UKCP18 SPEED bias corrected scenarios: create metadata and convert to tif

Create metadata of bias corrected datasets corresponding to environmental scenarios for periods of 20 years from UKCP18 SPEED project, and convert them to tif format. The scenarios correspond to different assumptions for Representative Concentration Pathway (RCP) which is related to greenhouse gas concentrations.

Load packages, read data and source custom scripts

rm(list = ls())
library(dplyr)

#> 
#> Attaching package: 'dplyr'

#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag

#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

library(stars)

#> Loading required package: abind

#> Loading required package: sf

#> Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1

path_proj <- day2day::git_path()
path_data <- file.path(path_proj, "data")
path_raw <- file.path(path_data, "raw")
path_cleaned <- file.path(path_data, "cleaned")
path_sce <- file.path(path_raw, "ukcp18-speed-bias-corrected")

source(file.path(path_proj, "src", "22-nc-to-tif.R"))

Create metadata using the file names

regex_extract <- paste(
    "ukcp18-speed_(rcp[[:digit:]]+)", "bias_corrected", "01_(.+)",
    "uk_1km_20yr-([[:alpha:]]+)-([[:alpha:]]+)", "([[:digit:]]+)-([[:digit:]]+)\\.nc",
    sep = "_"
)

metadata <- create_metadata(path_sce, regex_extract)

Convert to tif

purrr::walk2(metadata$file, metadata$variable, ~ nc_to_tif(.x, .y, path_sce, path_cleaned))

Save metadata

write.csv(metadata, file.path(path_sce, "metadata.csv"), row.names = FALSE)
metadata <- mutate(metadata, file = sub("\\.nc$", "\\.tif", file))
write.csv(metadata, file.path(path_cleaned, "ukcp18-speed_bias_corrected_01_metadata.csv"),
          row.names = FALSE)

Time to execute the task

Only useful when executed with Rscript.

proc.time()

#>    user  system elapsed 
#> 649.382  49.861 699.645