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MeteoSwiss - Open Data > Understanding MeteoSwiss' Open Data products > A - Ground-based Measurements

A - Ground-based Measurements

MeteoSwiss operates a network of land-based weather stations where current weather and climate data are automatically recorded. It covers all parts of the country and all altitude levels.

Note

For climate analyses, use the corresponding homogeneous time series data instead.

The following measurements (1-3; 5-7) and additional observations - manual recording of cloud cover (8) and vegetation development (9) - are available:


General information

All MeteoSwiss surface stations have a name and an identfier consisting of three letters (e.g. BER for Bern / Zollikofen or LUG for Lugano). Data files use this station identifier (in lower case) in the file name throughout all directories. A list of all station identfiers with station names, coordinates, height etc. can be found in the according 'station metadata' sections below.

Note

If you require hourly, daily, monthly or annual values, we strongly recommend that you download the corresponding aggregated data granularity. Various update frequencies (every 10 minutes to once a year) are available.


A1 - Automatic weather stations - Measured values

Around 160 stations of the automatic measurement network SwissMetNet comprise a complete measurement programme. They deliver temperature, humidity, precipitation, wind, radiation, pressure and sunshine duration every ten minutes.

The network is supplemented by around 100 automatic precipitation stations. Together, these stations form the basis for the creation of reliable local weather forecasts as well as severe weather and flood warnings. Additionally MeteoSwiss operates 3 automatic tower stations at 150m to 230m above ground for boundary layer measurements.

Note

For climate analyses, use the corresponding homogeneous time series data instead.

1.1. Data granularity, update frequency, format and volume

If you require hourly, daily, monthly or annual values, we strongly recommend that you download the corresponding aggregated data granularity t, h, d, m, y and update frequency hourly (now), daily (recent) or yearly (historical) for each station.

Time series can begin before the introduction of automatic measurements in the year 1981. Before 1981 at least three values per day were manually measured. They are stored as individual 10-minute values (synoptic observations).

Data format of all files is CSV with an estimated volume of ≤5.3 MB per file.

See example data files for station Salen-Reutenen (HAI) (abbreviation set in lower case) for all granularities and update frequencies mentioned: ogd-smn_hai_(data granularity)_(update frequency).csv.

Note

In addition we offer the current measured values of the main parameters of all stations (URL to follow) in a single data file, i.e. data granularity t. The main parameters included are: ...

1.2. Parameter metadata

See example parameter metadata files of data granularity: t, h, d, m and y.

The productive version will provide a single parameter metadata file for all granularities; file name: ogd-smn_meta_parameters.csv.

sremaxyv 1 % 471 Sonnenscheindauer; Verhältnis der Jahressumme zur maximal Möglichen sremaxmv 1 % 349 Sonnenscheindauer; Verhältnis der Monatssumme zur maximal Möglichen sremaxdv 1 % 222 Sonnenscheindauer; relativ zur absolut möglichen Tagessumme

1.3. Station metadata

See example station metadata file.

The productive version will provide a station metadata file with the file name: ogd-smn_meta_stations.csv.

1.4. Data visualisation

See e.g. MeteoSwiss' SwissMetNet network map.


A2 - Automatic precipitation stations - Measured values

As a meteorological parameter, precipitation exhibits a very high spatial variability and therefore requires a denser measurement network. In supplement to 1. Automatic weather stations MeteoSwiss thus operates about 100 additional stations for the automatic measurement of precipitation.

Note

For climate analyses, use the corresponding homogeneous time series data instead.

2.1. Data granularity, update frequency, format and volume

If you require hourly, daily, monthly or annual values, we strongly recommend that you download the corresponding aggregated data granularity t, h, d, m, y and update frequency hourly (now), daily (recent) or yearly (historical).

Time series can begin before the introduction of automatic measurements in the year 1981. Before 1981 at least three values per day were manually measured. They are stored as individual 10-minute values (synoptic observations).

Data format is CSV with an estimated volume of ≤5.3 MB per file.

See example data files for station AIR (set in lower case) for all granularities and update frequencies mentioned: ogd-smn-precip_air_(data granularity)_(update frequency).csv.

2.2. Parameter metadata

For example parameter metadata files see 1.2. Parameter metadata above.

The productive version will provide a single parameter metadata file for all granularities; file name: ogd-smn-precip_meta_parameters.csv.

2.3. Station metadata

See example station metadata file.

The productive version will provide a station metadata file with the file name: ogd-smn-precip_meta_stations.csv.

2.4. Data visualisation

See e.g. MeteoSwiss' SwissMetNet network map.


A3 - Automatic tower stations - Measured values

For boundary layer measurements MeteoSwis operates 3 automatic tower stations at 150m to 230m above ground. They deliver temperature, humidity, wind, radiation, pressure and sunshine duration every ten minutes.

