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:

install.packages('keyring')
library(keyring)
key_set('aemet') # A prompt asking for the secret (the API Key) will appear.

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] "2025-10-01"
#> 
#> $end_date
#> [1] "2025-10-01"
#> 
#> $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('2020-05-08'),
  api_key = key_get('aemet')
)
api_options

#> $resolution
#> [1] "daily"
#> 
#> $start_date
#> [1] "2020-04-25"
#> 
#> $end_date
#> [1] "2020-05-08"
#> 
#> $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 947 features and 5 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -18.115 ymin: 27.66528 xmax: 4.323889 ymax: 43.78611
#> Geodetic CRS:  WGS 84
#> # A tibble: 947 × 6
#>    service station_id station_name               station_province altitude
#>  * <chr>   <chr>      <chr>                      <chr>                 [m]
#>  1 aemet   B051A      SÓLLER, PUERTO             ILLES BALEARS           5
#>  2 aemet   B087X      BANYALBUFAR                ILLES BALEARS          60
#>  3 aemet   B013X      ESCORCA, LLUC              ILLES BALEARS         490
#>  4 aemet   B103B      ANDRATX - SANT ELM         ILLES BALEARS          52
#>  5 aemet   B158X      CALVIÀ, ES CAPDELLÀ        ILLES BALEARS          50
#>  6 aemet   B275E      SON BONET, AEROPUERTO      BALEARES               47
#>  7 aemet   B236C      PALMA, UNIVERSITAT         ILLES BALEARS          95
#>  8 aemet   B228       PALMA, PUERTO              ILLES BALEARS           3
#>  9 aemet   B248       SIERRA DE ALFABIA, BUNYOLA ILLES BALEARS        1030
#> 10 aemet   B334X      LLUCMAJOR                  ILLES BALEARS         140
#> # ℹ 937 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 769 features and 19 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -18.115 ymin: 27.71889 xmax: 4.323889 ymax: 43.78611
#> Geodetic CRS:  WGS 84
#> # A tibble: 769 × 20
#>    timestamp           service station_id station_name station_province altitude
#>  * <dttm>              <chr>   <chr>      <chr>        <chr>                 [m]
#>  1 2020-04-25 00:00:00 aemet   0009X      ALFORJA      TARRAGONA             406
#>  2 2020-04-25 00:00:00 aemet   0016A      REUS AEROPU… TARRAGONA              71
#>  3 2020-04-25 00:00:00 aemet   0016B      REUS (CENTR… TARRAGONA             118
#>  4 2020-04-25 00:00:00 aemet   0034X      VALLS        TARRAGONA             233
#>  5 2020-04-25 00:00:00 aemet   0061X      PONTONS      BARCELONA             632
#>  6 2020-04-25 00:00:00 aemet   0073X      SITGES       BARCELONA              58
#>  7 2020-04-25 00:00:00 aemet   0076       BARCELONA A… BARCELONA               4
#>  8 2020-04-25 00:00:00 aemet   0092X      BERGA        BARCELONA             682
#>  9 2020-04-25 00:00:00 aemet   0106X      BALSARENY    BARCELONA             361
#> 10 2020-04-25 00:00:00 aemet   0114X      PRATS DE LL… BARCELONA             700
#> # ℹ 759 more rows
#> # ℹ 14 more variables: mean_temperature [°C], min_temperature [°C],
#> #   max_temperature [°C], mean_relative_humidity [%],
#> #   min_relative_humidity [%], max_relative_humidity [%],
#> #   precipitation [L/m^2], wind_direction [°], mean_wind_speed [m/s],
#> #   max_wind_speed [m/s], insolation [h], max_atmospheric_pressure [hPa],
#> #   min_atmospheric_pressure [hPa], 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 32 rows containing non-finite outside the scale range
#> (`stat_bin()`).