Meteoswiss Data Download

Teaching staff, students and people working in teaching and research can access data on IDAweb free of charge. A university or college email address must be used when registering. Pupils and apprentices are not permitted to register themselves, but they can obtain data through their tutors. In cases of doubt, MeteoSwiss may check the status of an applicant with their institution.

Systematic meteorological measurements have been conducted in all parts of Switzerland since the middle of the 19th century. For more than 100 years, observers manually recorded the measured results in tables and sent them to MeteoSwiss by mail. Moreover, measuring strips from old recording measuring devices are available, on which the measured results are illustrated as graphs on paper. The digitalisation of these large amounts of analogue original observations involves the scanning of the data entry logs and the measuring strips, respectively and/or the actual digitalisation of the measured values, in order to make them available for computer-aided analyses.

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The most important measured parameters (temperature, precipitation, sunshine hours) of the Swiss National Basic Climatological Network (Swiss NBCN) were entered into the central Data Warehouse database of MeteoSwiss (link for the DWH page). All activities in connection with this digitalisation are documented in a technical report from MeteoSwiss:

The most important measured parameters (temperature, precipitation, sunshine hours) of the Swiss National Basic Climatological Network (Swiss NBCN) were entered into the central Data Warehouse database of MeteoSwiss (link for the DWH page). All activities in connection with this digitalisation are documented in a technical report from MeteoSwiss:

MeteoSwiss is still in the possession of its own archive. These days, it mainly contains information about the history of the measurements. For the interpretation of series of measurements and results of data analyses, it is important to know the measuring conditions at the respective point in time. After all, changes in the measuring conditions such as equipment changes, location changes or observer changes may have affected the measurements. A well-documented history of the station is an important prerequisite for the homogenization of lengthy series of measurements (link to the homogenisation page).

NEWS 20.12.2022 IMPORTANT: All datasets RhiresD, Tmin/Tmax/TabsD, SrelD (daily, monthly, annual) have been reprocessed by Meteoswiss on a 1x1km grid and are now provided only in the Swiss coordnate system CH1903+ LV95 on our site up until 2021. We will not update the old datasets anymore, but will keep them in the collection in folders marked "OLD" for now.

NEWS 19.10.2022: The RhiresD, Tmin/Tmax/TabsD, SrelD daily datasets for 2021 are now packed into the appropriate annual file. Please note that Meteoswiss changed the domain size and also the name of the file (now swiss.lv95 instread of swisscorr).

NEWS 13.1.2022: The RhiresD, Tmin/Tmax/TabsD, SrelD datasets are now updated on a continuous monthly basis (with a 1 month delay). Important: Please note that from 2020 on the datasets are coming from automated delivery and some of them have a flipped coordinate (Y coordinate) compared to the bulk delivery datasets prior to 2020. It is advsiable to always check that the downloaded datasets pre and post 2020 are correctly oriented in the Y axis. If not, flip to correct them. Other updates to the automatic delivery are explained external pageherecall_made.

NEWS 3.12.2018: The revised datasets are now available in the Swiss coordinate system (ch01, 1x1 km grid) and the latitude-longitude system (ch02, app 2x2 km grid). Daily, monthly and annual data are available.

Peter Molnar presented the use of the gridded data products in a Workshop at MeteoSwiss on 26.10.2018 "DownloadApplications of spatial climate datasets in hydrology (PDF, 2.2 MB)vertical_align_bottom"

MeteoSwiss provides selected gridded products to ETH researchers under a general license. We are serving as a central location for the distribution of this data within ETH. Data requests are eligible only from ETH faculty, postdocs and PhD students. For MSc student research it is the supervisor of the thesis who has to request the data. We appreciate any comments and suggestions on improving the data delivery.

Basics: These are daily gridded products for Switzerland developed from a combination of station data and interpolation techniques. For more details read the MeteoSwiss data documentation overview below. General terms and conditions for using the data specify also the correct citation of source. The MeteoSwiss Gridded Datasets webpage provides all additional information for each dataset. Data are provided at the daily resolution, but also aggregated monthly and annual sums.

Resolution: As of 2022 data are provided ony in the Swiss coordinate system CH1903+ LV95 on a 1x1 km grid. The filename contains "swiss.lv95". The original temporal resolution is daily. The monthly and annual sums/averages are inteprolated.

Format: The data format is NetCDF, with a separate file for every variable and year. We provide examples of Matlab and Python code to read this format and extract the data for regions, time periods, etc. If you develop your own routines we would appreciate if you share them with other users through our page. For viewing the original NetCDF we recommend the freeware Panoply from NASA (external page _made).

As the national weather service, MeteoSwiss is entrusted with the recording, storage and management of wide-ranging meteorological and climatological data. Ground-based stations, weather radars and numerous other sources provide millions of measurement values in various formats each and every day. In order to manage this wealth of data, MeteoSwiss operates a data warehouse system. This includes a central database known as the data warehouse (DWH). The system also has a central metadata repository which contains all information on the description of the actual measured values and the management of the respective processes. The system also provides the tools for the preparation and processing (aggregation, quality assurance and amendment) of meteorological and climatological data as well as various other applications.

I wonder whether an access key is required to get data from meteoswiss. I am running HA 2023.7.2 which has been set up in a virtual python 3.11 environment. Any hint what I would need to change to get Meteo Swiss data retrieval running in this environment would be very much appreciated.

To cope with the exponential growth in volumes of meteorological data and changing requirements in the coming years, ELCA will work closely with MeteoSwiss to update and expand their current data management solution topology. The aim is to switch to a horizontally scalable architecture, able to manage data with hybrid systems using on-premise solutions and microservices in a public cloud.

The project will give us an exciting opportunity to leverage our know-how and experience in data & analytics, providing MeteoSwiss with capabilities to expand and modernize their IT systems. Additionally, this collaboration will help enhance their operations, deliver better services to the public, and keep them ahead of the curve in the rapidly evolving field of weather forecasting.

The effects of solar ultraviolet (UV) radiation on life on Earth differ greatly. While overexposure to UV rays is harmful, small amounts of exposure are necessary for the synthesis of Vitamin D and good health. To optimize individual exposure to solar UV, it is therefore crucial to use UV data sources representative for entire populations and realistically accounting for various influencing factors. A UV climatology for Switzerland based on satellite data has been developed to provide risk estimates at population level. An algorithm generating ground-based radiation estimate has been transformed from the visible to the UV wavelength domain by adapting both a clear-sky radiation transfer model and a cloud modification factor model using satellite imagery. The algorithm allows the computation of global UV erythemal irradiance at a spatial resolution of 1.5 - 2 km and an hourly temporal resolution over fifteen years. A validation, conducted with measurements from three meteorological stations over ten years, showed that the expanded uncertainty for low hourly UVI values (UVI < 3) is about 0.3, while for high hourly UVI values (UVI > 6) it can go up to 1.5. In clear-sky situation, the uncertainty is in the range of 10-15%. The climatology developed allows to visualise potential UV exposure at regional and national scale. National prevention intervention could use new strategies to better focus on populations at risk and better tailor available researches. The UV climatology allows a high versatility in adapting the data extraction to the goal of studies using it. Further tailored data extraction and analysis will be necessary to exploit this climatology in a wide range of environmental and occupational health applications. Its development was focused on Switzerland, but the techniques used can be extended globally. 2351a5e196