3.1. Data granularity, update frequency, format and volume

If you require hourly, daily, monthly or annual values, we strongly recommend that you download the corresponding aggregated data granularity t, h, d, m, y and update frequency hourly (now), daily (recent) or yearly (historical),

Data format is CSV with an estimated volume of ≤5.3 MB per file.

See example data files for station UEB (set in lower case) for all granularities and update frequencies mentioned: ogd-smn-tower_ueb_(data granularity)_(update frequency).csv.

3.2. Parameter metadata

For example parameter metadata files see 1.2. Parameter metadata above.

The productive version will provide a single parameter metadata file for all granularities; file name: ogd-smn-tower_meta_parameters.csv.

3.3. Station metadata

See example station metadata file.

The productive version will provide a station metadata file with the file name: ogd-smn-tower_meta_stations.csv.

3.4. Data visualisation

See ... .


A4 - Automatic soil stations - Measured values

(not yet realised)


A5 - Manual precipitation stations - Measured values

In addition to its automatic precipitation measurements (see 1. Automatic weather stations, 2. Automatic precipitation stations and 3. Automatic tower stations above), MeteoSwiss operates a manual precipitation monitoring network.

Measurements are taken once a day and transmitted to MeteoSwiss via SMS. The network comprises around 240 locations, about 190 stations measure rainfall and snow, and about 50 stations measure snow only. Due to their long-series measurements, they are of great climatological significance.

Note

For climate analyses, use the corresponding homogeneous time series data instead.

In mountainous areas that are difficult to access, the network is supplemented by around 60 totalisers which record the volume of precipitation for an entire year (see 5. Totaliser precipitation stations).

5.1. Data granularity, update frequency, format and volume

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

Data format of all files is CSV with an estimated volume of ≤0.6 MB per file.

See example data files for station PON (set in lower case) for all granularities and update frequencies mentioned: ogd-nime_pon_(data granularity)_(update frequency).csv.

5.2. Parameter metadata

See example parameter metadata files of data granularity: d, m and y.

The productive version will provide a single parameter metadata file for all granularities; file name: ogd-nime_meta_parameters.csv.

5.3. Station metadata

See example station metadata file.

The productive version will provide a station metadata file with the file name: ogd-nime_meta_stations.csv.

5.4. Data visualisation

See e.g. MeteoSwiss' SwissMetNet network map.


A6 - Totaliser precipitation stations - Measured values

In supplement to 5. Manual precipitation stations – Measured values in mountainous areas that are difficult to access, MeteoSwiss operates around 60 totalisers which record the volume of precipitation for an entire year (see section "Totaliser monitoring network – annual readings" here.

Note

For climate analyses, use the corresponding homogeneous time series data instead.

6.1. Data granularity, update frequency, format and volume

There are files of data granularity y and update frequency yearly (historical) for each station.

Data format of all files is CSV with an estimated volume of ≤0.6 MB per file.

See example data file for station MGR (set in lower case): ogd-tot_mgr_y_historical.

6.2. Parameter metadata

See example parameter metadata file of data granularity: y.

The productive version will provide a parameter metadata file with the name: ogd-tot_meta_parameters.csv.

6.3. Station metadata

See example station metadata file.

The productive version will provide a station metadata file with the file name: ogd-tot_meta_stations.csv.

6.4. Data visualisation

See e.g. MeteoSwiss' SwissMetNet network map.


A7 - Pollen stations - Measured values

MeteoSwiss operates the national pollen monitoring network. It consists of around 15 monitoring stations which cover Switzerland's most important climatic and vegetation regions. The measurements obtained provide invaluable information for those who suffer from allergies.

Additionally since 2023 the new automatic pollen network is operational: for the first time in the world, instead of daily averages being available after a week, airborne pollen concentrations (No/m³, number of grains per cubic metre of air) of Birch, Beech, Oak, Alder, Ash, Grasses and Hazel are available in real time at an hourly resolution.

7.1. Data granularity, update frequency, format and volume

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

Note

The granularities h and d contain average pollen concentrations, while the granularities m and y contain pollen integrals.

Data format is CSV with an estimated volume of 0.6 MB per file.

See example data files for station PBS (set in lower case) for granularities h and d and update frequencies recent and historical: ogd-pollen_pbs_(data granularity)_(update frequency).csv.

7.2. Parameter metadata

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

7.3. Station metadata

See example station metadata file.

7.4. Data visualisation

See e.g. MeteoSwiss' POLLEN network map.


A8 - Meteorological visual observations

MeteoSwiss' data on current weather events is supplemented by visual human observations, which describe the atmospheric conditions around the observation sites in detail.

