AEMET service
AEMET is the Spanish
national meteorologic service, and is the national meteorology authority
providing quality data for public and research use, as well as
prediction products and disaster warning system. meteospain
only access to the automatic meteorological stations network data.
AEMET options
Temporal resolution
meteospain offers access to the AEMET API at different
temporal resolutions:
- “current_day”, returning the latest 24 hours of measures for all or selected stations.
- “daily”, returning the daily aggregated measures for all or selected stations.
- “monthly”, returning the monthly aggregated measures for only one station.
- “yearly”, returning the yearly aggregated measures for only one station.
In “daily”, a start_date (and optionally an
end_date) arguments must be provided, indicating the period
from which retrieve the data.
In “monthly” and “yearly”, only the years in start_date and
end_date are used, returning all year monthly or yearly
values (i.e start_date = as.Date("2020-12-01") is
the same as start_date = as.Date("2020-01-01") as both will
return all 2020 measures).
Stations
meteospain access the data in the AEMET API collecting
all stations. If a character vector of stations codes is supplied in the
stations argument, a filter step is done before returning
the data to maintain only the stations supplied.
The exception for this are “monthly” and “yearly” temporal resolutions. AEMET API only allows for one station to be retrieved.
AEMET API Key
AEMET API only allow access to the data with a personal API Key. This
token must be included in the api_key argument of
aemet_options function.
To obtain the API Key, please visit https://opendata.aemet.es/centrodedescargas/inicio and
follow the instructions at “Obtencion de API Key”.
It is not advisable to use the keys directly in any script shared or publicly available (github…), neither store them in plain text files. One option is using the keyring package for managing and accessing keys:
Examples
# current day, all stations
api_options <- aemet_options(
resolution = 'current_day',
api_key = key_get('aemet')
)
api_options#> $resolution
#> [1] "current_day"
#>
#> $start_date
#> [1] "2023-12-19"
#>
#> $end_date
#> [1] "2023-12-19"
#>
#> $stations
#> NULL
#>
#> $api_key
#> [1] "my_api_key"# daily, all stations
api_options <- aemet_options(
resolution = 'daily',
start_date = as.Date('2020-04-25'), end_date = as.Date('2020-05-25'),
api_key = key_get('aemet')
)
api_options#> $resolution
#> [1] "daily"
#>
#> $start_date
#> [1] "2020-04-25"
#>
#> $end_date
#> [1] "2020-05-25"
#>
#> $stations
#> NULL
#>
#> $api_key
#> [1] "my_api_key"# monthly, only one station because AEMET API limitations
api_options <- aemet_options(
resolution = 'monthly',
start_date = as.Date('2020-04-25'), end_date = as.Date('2020-05-25'),
station = "0149X",
api_key = key_get('aemet')
)
api_options#> $resolution
#> [1] "monthly"
#>
#> $start_date
#> [1] "2020-01-01"
#>
#> $end_date
#> [1] "2020-12-31"
#>
#> $stations
#> [1] "0149X"
#>
#> $api_key
#> [1] "my_api_key"AEMET stations info
Accessing station metadata for AEMET is simple:
get_stations_info_from('aemet', api_options)
#> Simple feature collection with 291 features and 5 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -17.91528 ymin: 27.73583 xmax: 4.215556 ymax: 43.78611
#> Geodetic CRS: WGS 84
#> # A tibble: 291 × 6
#> service station_id station_name station_province altitude
#> * <chr> <chr> <chr> <chr> [m]
#> 1 aemet 0252D ARENYS DE MAR BARCELONA 74
#> 2 aemet 0076 BARCELONA AEROPUERTO BARCELONA 4
#> 3 aemet 0200E BARCELONA, FABRA BARCELONA 408
#> 4 aemet 0201D BARCELONA BARCELONA 6
#> 5 aemet 0149X MANRESA BARCELONA 291
#> 6 aemet 0229I SABADELL AEROPUERTO BARCELONA 146
#> 7 aemet 0255B SANTA SUSANNA BARCELONA 40
#> 8 aemet 0367 GIRONA AEROPUERTO GIRONA 143
#> 9 aemet 0370B GIRONA, ANTIC INSTITUT GIRONA 95
#> 10 aemet 0372C PORQUERES GIRONA 157
#> # ℹ 281 more rows
#> # ℹ 1 more variable: geometry <POINT [°]>AEMET data
api_options <- aemet_options(
resolution = 'daily',
start_date = as.Date('2020-04-25'),
api_key = key_get('aemet')
)
spain_20200425 <- get_meteo_from('aemet', options = api_options)
#> ℹ © AEMET. Autorizado el uso de la información y su reproducción citando a
#> AEMET como autora de la misma.
#> https://www.aemet.es/es/nota_legal
spain_20200425
#> Simple feature collection with 237 features and 12 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -17.91528 ymin: 27.81639 xmax: 4.215556 ymax: 43.78611
#> Geodetic CRS: WGS 84
#> # A tibble: 237 × 13
#> timestamp service station_id station_name station_province altitude
#> <dttm> <chr> <chr> <chr> <chr> [m]
#> 1 2020-04-25 00:00:00 aemet 0016A REUS AEROPU… TARRAGONA 71
#> 2 2020-04-25 00:00:00 aemet 0076 BARCELONA A… BARCELONA 4
#> 3 2020-04-25 00:00:00 aemet 0149X MANRESA BARCELONA 291
#> 4 2020-04-25 00:00:00 aemet 0200E BARCELONA, … BARCELONA 408
#> 5 2020-04-25 00:00:00 aemet 0201D BARCELONA BARCELONA 6
#> 6 2020-04-25 00:00:00 aemet 0252D ARENYS DE M… BARCELONA 74
#> 7 2020-04-25 00:00:00 aemet 0255B SANTA SUSAN… BARCELONA 40
#> 8 2020-04-25 00:00:00 aemet 0324A RIPOLL GIRONA 675
#> 9 2020-04-25 00:00:00 aemet 0367 GIRONA AERO… GIRONA 143
#> 10 2020-04-25 00:00:00 aemet 0372C PORQUERES GIRONA 157
#> # ℹ 227 more rows
#> # ℹ 7 more variables: mean_temperature [°C], min_temperature [°C],
#> # max_temperature [°C], precipitation [L/m^2], mean_wind_speed [m/s],
#> # insolation [h], geometry <POINT [°]>Visually:
spain_20200425 |>
units::drop_units() |>
ggplot() +
geom_sf(aes(colour = mean_temperature)) +
scale_colour_viridis_c()
spain_20200425 |>
ggplot() +
geom_histogram(aes(x = precipitation))
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> Warning: Removed 17 rows containing non-finite values (`stat_bin()`).