Access to Spanish Meteorological Stations Services.

meteospain

meteospain aims to offer access to different Spanish meteorological stations data in an uniform way.

Installation

meteospain is in CRAN, and can be installed as any other package:

install.packages('meteospain')

Also, meteospain is in active development. You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("emf-creaf/meteospain")

Services

The following meteorological stations services are available:

• AEMET, the Spanish State Meteorological Agency.
• MeteoCat, the Catalan Meteorology Service.
• MeteoGalicia, the Galician Meteorological Service.
• RIA, the Andalucian Agroclimatic Information Network.
• Meteoclimatic, the Spanish non-professional meteorological stations network.

Examples

Access to the services is done with the get_meteo_from function, providing the name of the service and the options. Each service has a dedicated *service*_options() function to guide through the specifics of each service:

library(meteospain)

mg_options <- meteogalicia_options(resolution = 'current_day')
get_meteo_from('meteogalicia', mg_options)
#> ℹ A información divulgada a través deste servidor ofrécese gratuitamente aos
#>   cidadáns para que poida ser
#> utilizada libremente por eles, co único compromiso de mencionar expresamente a
#> MeteoGalicia e á
#> Consellería de Medio Ambiente, Territorio e Vivenda da Xunta de Galicia como
#> fonte da mesma cada vez
#> que as utilice para os usos distintos do particular e privado.
#> https://www.meteogalicia.gal/web/informacion/notaIndex.action
#> Simple feature collection with 3720 features and 14 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -9.178318 ymin: 41.8982 xmax: -6.765224 ymax: 43.734
#> Geodetic CRS:  WGS 84
#> # A tibble: 3,720 × 15
#>    timestamp           service station_id station_name station_province altitude
#>    <dttm>              <chr>   <chr>      <chr>        <chr>                 [m]
#>  1 2023-10-22 14:00:00 meteog… 10045      Mabegondo    A Coruña               94
#>  2 2023-10-22 14:00:00 meteog… 10046      Marco da Cu… A Coruña              651
#>  3 2023-10-22 14:00:00 meteog… 10047      Pedro Murias Lugo                   51
#>  4 2023-10-22 14:00:00 meteog… 10048      O Invernade… Ourense              1026
#>  5 2023-10-22 14:00:00 meteog… 10049      Corrubedo    A Coruña               30
#>  6 2023-10-22 14:00:00 meteog… 10050      CIS Ferrol   A Coruña               37
#>  7 2023-10-22 14:00:00 meteog… 10052      Muralla      A Coruña              661
#>  8 2023-10-22 14:00:00 meteog… 10053      Campus Lugo  Lugo                  400
#>  9 2023-10-22 14:00:00 meteog… 10055      Guitiriz-Mi… Lugo                  684
#> 10 2023-10-22 14:00:00 meteog… 10056      Marroxo      Lugo                  645
#> # ℹ 3,710 more rows
#> # ℹ 9 more variables: temperature [°C], min_temperature [°C],
#> #   max_temperature [°C], relative_humidity [%], precipitation [L/m^2],
#> #   wind_direction [°], wind_speed [m/s], insolation [h], geometry <POINT [°]>

Stations info can be accessed with get_stations_info_from function:

get_stations_info_from('meteogalicia', mg_options)
#> Simple feature collection with 156 features and 5 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -9.178318 ymin: 41.8982 xmax: -6.765224 ymax: 43.7383
#> Geodetic CRS:  WGS 84
#> # A tibble: 156 × 6
#>    service      station_id station_name             station_province altitude
#>  * <chr>        <chr>      <chr>                    <chr>                 [m]
#>  1 meteogalicia 10157      Coruña-Torre de Hércules A Coruña               21
#>  2 meteogalicia 14000      Coruña-Dique             A Coruña                5
#>  3 meteogalicia 10045      Mabegondo                A Coruña               94
#>  4 meteogalicia 14003      Punta Langosteira        A Coruña                5
#>  5 meteogalicia 10144      Arzúa                    A Coruña              362
#>  6 meteogalicia 19005      Guísamo                  A Coruña              175
#>  7 meteogalicia 19012      Cespón                   A Coruña               59
#>  8 meteogalicia 10095      Sergude                  A Coruña              231
#>  9 meteogalicia 10800      Camariñas                A Coruña                5
#> 10 meteogalicia 19001      Rus                      A Coruña              134
#> # ℹ 146 more rows
#> # ℹ 1 more variable: geometry <POINT [°]>

Returned objects are spatial objects (using the sf R package), so results can be plotted directly:

library(sf)
#> Linking to GEOS 3.12.0, GDAL 3.7.2, PROJ 9.2.1; sf_use_s2() is TRUE
mg_options <- meteogalicia_options(resolution = 'daily', start_date = as.Date('2021-04-25'))
plot(get_meteo_from('meteogalicia', mg_options))
#> ℹ A información divulgada a través deste servidor ofrécese gratuitamente aos
#>   cidadáns para que poida ser
#> utilizada libremente por eles, co único compromiso de mencionar expresamente a
#> MeteoGalicia e á
#> Consellería de Medio Ambiente, Territorio e Vivenda da Xunta de Galicia como
#> fonte da mesma cada vez
#> que as utilice para os usos distintos do particular e privado.
#> https://www.meteogalicia.gal/web/informacion/notaIndex.action
#> Warning: plotting the first 9 out of 16 attributes; use max.plot = 16 to plot
#> all

plot(get_stations_info_from('meteogalicia', mg_options))

API keys

Some services, like AEMET or Meteocat, require an API key to access the data. meteospaindoesn’t provide any key for those services, see ?services_options for information about this.

Once a key has been obtained, we can get the meteo:

get_meteo_from('aemet', aemet_options(api_key = keyring::key_get("aemet")))
#> 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
#> Simple feature collection with 18048 features and 14 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -18.115 ymin: 27.66667 xmax: 4.323889 ymax: 43.78621
#> Geodetic CRS:  WGS 84
#> # A tibble: 18,048 × 15
#>    timestamp           service station_id station_name station_province altitude
#>    <dttm>              <chr>   <chr>      <chr>        <chr>                 [m]
#>  1 2023-10-22 14:00:00 aemet   0016A      REUS/AEROPU… <NA>                   71
#>  2 2023-10-22 14:00:00 aemet   0034X      VALLS        <NA>                  233
#>  3 2023-10-22 14:00:00 aemet   0042Y      TARRAGONA  … <NA>                   55
#>  4 2023-10-22 14:00:00 aemet   0061X      PONTONS      <NA>                  632
#>  5 2023-10-22 14:00:00 aemet   0066X      VILAFRANCA … <NA>                  177
#>  6 2023-10-22 14:00:00 aemet   0073X      SITGES-VALL… <NA>                   58
#>  7 2023-10-22 14:00:00 aemet   0076       BARCELONA/A… <NA>                    4
#>  8 2023-10-22 14:00:00 aemet   0106X      BALSARENY    <NA>                  361
#>  9 2023-10-22 14:00:00 aemet   0114X      PRATS DE LL… <NA>                  700
#> 10 2023-10-22 14:00:00 aemet   0120X      MOIÀ         <NA>                  742
#> # ℹ 18,038 more rows
#> # ℹ 9 more variables: temperature [°C], min_temperature [°C],
#> #   max_temperature [°C], relative_humidity [%], precipitation [L/m^2],
#> #   wind_direction [°], wind_speed [m/s], insolation [h], geometry <POINT [°]>