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sondera

pypi_shield pypi_license tests_workflow Documentation Status

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

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.