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Forecast database for beaches

Source: R/aemet_forecast_beach.R
aemet_forecast_beaches.Rd

Get a database of daily weather forecasts for a beach. Beach database can be accessed with aemet_beaches().

Usage

aemet_forecast_beaches(
  x,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE,
  progress = TRUE
)

Arguments

x

A vector of beaches codes to extract. See aemet_beaches().

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

progress

Logical, display a cli::cli_progress_bar() object. If verbose = TRUE won't be displayed.

Value

A tibble or a sf object.

API Key

You need to set your API Key globally using aemet_api_key().

See also

aemet_beaches() for beaches codes.

Other aemet_api_data: aemet_alert_zones(), aemet_alerts(), aemet_beaches(), aemet_daily_clim(), aemet_extremes_clim(), aemet_forecast_daily(), aemet_forecast_fires(), aemet_last_obs(), aemet_monthly, aemet_normal, aemet_stations()

Other forecasts: aemet_forecast_daily(), aemet_forecast_fires(), aemet_forecast_tidy()

Examples

# Forecast for beaches in Palma, Mallorca
library(dplyr)
library(ggplot2)

palma_b <- aemet_beaches() %>%
  filter(ID_MUNICIPIO == "07040")

forecast_b <- aemet_forecast_beaches(palma_b$ID_PLAYA)
#> 
#> AEMET API call for '0704001' returned an error
#> Return NULL for this query
glimpse(forecast_b)
#> Rows: 3
#> Columns: 36
#> $ elaborado                <dttm> 2025-04-02 08:50:17, 2025-04-02 08:50:17, 20…
#> $ id                       <chr> "0704007", "0704007", "0704007"
#> $ localidad                <chr> "07040", "07040", "07040"
#> $ fecha                    <date> 2025-04-02, 2025-04-03, 2025-04-04
#> $ nombre                   <chr> "Playa de Palma", "Playa de Palma", "Playa de…
#> $ estadoCielo_value        <lgl> NA, NA, NA
#> $ estadoCielo_f1           <int> 120, 110, 120
#> $ estadoCielo_descripcion1 <chr> "muy nuboso", "nuboso", "muy nuboso"
#> $ estadoCielo_f2           <int> 120, 120, 100
#> $ estadoCielo_descripcion2 <chr> "muy nuboso", "muy nuboso", "despejado"
#> $ viento_value             <lgl> NA, NA, NA
#> $ viento_f1                <int> 220, 220, 220
#> $ viento_descripcion1      <chr> "moderado", "moderado", "moderado"
#> $ viento_f2                <int> 220, 220, 220
#> $ viento_descripcion2      <chr> "moderado", "moderado", "moderado"
#> $ oleaje_value             <lgl> NA, NA, NA
#> $ oleaje_f1                <int> 310, 310, 310
#> $ oleaje_descripcion1      <chr> "débil", "débil", "débil"
#> $ oleaje_f2                <int> 310, 310, 310
#> $ oleaje_descripcion2      <chr> "débil", "débil", "débil"
#> $ tMaxima_value            <lgl> NA, NA, NA
#> $ tMaxima_valor1           <int> 20, 22, 23
#> $ sTermica_value           <lgl> NA, NA, NA
#> $ sTermica_valor1          <int> 440, 450, 450
#> $ sTermica_descripcion1    <chr> "fresco", "suave", "suave"
#> $ tAgua_value              <lgl> NA, NA, NA
#> $ tAgua_valor1             <int> 16, 16, 16
#> $ uvMax_value              <lgl> NA, NA, NA
#> $ uvMax_valor1             <int> 6, 6, 5
#> $ tmaxima_value            <lgl> NA, NA, NA
#> $ tmaxima_valor1           <int> 20, 22, 23
#> $ stermica_value           <lgl> NA, NA, NA
#> $ stermica_valor1          <int> 440, 450, 450
#> $ stermica_descripcion1    <chr> "fresco", "suave", "suave"
#> $ tagua_value              <lgl> NA, NA, NA
#> $ tagua_valor1             <int> 16, 16, 16

ggplot(forecast_b) +
  geom_line(aes(fecha, tagua_valor1, color = nombre)) +
  facet_wrap(~nombre, ncol = 1) +
  labs(
    title = "Water temperature in beaches of Palma (ES)",
    subtitle = "Forecast 3-days",
    x = "Date",
    y = "Temperature (Celsius)",
    color = "Beach"
  )