ERDDAP Extraction

metadata: erddap_sst.yml

Published

2025-08-13 00:02 UTC

Code

# dir_extractr = "/share/github/marinebon/extractr"
# dir_extractr = "~/Github/marinebon/extractr" # DEBUG
# devtools::load_all(dir_extractr)
# devtools::install_local(dir_extractr, force = T)
# devtools::install_github("marinebon/extractr", force = T)
librarian::shelf(
  dplyr, DT, fs, glue, here, logger, lubridate, mapview, purrr, RColorBrewer, readr, 
  sf, stringr, terra, tibble, tidyr, units, yaml,
  marinebon/extractr,
  quiet = T)

options(readr.show_col_types = F)
mapviewOptions(
  basemaps       = "Esri.OceanBasemap",
  vector.palette = colorRampPalette(brewer.pal(n=5, name="Spectral")))

if (!exists("params"))
  params <- list(yml = here("meta/erddap_sst.yml")) # DEBUG

1 Polygons

Code

sanctuaries_rds <- here("../climate-dashboard/data/sanctuaries.rds")
buf_pct         <- 0.20 # 20% of area

ply_sanctuaries <- readRDS(sanctuaries_rds)

# buffer polygon and get bounding boxes
ply_sanctuaries <- ply_sanctuaries |>
  mutate(
    area_km2  = st_area(geom) |> 
      set_units("km^2") |> 
      as.numeric() |> 
      round(2),
    buf_km    = (sqrt(area_km2) * buf_pct) |> 
      round(2),
    bbox_geom = map2(geom, area_km2, \(g,a) {
      st_sfc(g, crs = 4326) |> 
        st_buffer(buf_km * 1000) |> 
        st_bbox() |>
        round(2) |> 
        st_as_sfc() }),
    bbox_chr  = map_chr(bbox_geom, \(x) {  # xmin, ymin, xmax and ymax
      st_bbox(x) |> 
        as.numeric() |> 
        paste(collapse = ",") } ) ) |> 
  unnest(bbox_geom)
bb_sanctuaries <- st_set_geometry(ply_sanctuaries, "bbox_geom") |> 
  select(-geom)
ply_sanctuaries <- select(ply_sanctuaries, -bbox_geom)

# show map
mapView(ply_sanctuaries, zcol = "nms") +
  mapView(bb_sanctuaries, zcol = "nms", legend = F)

Code

ply_sanctuaries |>
  st_drop_geometry() |>
  datatable()

2 Dataset

2.1 Metadata

Contents of erddap_sst.yml:

Code

cat(
  "```yaml",
  readLines(params$yml),
  "```",
  sep = "\n")

erddap_url: https://coastwatch.noaa.gov/erddap/griddap/noaacrwsstDaily.html
erddap_variable: analysed_sst

2.2 Information

Code

meta <- read_yaml(params$yml) 
proc_prod <- path_ext_remove(basename(params$yml))

dir_out <- glue("/share/data/noaa-onms/climate-dashboard-app/{proc_prod}")
dir_create(dir_out)

v     <- meta$erddap_variable
(ed   <- ed_info(meta$erddap_url))

<ERDDAP info> noaacrwsstDaily 
 Base URL: https://coastwatch.noaa.gov/erddap 
 Dataset Type: griddap 
 Dimensions (range):  
     time: (1985-01-01T12:00:00Z, 2025-08-10T12:00:00Z) 
     latitude: (-89.975, 89.975) 
     longitude: (-179.975, 179.975) 
 Variables:  
     analysed_sst: 
         Units: degree_C 
     sea_ice_fraction: 
         Units: 1

Code

times <- ed_dim(ed, "time")

3 Polygon years

Code

d_nms_yr_todo <- ply_sanctuaries |> 
  st_drop_geometry() |> 
  arrange(nms) |> 
  select(nms) |> 
  cross_join(
    tibble(
      year = year(min(times)):year(max(times)))) |> 
  mutate(
    d = map2(nms, year, \(nms, year) { # nms = "CBNMS"; year = 2025
      
      times_yr <- times[year(times) == year]
      tif      <- glue("{dir_out}/{nms}/{year}.tif")
      
      # if missing tif,return all times
      if (!file.exists(tif))
        return(list(
          time_min = min(times_yr),
          time_max = max(times_yr),
          n_times  = length(times_yr)))
      
      # get times from tif
      r <- rast(tif)
      times_tif <- time(r)
      
      # if all times done, return NAs
      if (all(times_yr %in% times_tif))
        return(list(
          n_times  = 0,
          time_min = NA,
          time_max= NA)) 
      
      # otherwise, return time range missing
      i <- !times_yr %in% times_tif
      list(
          n_times  = sum(i),
          time_min = min(times_yr[i]),
          time_max = max(times_yr[i])) 
      }),
    time_min = map_vec(d, pluck, "time_min"),
    time_max = map_vec(d, pluck, "time_max"),
    n_times  = map_int(d, pluck, "n_times") ) |> 
  select(-d) |> 
  filter(n_times > 0) |> 
  rowid_to_column("i") |>
  relocate(i)

d_nms_yr_todo |> 
  group_by(nms) %>%
  {if (nrow(.) > 0)
    summarize(
      .,
      time_min = min(time_min, na.rm = T),
      time_max = max(time_max, na.rm = T),
      n_times  = sum(n_times)) else .} |>
  datatable(
    caption  = "Sanctuaries missing available ERDDAP times.",
    rownames = F,
    options  = list(
      pageLength = 5,
      lengthMenu = c(5, 50, nrow(d_nms_yr_todo))))

4 Extract dataset per polygon year

Using extractr::ed_extract(), .

