ERDDAP Precipitation for Sanctuaries

Code 
librarian::shelf(
  dplyr,
  DT,
  fs,
  glue,
  here,
  purrr,
  readr,
  stringr,
  tidyr,
  quiet = T)
options(readr.show_col_types = F)

dir_erddap_precip <- here("../climate-dashboard-app/data_local/erddap_precip")
results_csv       <- here("data/erddap.csv")

Read & transform

Read all per-sanctuary per-year CSVs from climate-dashboard-app/data_local/erddap_precip/ and consolidate into a single CSV matching the copernicus.csv format.

Code 
nms_dirs <- dir_ls(dir_erddap_precip, type = "directory") |>
  keep(\(x) !str_detect(basename(x), "-"))  # exclude MBNMS-david, MBNMS-main

d <- map_dfr(nms_dirs, \(nms_dir) {
  nms_code <- basename(nms_dir)
  csvs     <- dir_ls(nms_dir, glob = "*.csv")
  map_dfr(csvs, \(csv_path) {
    read_csv(csv_path) |>
      mutate(
        nms     = nms_code,
        dataset = "IMERG_monthly_global_precip",
        var     = str_replace(lyr, "\\|.*", ""),
        stat    = "mean",
        value   = mean) |>
      select(nms, dataset, var, time, stat, value)
  })
}) |>
  arrange(nms, dataset, var, time, stat)

write_csv(d, results_csv)

Results

Code 
n_sanctuaries <- n_distinct(d$nms)
time_min      <- min(d$time)
time_max      <- max(d$time)
n_rows        <- nrow(d)

glue(
  "Rows: {n_rows}
   Sanctuaries: {n_sanctuaries} ({paste(sort(unique(d$nms)), collapse = ', ')})
   Time range: {time_min} to {time_max}
   Variables: {paste(unique(d$var), collapse = ', ')}
   Stats: {paste(unique(d$stat), collapse = ', ')}
   Datasets: {paste(unique(d$dataset), collapse = ', ')}")
Rows: 4662
Sanctuaries: 14 (CBNMS, CINMS, CPNMS, FGBNMS, FKNMS, GFNMS, GRNMS, HIHWNMS, MBNMS, MNMS, NMSAS, OCNMS, SBNMS, TBNMS)
Time range: 1998-01-01 to 2025-09-01
Variables: precipitation
Stats: mean
Datasets: IMERG_monthly_global_precip
Code 
datatable(d)