Welcome to sondera’s documentation!
Documentation is under construction. Please refer to the API reference.
Contents:
Indices and tables
Readme
sondera
Overview
sondera is a python package providing clients for accessing Swedish hydrology and meteorology related open data and observations.
Download stream discharge, groundwater levels, climate and weather observations and more from stations across Sweden. Data sources currently include Swedish Meteorological and Hydrological Institute (SMHI) open data API and Swedish Geological Survey (SGU) groundwater API.
Consider the API unstable, it may change at short or no notice.
Data sources and licenses
It is the end users responsibility to adhere to the license of each respective data provider. See the links to the licenses below.
The following clients are currently implemented or under implementation:
Observations
SMHI Open Data Meteorological Observations (license, host link)
SMHI Open Data Hydrological Observations (license, host link)
Model products
Parameters available
Hydrometric parameters
Stream discharge
Groundwater level
Weather and climate parameters
More than 40 parameters, including
Precipitation
Air temperature
Wind speed
Solar radiation (station data via MetObs, distributed data via Strång)
Requirements and installation
Requirements:
numpy
pandas
geopandas
requests
tqdm
Install from pypi using pip
pip install sondera
General description and example usage
Observational data which is linked to a station is returned as a DataSeries object, which contains metadata information in addition to the observed data series.
Modelling products are returned as the data series only, which is either a pandas Series or DataFrame, or xarray for multi-dimensional data.
# Example getting hourly air temperature for the latest months from
# SMHI station Stockholm-Observatoriekullen A (number 98230)
from sondera.clients.smhi import MetObsClient, ParametersMetObs
client = MetObsClient()
# For the parameter we can pass either the ParametersMetObs enum
# or simply the SMHI integer id (which is 1 for hourly air temperature)
air_temp = client.get_observations(parameter=ParametersMetObs.TemperatureAirHour,
station=98230,
period='latest-months')
# observations are stored under "data" attribute as a pandas.Series
air_temp.data.head(5)
timestamp
2021-12-31 01:00:00 4.9
2021-12-31 02:00:00 4.2
2021-12-31 03:00:00 3.5
2021-12-31 04:00:00 3.1
2021-12-31 05:00:00 3.0
Name: TemperatureAirHour, dtype: float64
# additional data, such as quality tags are stored under "aux_data"
air_temp.aux_data.head(5)
quality
timestamp
2021-12-31 01:00:00 G
2021-12-31 02:00:00 G
2021-12-31 03:00:00 G
2021-12-31 04:00:00 G
2021-12-31 05:00:00 G
# information on the station is also available, such as name, id, coordinates,
# and history
air_temp.station
Station(name='Stockholm-Observatoriekullen A', id=98230, agency='SMHI',
position=Coordinate(y=59.341681, x=18.054928, z=43.133, epsg_xy=4326, epsg_z=5613),
station_type=<StationType.MetStation: 2>, active_station=True,
active_period=[Timestamp('1996-10-01 00:00:00'), Timestamp('2022-05-10 07:00:00')],
last_updated=Timestamp('2022-05-10 07:00:00'), station_info={},
position_history=[{'from': Timestamp('1996-10-01 00:00:00'),
'to': Timestamp('2022-05-10 07:00:00'),
'position': Coordinate(y=59.341681, x=18.054928, z=43.133,
epsg_xy=4326, epsg_z=5613)}])
Feedback and issues
Please report issues here: https://github.com/rhkarls/sondera/issues
General feedback is most welcome, please post that as well under issues.