Code

# rerddap::cache_delete_all()

fxn <- function(i, nms, time_min, time_max, ...){ #  nms = "MNMS"; year = 2010 ; i = 97
  
  err <- tryCatch({
    
    log_info("{sprintf('%03d', i)}: {nms}, {time_min} to {time_max}")
    
    yr <- year(time_min)

    ply <- ply_sanctuaries |>
      filter(nms == !!nms)
    bb <- bb_sanctuaries |>
      filter(nms == !!nms) |> 
      st_bbox()
    
    extractr::ed_extract(
      ed,
      var       = v,
      sf_zones  = ply,
      bbox      = bb,
      mask_tif  = F,
      rast_tif  = glue("{dir_out}/{nms}/{yr}.tif"),
      zonal_fun = "mean",
      zonal_csv = glue("{dir_out}/{nms}/{yr}.csv"),
      dir_nc    = glue("{dir_out}/{nms}/{yr}_nc"),
      keep_nc   = F,
      n_max_vals_per_req = 1e+05,
      time_min  = time_min,
      time_max  = time_max,
      verbose   = T)
    
    return(NA)
  }, error = function(e) {
    
    log_error(conditionMessage(e))
    return(conditionMessage(e))
  })
  
  err
} 

res <- d_nms_yr_todo |> 
  mutate(
    error = pmap_chr(list(i, nms, time_min, time_max), fxn))

Downloading 1 requests, up to 111 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:01:31 UTC

Downloading 1 requests, up to 63 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:01:38 UTC

Downloading 1 requests, up to 36 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:01:44 UTC

Downloading 1 requests, up to 64 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:01:54 UTC

Error in open.connection(structure(4L, class = c("curl", "connection"), conn_id = <pointer: 0x55a11f705880>),  : 
  cannot open the connection
Error in open.connection(structure(5L, class = c("curl", "connection"), conn_id = <pointer: 0x55a1284e8320>),  : 
  cannot open the connection

Downloading 1 requests, up to 392 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:05 UTC

Downloading 1 requests, up to 16 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:11 UTC

Downloading 1 requests, up to 27 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:17 UTC

Downloading 1 requests, up to 162 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:24 UTC

Error in open.connection(structure(6L, class = c("curl", "connection"), conn_id = <pointer: 0x55a12066fd70>),  : 
  cannot open the connection

Downloading 1 requests, up to 420 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:32 UTC

Error : Error {
    code=503;
    message="Service Unavailable: There was a (temporary?) problem.  Wait a minute, then try again.  (In a browser, click the Reload button.)";
}


RETRYing...

Downloading 1 requests, up to 10 time slices each

Fetching request 1 of 1 (2025-08-09 to 2025-08-10) ~ 00:02:42 UTC

Error in open.connection(structure(7L, class = c("curl", "connection"), conn_id = <pointer: 0x55a116065c30>),  : 
  cannot open the connection
Error in open.connection(structure(8L, class = c("curl", "connection"), conn_id = <pointer: 0x55a12781ebb0>),  : 
  cannot open the connection
Error in open.connection(structure(9L, class = c("curl", "connection"), conn_id = <pointer: 0x55a118db8870>),  : 
  cannot open the connection

Warning: There were 6 warnings in `mutate()`.
The first warning was:
ℹ In argument: `error = pmap_chr(list(i, nms, time_min, time_max), fxn)`.
Caused by warning:
! Failed to open 'https://coastwatch.noaa.gov/erddap/griddap/noaacrwsstDaily.csvp?longitude': The requested URL returned error: 503
ℹ Run `dplyr::last_dplyr_warnings()` to see the 5 remaining warnings.

4.1 Successes

Code

res |> 
  mutate(
    success = is.na(error)) |> 
  group_by(success) |> 
  summarize(
    n = n()) |> 
  datatable()

4.2 Errors (if any)

Code

# rast(glue("{dir_out}/{nms}/{yr}.tif")) |> names()

res |> 
  filter(!is.na(error)) |> 
  group_by(nms) |> 
  summarize(
    n_years = n(),
    errors  = unique(error) |> paste(collapse = "\n\n----\n\n")) |> 
  datatable()

R package versions

Code

devtools::session_info()

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.2 (2024-10-31)
 os       Ubuntu 24.04.1 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-08-13
 pandoc   3.5 @ /usr/bin/ (via rmarkdown)

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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library

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