you have taken note of the Terms of use.

Download options

Manual download via STAC Browser

Users who prefer to use a web interface to browse and download individual files can use the STAC Browser for DAILY-LOCAL and DAILY-GRIDDED.

Download using bash

The script download_ch2025_interactive.sh can be used to download Climate CH2025 files via the STAC API.

Prerequisites: bash with tools curl, jq and wget installed. The script was tested on Ubuntu Linux.

Usage:

• Download the file to the folder where you to want to store the data.
• Run the bash script in a terminal. The console will ask you to choose between DAILY-LOCAL and DAILY-GRIDDED datasets. Afterwards you can set further specifications for DAILY-LOCAL (stations, parameters, GWLs, file format) or DAILY-GRIDDED (parameters, GWLs) and finally choose to download the desired data.

Example download session:

$ bash download_ch2025_interactive.sh 
Do you want to download DAILY-LOCAL or DAILY-GRIDDED? (local/gridded): local
Enter station code (e.g. ABO, ZER or all): abo
Enter parameter (pr, tas, tasmin, tasmax, rsds, hurs, sfcwind or all): tasmin
Enter GWL (ref91-20, GWL1.5, GWL2.0, GWL2.5, GWL3.0 or all): ref91-20
Enter format (.csv or .zip): .csv
Querying STAC API for collection: ch.meteoschweiz.ogd-climate-scenarios-ch2025
✅ Found 1 matching files:
https://rgw.cscs.ch/mchogd:cscs.meteoswiss.ogd.climate/ogd-climate-scenarios-ch2025/abo/ogd-climate-scenarios-ch2025_abo_tasmin_ref91-20.csv
Please wait: Calculating total size...
⚠️  Careful: 1 files will be downloaded. Estimated total size: 1.29 MB.
Continue? (y/n): y
Enter path to save data (default: ogd-climate-scenarios-ch2025/abo): 
Downloading files...
Downloading: https://rgw.cscs.ch/mchogd:cscs.meteoswiss.ogd.climate/ogd-climate-scenarios-ch2025/abo/ogd-climate-scenarios-ch2025_abo_tasmin_ref91-20.csv
✅ Download successful: Files saved in ogd-climate-scenarios-ch2025/abo

Download using R

The R package rstac implements some functionality to query a STAC API. However, it does not currently support pagination well. For this reason, we do not provide an R script here.

More information about the STAC specification and tutorials for R can be found on stacspec.org.

Download using Python

The download_ch2025_data.py script shows how one could use the Python language with the pystac and pystac_client packages to query the STAC API and download files.

More information about the STAC specification and python tutorials can be found on stacspec.org.

Data structure and format

Here is a short overview of the datasets:

Attributes	DAILY-LOCAL	DAILY-GRIDDED
Number of Parameters	7	4
Formats	CSV, NetCDF (in ZIPs)	NetCDF
Data Volume per file	CSV: ~1.5 MB NetCDF: ~200KB	~1-2 GB

Detailed information on the available simulations and variables, limitations and a list of available Swiss stations can be found in the user documentation of the localized Climate CH2025 datasets:

• User documentation pdf on the MeteoSwiss website
• Climate CH2025 datasets on the MeteoSwiss Website

Metadata

DAILY-LOCAL Parameters

ogd-climate-scenarios-ch2025_meta_parameters.csv provides a list of all parameter identifiers with description, parameter group and unit of measurement.

DAILY-LOCAL Stations

All stations have a three-letter identifier (e.g. BER for "Bern/Zollikofen" or LUG for "Lugano").

ogd-climate-scenarios-ch2025_meta_stations.csv provides a list of all station identifiers with full station name, altitude and coordinates.

DAILY-GRIDDED Parameters

ogd-climate-scenarios-ch2025-grid_meta_parameters.csv provides a list of all parameter identifiers with description, parameter group and unit of measurement.

Contact and staying up to date

Please use our contact form for questions: https://www.meteoswiss.admin.ch/about-us/contact/contact-form.html

To receive updates on the datasets and complementary products, please sign up for the "MeteoSwiss Climate Newsletter":

• in German,
• in French or
• in Italian.