Appendix A — Plot Japan Climate Map

日本語はこちら（JP）

This chapter draws Japan climate maps using tmap and rnaturalearth.

Load data

data_dir <- Sys.getenv("PROJECT_DATA_DIR")
sf_climate <- readRDS(file.path(
  data_dir,
  "climate_mesh_data_joined/climate_mesh_data_with_aridity_index.rds"
))

Plot PET

# renv::install("ropensci/rnaturalearthhires")
variable <- "PET_year"
japan <- ne_states(country = "Japan", returnclass = "sf")
sf_plot <- sf_climate[!is.na(sf_climate[[variable]]), ]
tm <- tm_shape(japan, crs = 4612) +
  tm_polygons(col = "gray90") +
  tm_shape(sf_plot[, variable], crs = 4612) +
  tm_fill(
    fill = variable,
    fill.scale = tm_scale_continuous(values = "viridis"),
    fill.legend = tm_legend(
      title = variable,
      reverse = TRUE,
      position = c("right", "bottom"),
      frame = FALSE,
      bg.color = "transparent"
    )
  ) +
  tm_layout(frame = FALSE, bg.color = "transparent")
print(tm)

output_dir <- "output"
dir.create(output_dir, showWarnings = FALSE, recursive = TRUE)
tmap_save(
  tm,
  filename = file.path(
    output_dir,
    paste0("japan_climate_map_", variable, ".png")
  ),
  dpi = 300
)

PET map result; Data source: National Land Numerical Information Download Site, Ministry of Land, Infrastructure, Transport and Tourism, Japan. URL: https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-G02-v3_0.html

Plot Aridity Index

variable <- "aridity_index"
japan <- ne_states(country = "Japan", returnclass = "sf")
sf_plot <- sf_climate[!is.na(sf_climate[[variable]]), ]
tm <- tm_shape(japan, crs = 4612) +
  tm_polygons(col = "gray90") +
  tm_shape(sf_plot[, variable], crs = 4612) +
  tm_fill(
    fill = variable,
    # Low AI (drier) is yellow; high AI (wetter) is purple.
    fill.scale = tm_scale_continuous(values = hcl.colors(100, "Viridis", rev = TRUE)),
    fill.legend = tm_legend(
      title = "AI: low = dry, high = humid",
      reverse = TRUE,
      position = c("right", "bottom"),
      frame = FALSE,
      bg.color = "transparent"
    )
  ) +
  tm_layout(frame = FALSE, bg.color = "transparent")
print(tm)

tmap_save(
  tm,
  filename = file.path(
    output_dir,
    paste0("japan_climate_map_", variable, ".png")
  ),
  dpi = 300
)

Aridity Index map result; Data source: National Land Numerical Information Download Site, Ministry of Land, Infrastructure, Transport and Tourism, Japan. URL: https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-G02-v3_0.html

Yellow indicates lower AI (drier conditions); purple indicates higher AI (wetter conditions).

Plot monthly Aridity Index

The same map can be drawn for each monthly AI column. Run the loop to save one PNG per month.

japan <- ne_states(country = "Japan", returnclass = "sf")
month_labels <- month.abb
for (month in seq_along(month_labels)) {
  month_label <- month_labels[month]
  variable <- paste0("aridity_index_", month_label)
  sf_plot <- sf_climate[!is.na(sf_climate[[variable]]), ]
  tm <- tm_shape(japan, crs = 4612) +
    tm_polygons(col = "gray90") +
    tm_shape(sf_plot[, variable], crs = 4612) +
    tm_fill(
      fill = variable,
      fill.scale = tm_scale_continuous(
        values = hcl.colors(100, "Viridis", rev = TRUE)
      ),
      fill.legend = tm_legend(
        title = paste0(variable, ": low = dry, high = humid"),
        reverse = TRUE,
        position = c("right", "bottom"),
        frame = FALSE,
        bg.color = "transparent"
      )
    ) +
    tm_layout(
      frame = FALSE,
      bg.color = "transparent"
    )
  print(tm)

  tmap_save(
    tm,
    filename = file.path(
      output_dir,
      paste0("japan_climate_map_", variable, ".png")
    ),
    dpi = 300
  )
}