Datos

Como ayer usé datos del reanálisis oceánico, hoy le toca a la atmósfera. Los datos salen de nuevo del Climate Data Store y esta vez voy a usar el paquete ecmwfr para descargarlos automáticamente.

request <- list(
  format = "netcdf",
  product_type = "monthly_averaged_reanalysis",
  variable = "geopotential",
  pressure_level = c("200", "500", "1000"),
  year = "2023",
  month = "10",
  time = "00:00",
  dataset_short_name = "reanalysis-era5-pressure-levels-monthly-means",
  target = "geopotencial_era5.nc"
)

ecmwfr::wf_request(request, user = "94903", path = "datos/")
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## [1] "datos//geopotencial_era5.nc"

Voy a trabajar con datos de geopotencial que viene a ser a que altura desde la superficie me encuentro con una determinada presión atmosférica y da una idea de donde están los centros de presión y la pinta del viento geostrófico. Esto es la media mensual para octubre de 2023.

sf::sf_use_s2(FALSE)
mapa <- rnaturalearth::ne_coastline(returnclass = "sf") %>% 
  sf::st_crop(xmin = -180, xmax = 180, ymin = -90, ymax = -5)

z <- ReadNetCDF("datos/geopotencial_era5.nc")

grid <- expand.grid(longitude = seq(0, 360, by = 2.5),
                    latitude = seq(-90, 90, by = 2.5))

z %>% 
  .[level == 200] %>% 
  .[latitude < 0] %>% 
  .[, gh.z := Anomaly(z), by = .(latitude)] %>% 
  .[, c("u", "v") := GeostrophicWind(gh.z, longitude, latitude)] %>% 
  .[grid, on = .NATURAL] %>% 
  na.omit() %>% 
  ggplot(aes(longitude, latitude)) +
  geom_contour_fill(aes(z = gh.z, fill = after_stat(level)), xwrap = c(0, 360)) +
  geom_sf(data = mapa, inherit.aes = FALSE) +
  geom_streamline(aes(dx = dlon(u, latitude), dy = dlat(v)), 
                  dt = 100, S = 100, 
                  xwrap = c(0, 360), arrow = NULL) +
  scale_fill_divergent_discretised(guide = guide_colorsteps(barwidth = 0.5,
                                                            barheight = 15)) +
  coord_sf(crs = "+proj=laea +lat_0=-90", default_crs = "+proj=lonlat") +
  labs(x = NULL, y = NULL, fill = NULL,
       title = "Anomalía de la altura geopotencial en 200 hPa y viento geostrófico",
       subtitle = "Promedio mensual para octubre de 2023",
       caption = "Fuente: ERA5 - Reanalisis Europeo") +
  theme_void(base_size = 10,
             base_family = "Roboto Condensed Light") +
  theme(plot.title = element_text(face = "bold"),
        plot.margin = unit(c(0.3, 0.3, 0.3, 0.3), "cm"))

# ggsave("day18.png", device = png, type = "cairo", bg = "white", width = 12, height = 11, units = "cm", dpi = 150)