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MeteoSwiss - Open Data > Understanding MeteoSwiss' Open Data products > E. Forecast Data

E. Forecast Data

Forecasting systems calculate future atmospheric conditions on the basis of measurement data and observations. MeteoSwiss uses these weather models to create weather forecasts and to enable it to issue weather warnings in the event of imminent hazards.

The following forecast data are available:

  1. Short-term forecast data 🟡 documentation upcoming
  2. Numerical weather forecasting model 🟡 documentation upcoming
  3. Local forecast data 🟡 documentation upcoming

1. Short-term forecast data

Nowcasting involves high spatial and temporal resolution forecasts of weather developments for the next few minutes and up to a maximum of six hours ahead. MeteoSwiss uses these short-term forecasts to, among other things, predict thunderstorms, hail and heavy rainfall.

As MeteoSwiss is planning to replace the current 'INCA' nowcasting software, the following datasets are available from the start of our open data provision:

  • Precipitation (10min values): quantitative chain (based on CombiPrecip, RR)
  • Wind, wind gust and wind direction (10min values)
  • Relative sunshine duration (10min values)
  • Total cloudiness (10min values)

The following datsets will be provided next:

  • Snowfall (10min values): quantitative chain (based on CombiPrecip, RS)
  • ...
  • ...

1.1. Data granularity, update frequency, format and volume

Data granularity is every 10min. Update frequency for the period 0h- +6h is specified per dataset in the table below.

Data format is NetCDF.

Dataset Update frequency Example data file Productive version file name Estimated volume per file (MB)
Precipitation (10min values): quantitative chain (based on CombiPrecip, RR) every 10min RR_INCA_202106280700.nc ogd-nowcasting_RR-INCA_(date and time code).nc 1.7
Wind, wind gust and wind direction (10min values) every 10min ... ogd-nowcasting_(product name)_(date and time code).nc ...
Relative sunshine duration (10min values) 10min SU_INCA_202106280700.nc ogd-nowcasting_SU-INCA_(date and time code).nc 6.4
Total cloudiness (10min values) 10min SU_INCA_202106280700.nc ogd-nowcasting_SU-INCA_(date and time code).nc 6.4
Snowfall (10min values): quantitative chain (based on CombiPrecip, RS) every 10min RS_INCA_202106280700.nc ogd-nowcasting_RS-INCA_(date and time code).nc 0.4

1.2. Parameter metadata

Parameter metadata is part of each NetCDF-File. See example data files in the table above.

1.3. Coordinate system

The coordinate system is Swiss LV95 EPSG:2056.

1.4. Data visualisation

See e.g. MeteoSwiss' ....


2. Numerical weather forecasting model

MeteoSwiss uses two models, ICON-CH1-EPS and ICON-CH2-EPS, to forecast atmospheric changes in Switzerland and its surroundings over a longer period than nowcasting, providing predictions for up to five days. Both models include ensemble data assimilation.

2.1 Model Specification

Attributes ICON-CH1-EPS ICON-CH2-EPS
Collection Name ogd-forecasting-icon-ch1 ogd-forecasting-icon-ch2
Horizontal Grid Size 1 km 2.1 km
Ensemble Members 11 21
Forecast Period 33 h 120 h
Grid Native icosahedral Native icosahedral
Temporal Resolution 1 h 1 h
Model Run Interval every 3 h every 6 h
Format GRIB edition 2 GRIB edition 2

2.2 Available Parameters

Users can find information about available parameters, including metadata, by referring to the list of variables.

2.3 Accessing Forecast Data

The user can access the forecast model output data of the last 24 hours. Data that is older than 24 hours is no longer available. To see what data is accessible, the user can search in Catalog 1 for data on ICON-CH1-EPS and in Catalog 2 for ICON-CH2-EPS.

2.4 Additional Data Information

2.4.1 Parameter metadata

The parameter metadata is part of each GRIB file.

2.4.2 Coordinate system

The ICON-CH1-EPS and ICON-CH2-EPS model uses a native icosahedral grid inherited by the original ICON model grid. In order to regrid to another grid we provide regridding operators.

2.4.3 Data visualisation

See jupyter-notebook examples.


3. Local forecast data

...

...

Data granularity, update frequency, format and volume

There are files of data granularity ..., ..., ..., ... and update frequency hourly (now), daily (recent) or yearly (historical) for each station.

Data format is CSV with an estimated volume of ... MB per file.

See example data files: ....

Parameter metadata

See example parameter metadata files of data granularity: ... and ....

Station metadata

See example station metadata file.

Data visualisation

See e.g. MeteoSwiss' ....