AEMET service
In meteospain: Access to Spanish Meteorological Stations Services

# use eval = NOT_CRAN in the chunks connecting to API, to avoid errors or warnings in CRAN checks
NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true")
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  purl = NOT_CRAN
)

# env keyring
withr::local_options(list("keyring_backend" = "env"))

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

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:

r 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

# current day, all stations
fake_api <- aemet_options(
  resolution = 'current_day',
  api_key = 'my_api_key'
)
fake_api

# 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

# daily, all stations
fake_api <- aemet_options(
  resolution = 'daily',
  start_date = as.Date('2020-04-25'), end_date = as.Date('2020-05-08'),
  api_key = 'my_api_key'
)
fake_api

# 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

# monthly, only one station because AEMET API limitations
fake_api <- aemet_options(
  resolution = 'monthly',
  start_date = as.Date('2020-01-01'), end_date = as.Date('2020-12-31'),
  station = "0149X",
  api_key = 'my_api_key'
)
fake_api

AEMET stations info

Accessing station metadata for AEMET is simple:

get_stations_info_from('aemet', api_options)

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)
spain_20200425

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))