Meteorological observers make visual observations and take readings from measurement instruments between two and eight times per day every day of the year at around 20 locations in Switzerland. The following aspects are observed:

  • Meteorological visibility
  • Current weather: e.g. moderate rain showers, snowfall, fog with formation of hoarfrost
  • Past weather: the main weather phenomena during the past 3, 6 or 12 hours, e.g. thunderstorms, drizzle, drifting snow
  • Ground conditions: e.g. powder snow covering the entire ground surface; frozen; damp
  • Clouds: extent of total cloud cover, type and shape of visible clouds, the altitude of the cloud base
  • Mesurement of fresh and total snow depth

8.1. Data granularity, update frequency, format and volume

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

Data format is CSV with an estimated volume of ≤0.04 MB per file.

See example data files for station BAS (set in lower case) for granularity t and update frequencies now, recent and historical: ogd-obs_bas_t_(update frequency).csv.

8.2. Parameter metadata

See example parameter metadata file of data granularity: t.

8.3. Station metadata

See example station metadata file.

8.4. Data visualisation

See e.g. MeteoSwiss' OBS network map.


A9 - Phenological observations

The Swiss Phenology Network consists of around 160 stations. Some 26 different plant species are observed in order to describe the vegetation development. On the basis of this information, it is possible to investigate the impact of climate change on the vegetation. The observations also serve to generate forecasting models for the start of flowering.

9.1. Data granularity, update frequency, format, volume and structure

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

Data format is CSV with an estimated volume of ≤7.1 MB per file.

Data structure conforms to the example data files for granularity y and update frequencies recent and historical: ogd-phenology_(station identifier)_y_(update frequency).csv.

Variable name Description Datatype Note
param_id Parameter identification Number see Parameter metadata
nat_abbr Station abbreviation Text see Station metadata
reference_year Reference year YYYY
value Date of observation YYYYMMDD
doy Day of year Number negative values: Observation in the year preceding the reference year.
values greater than 365: Observation in the year following the reference year.

9.2. Parameter metadata

The available parameters are listed in the example parameter metadata file of data granularity: y.

Variable name Description Datatype Example value Note
param_id Parameter identification Number 601
param_shortname Parameter shortname Integer maesh13d
scientific name Plant's scientific name + phenophase* in English String Aesculus hippocastanum - leaf unfolding (50%) *phenophase: An observable stage or phase in the annual life cycle of a plant that can be defined by a start and end point.
desc_english Plant's common name + phenophase* in English String Horse chestnut - leaf unfolding (50%)
desc_deutsch Plant's common name + phenophase* in German String Rosskastanie - Blattentfaltung (50%)
desc_italiano Plant's common name + phenophase* in Italian String Ippocastano - spiegamento delle foglie (50%)
desc_français Plant's common name + phenophase* in Italian String Marronnier - déploiement des feuilles (50%)

9.3. Station metadata

The available parameters are listed in the example station metadata file.

Variable name Description Datatype/Unit Example value Note
Station Station name Text St. Gallen
Abbr. Station abbreviation Text STG
WIGOS-ID WIGOS Station identifier (WSI) 4 Block Number 0-20000-0-06681 WSI is used to register an observing station or platform in the OSCAR/Surface database.
Station type Station type Text Phenology station
Data Owner Data Owner Text MeteoSwiss
Station height m a. sea level Station height Meter above sea level 711
CoordinatesE Swiss coordinates system LV95, East Number 2746301
CoordinatesN Swiss coordinates system LV95, North Number 1255286
Latitude Global WGS84 GPS coordinates, Latitude Decimal degrees 47.432103
Longitude Global WGS84 GPS coordinates, Longitude Decimal degrees 9.378022
Exposition to be explained Text plain
Canton Swiss canton abreviation Text SG
Measurements List of observed plants, scientific names Text Aesculus hippocastanum, Fagus sylvatica, Acer pseudoplatanus, Sorbus aucuparia, Corylus avellana, Tilia platyphyllos, Sambucus nigra, Tilia cordata, Larix decidua, Picea abies, Robinia pseudoacacia, Betula pendula, Castanea sativa, Tussilago farfara, Anemone nemorosa, Dactylis glomerata, Taraxacum officinale, Cardamine pratensis, Leucanthemum vulgare, Colchicum autumnale, Prunus avium, Pyrus communis, Malus domestica, Hay
Link More information about the station and the start date of observations (per plant) URL https://www.meteoswiss.admin.ch/services-and-publications/applications/measurement-values-and-measuring-networks.html#param=messnetz-phaenologie&station=STG

9.4. Data visualisation

See e.g. MeteoSwiss' PHENOLOGY network map.


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