# MeteoGalicia service

    library(meteospain)
    library(dplyr)
    library(ggplot2)
    library(ggforce)
    library(units)
    library(sf)

# MeteoGalicia service

MeteoGalicia service offers the data of the galician automatic meteorological stations network. This network is supported and assessed by the Xunta de Galicia and the data should be trustworthy.

## MeteoGalicia options

### Temporal resolution

MeteoGalicia API offers data at different temporal resolutions:

- “instant”, returning the latest measures for all or selected stations.
- “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 all or selected stations.

In both, “daily” and “monthly”, a `start_date` (and optionally an `end_date`) arguments must be provided, indicating the period from which retrieve the data.

### Stations

MeteoGalicia API allows specifying stations code to narrow the data retrieved. So, a character vector of station codes can be supplied in the `stations` argument.

### Examples

    # last measure for all stations
    api_options <- meteogalicia_options()
    api_options
    #> $resolution
    #> [1] "instant"
    #>
    #> $start_date
    #> [1] "2025-11-12"
    #>
    #> $end_date
    #> [1] "2025-11-12"
    #>
    #> $stations
    #> NULL

    # current day, only some stations
    api_options <- meteogalicia_options(
      resolution = 'current_day',
      stations = c('10157', '14000', '10045')
    )
    api_options
    #> $resolution
    #> [1] "current_day"
    #>
    #> $start_date
    #> [1] "2025-11-12"
    #>
    #> $end_date
    #> [1] "2025-11-12"
    #>
    #> $stations
    #> [1] "10157" "14000" "10045"

    # daily, all stations
    api_options <- meteogalicia_options(
      resolution = 'daily',
      start_date = as.Date('2020-04-25'), end_date = as.Date('2020-05-25')
    )
    api_options
    #> $resolution
    #> [1] "daily"
    #>
    #> $start_date
    #> [1] "2020-04-25"
    #>
    #> $end_date
    #> [1] "2020-05-25"
    #>
    #> $stations
    #> NULL

    # monthly, some stations
    api_options <- meteogalicia_options(
      resolution = 'monthly',
      start_date = as.Date('2020-04-01'), end_date = as.Date('2020-08-01'),
      stations = c('10157', '14000', '10045')
    )
    api_options
    #> $resolution
    #> [1] "monthly"
    #>
    #> $start_date
    #> [1] "2020-04-01"
    #>
    #> $end_date
    #> [1] "2020-08-01"
    #>
    #> $stations
    #> [1] "10157" "14000" "10045"

## MeteoGalicia stations info

Accessing station metadata for MeteoGalicia is simple:

    get_stations_info_from('meteogalicia')
    #> Simple feature collection with 155 features and 5 fields
    #> Geometry type: POINT
    #> Dimension:     XY
    #> Bounding box:  xmin: -9.184586 ymin: 41.8982 xmax: -6.765224 ymax: 43.7383
    #> Geodetic CRS:  WGS 84
    #> # A tibble: 155 × 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 10095      Sergude                  A Coruña              231
    #>  8 meteogalicia 10800      Camariñas                A Coruña                5
    #>  9 meteogalicia 19001      Rus                      A Coruña              134
    #> 10 meteogalicia 10147      Cariño                   A Coruña               20
    #> # ℹ 145 more rows
    #> # ℹ 1 more variable: geometry <POINT [°]>

## MeteoGalicia data

    api_options <- meteogalicia_options(
      resolution = 'monthly',
      start_date = as.Date('2020-01-01'),
      end_date = as.Date('2020-12-31')
    )
    galicia_2020 <- get_meteo_from('meteogalicia', options = api_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/aviso-legal
    galicia_2020
    #> Simple feature collection with 1770 features and 31 fields
    #> Geometry type: POINT
    #> Dimension:     XY
    #> Bounding box:  xmin: -9.178318 ymin: 41.8982 xmax: -6.765224 ymax: 43.70426
    #> Geodetic CRS:  WGS 84
    #> # A tibble: 1,770 × 32
    #>    timestamp           service station_id station_name station_province altitude
    #>    <dttm>              <chr>   <chr>      <chr>        <chr>                 [m]
    #>  1 2020-01-01 00:00:00 meteog… 10045      Mabegondo    A Coruña               94
    #>  2 2020-01-01 00:00:00 meteog… 10046      Marco da Cu… A Coruña              651
    #>  3 2020-01-01 00:00:00 meteog… 10047      Pedro Murias Lugo                   51
    #>  4 2020-01-01 00:00:00 meteog… 10048      O Invernade… Ourense              1026
    #>  5 2020-01-01 00:00:00 meteog… 10049      Corrubedo    A Coruña               30
    #>  6 2020-01-01 00:00:00 meteog… 10050      CIS Ferrol   A Coruña               37
    #>  7 2020-01-01 00:00:00 meteog… 10052      Muralla      A Coruña              661
    #>  8 2020-01-01 00:00:00 meteog… 10053      Campus Lugo  Lugo                  400
    #>  9 2020-01-01 00:00:00 meteog… 10055      Guitiriz-Mi… Lugo                  684
    #> 10 2020-01-01 00:00:00 meteog… 10056      Marroxo      Lugo                  645
    #> # ℹ 1,760 more rows
    #> # ℹ 26 more variables: mean_temperature [°C], min_temperature [°C],
    #> #   min_temperature_mean [°C], max_temperature [°C], max_temperature_mean [°C],
    #> #   mean_relative_humidity [%], min_relative_humidity_mean [%],
    #> #   max_relative_humidity_mean [%], precipitation [L/m^2],
    #> #   max_precipitation_24h [L/m^2], mean_wind_direction [°],
    #> #   max_wind_direction [°], mean_wind_speed [m/s], max_wind_speed [m/s], …

Visually:

    galicia_2020 |>
      units::drop_units() |>
      mutate(month = lubridate::month(timestamp, label = TRUE)) |>
      ggplot() +
      geom_sf(aes(colour = max_temperature)) +
      facet_wrap(vars(month), ncol = 4) +
      scale_colour_viridis_c()

    galicia_2020 |>
      mutate(month = lubridate::month(timestamp, label = TRUE)) |>
      ggplot() +
      geom_histogram(aes(x = precipitation)) +
      facet_wrap(vars(month), ncol = 4)
    #> `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
    #> Warning: Removed 1 row containing non-finite outside the scale range
    #> (`stat_bin()`).