Get last observation values for a station.
Usage
aemet_last_obs(
station = "all",
verbose = FALSE,
return_sf = FALSE,
extract_metadata = FALSE,
progress = TRUE
)Arguments
- station
Character string with station identifier code(s) (see
aemet_stations()) or "all" for all the stations.- verbose
Logical
TRUE/FALSE. Provides information about the flow of information between the client and server.- return_sf
Logical
TRUEorFALSE. Should the function return ansfspatial object? IfFALSE(the default value) it returns a tibble. Note that you need to have the sf package installed.- extract_metadata
Logical
TRUE/FALSE. OnTRUEthe output is a tibble with the description of the fields. See alsoget_metadata_aemet().- progress
Logical, display a
cli::cli_progress_bar()object. Ifverbose = TRUEwon't be displayed.
API Key
You need to set your API Key globally using aemet_api_key().
Examples
library(tibble)
obs <- aemet_last_obs(c("9434", "3195"))
glimpse(obs)
#> Rows: 26
#> Columns: 26
#> $ idema <chr> "9434", "9434", "9434", "9434", "9434", "9434", "9434", "943…
#> $ lon <dbl> -1.004167, -1.004167, -1.004167, -1.004167, -1.004167, -1.00…
#> $ fint <dttm> 2026-04-24 21:00:00, 2026-04-24 22:00:00, 2026-04-24 23:00:…
#> $ prec <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ alt <dbl> 249, 249, 249, 249, 249, 249, 249, 249, 249, 249, 249, 249, …
#> $ vmax <dbl> 4.3, 2.7, 2.9, 3.2, 2.5, 3.3, 1.4, 2.1, 2.3, 2.9, 4.7, 8.6, …
#> $ vv <dbl> 2.0, 2.2, 1.5, 1.1, 1.4, 1.2, 1.0, 1.3, 0.9, 1.1, 3.1, 5.6, …
#> $ dv <dbl> 106, 107, 66, 72, 121, 96, 66, 121, 253, 325, 314, 304, 330,…
#> $ lat <dbl> 41.66056, 41.66056, 41.66056, 41.66056, 41.66056, 41.66056, …
#> $ dmax <dbl> 103, 95, 110, 85, 85, 138, 318, 138, 303, 310, 315, 290, 303…
#> $ ubi <chr> "ZARAGOZA AEROPUERTO", "ZARAGOZA AEROPUERTO", "ZARAGOZA A…
#> $ pres <dbl> 987.5, 988.0, 988.3, 988.2, 988.0, 988.0, 988.2, 988.1, 988.…
#> $ hr <dbl> 55, 59, 63, 71, 74, 73, 75, 78, 78, 78, 78, 70, 65, 75, 63, …
#> $ stdvv <dbl> 0.5, 0.2, 0.4, 0.3, 0.2, 0.1, 0.2, 0.3, 0.4, 0.4, 0.8, 1.0, …
#> $ ts <dbl> 17.1, 15.7, 15.1, 15.9, 13.2, 15.4, 13.3, 12.3, 12.4, 14.1, …
#> $ pres_nmar <dbl> 1016.8, 1017.4, 1017.8, 1017.8, 1017.7, 1017.7, 1018.0, 1018…
#> $ tamin <dbl> 20.1, 19.0, 18.1, 16.9, 16.0, 15.9, 15.5, 14.7, 14.4, 14.2, …
#> $ ta <dbl> 20.1, 19.0, 18.1, 16.9, 16.0, 16.1, 15.5, 14.7, 14.4, 14.8, …
#> $ tamax <dbl> 21.5, 20.1, 19.0, 18.1, 16.9, 16.2, 16.1, 15.5, 14.7, 14.8, …
#> $ tpr <dbl> 10.8, 10.8, 11.0, 11.6, 11.3, 11.2, 11.1, 10.9, 10.6, 11.0, …
#> $ stddv <dbl> 11, 7, 13, 23, 18, 14, 11, 19, 24, 124, 11, 11, 13, NA, NA, …
#> $ inso <dbl> 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.7, 58.9, 60.0…
#> $ tss5cm <dbl> 24.7, 23.8, 23.1, 22.6, 22.1, 21.6, 21.4, 20.9, 20.4, 20.1, …
#> $ pacutp <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, N…
#> $ tss20cm <dbl> 23.9, 23.9, 23.7, 23.5, 23.3, 23.1, 22.9, 22.6, 22.4, 22.2, …
#> $ rviento <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 27, 60, …
