Meteocat

Meteocat is the Catalan Meteorological Service. It provides a REST API to access its data. To use the Meteocat API, you first need to have an API key. You can get one by registering at apidocs.meteocat.gencat.cat/section/informacio-general/plans-i-registre. You can choose the “Accés ciutadà i administració” plan, which is free, or the paid “Accés professionals” plan. In both cases, you need to check the box “Dades de la XEMA” (automated weather stations) to get access to the data used in meteostations-geopy. You will then receive by mail the API key.

Let us now use the MeteocatClient class by instantiating it with the API key and the region of interest (which must be part of Catalonia so that it contains some stations).

from meteostations.clients import MeteocatClient

API_KEY = "<your-api-key>"
region = "Conca de Barberà"

client = MeteocatClient(region, API_KEY)

Once instantiated, the stations_gdf property features the stations within the region, with its locations and other attributes:

client.stations_gdf

	codi	nom	tipus	emplacament	altitud	estats	coordenades.latitud	coordenades.longitud	municipi.codi	municipi.nom	comarca.codi	comarca.nom	provincia.codi	provincia.nom	xarxa.codi	xarxa.nom	geometry
27	CW	l'Espluga de Francolí	A	Urb. Espluga Parc	446.0	[{'codi': 2, 'dataInici': '1996-02-23T21:00Z',...	41.39241	1.09894	430542	L'Espluga de Francolí	16	Conca de Barberà	43	Tarragona	1	XEMA	POINT (1.09894 41.39241)
87	UJ	Santa Coloma de Queralt	A	Partida la Cabana	709.0	[{'codi': 2, 'dataInici': '1996-11-19T20:00Z',...	41.52879	1.36830	431397	Santa Coloma de Queralt	16	Conca de Barberà	43	Tarragona	1	XEMA	POINT (1.36830 41.52879)
142	W8	Blancafort	A	Cooperativa vinícola, pl.del Sindicat	438.0	[{'codi': 2, 'dataInici': '2000-01-18T12:00Z',...	41.44237	1.15998	430290	Blancafort	16	Conca de Barberà	43	Tarragona	1	XEMA	POINT (1.15998 41.44237)

Similarly, the variables_df property features the available variables and its metadata:

client.variables_df.head()

	codi	nom	unitat	acronim	tipus	decimals
0	1	Pressió atmosfèrica màxima	hPa	Px	DAT	1
1	2	Pressió atmosfèrica mínima	hPa	Pn	DAT	1
2	3	Humitat relativa màxima	%	HRx	DAT	0
3	4	Temperatura màxima de subsòl a 5 cm	°C	TSUBx5	DAT	1
4	5	Temperatura mínima de subsòl a 5 cm	°C	TSUBn5	DAT	1

Given a variable and a time range, the time seres data frame of measurements in the corresponding stations can be obtained with the get_ts_df method as in:

variable = "temperature"
start_date = "2021-08-13"
end_date = "2021-08-16"

ts_df = client.get_ts_df(variable, start_date, end_date)
ts_df

codi	CW	UJ	W8
time
2021-08-13 00:00:00+00:00	20.2	21.6	20.2
2021-08-13 00:30:00+00:00	19.8	20.5	19.6
2021-08-13 01:00:00+00:00	19.5	21.2	19.3
2021-08-13 01:30:00+00:00	20.1	22.0	19.2
2021-08-13 02:00:00+00:00	19.2	21.7	18.9
...	...	...	...
2021-08-16 21:30:00+00:00	20.6	18.8	20.6
2021-08-16 22:00:00+00:00	19.7	18.7	19.5
2021-08-16 22:30:00+00:00	19.3	17.8	19.3
2021-08-16 23:00:00+00:00	18.8	16.9	18.7
2021-08-16 23:30:00+00:00	18.2	16.2	18.1

192 rows × 3 columns

The variable argument can be either: - a meteocat variable code (integer or string) or variable name (string) - see the “CODI_VARIABLE” and “NOM_VARIABLE” columns in “Metadades variables meteorològiques” - or an essential climate variable (ECV) following the meteostations-geopy nomenclature (string).

The returned object is a pandas data frame upon which we can operate using any of its supported functions, e.g.:

ts_df.resample("H").mean().plot()

<Axes: xlabel='time'>

TODO: We can also use the get_ts_gdf method to include the locations of the stations along with the time series of measurements as in:

# TODO: ts_gdf = client.get_ts_gdf(variable, start_date, end_date)