Prepare climate data for multiple scenarios

Prepare data from raw to form needed for calculating the index. See the NatureServe Guidelines for details on how the data is prepared. This processes multiple scenarios with the same set of breaks.

Usage

prep_clim_data_multi(
  mat_norm,
  mat_fut,
  cmd_norm,
  cmd_fut,
  ccei = NULL,
  map = NULL,
  mwmt = NULL,
  mcmt = NULL,
  clim_poly = NULL,
  in_folder = NULL,
  out_folder,
  reproject = FALSE,
  overwrite = FALSE,
  scenario_name = "",
  brks = NULL,
  brks_mat = NULL,
  brks_cmd = NULL,
  brks_ccei = NULL,
  quiet = FALSE
)

Arguments

mat_norm, mat_fut, cmd_norm, cmd_fut, ccei, map, mwmt, mcmt, clim_poly: file paths to find data if in_folder is not given
in_folder: file path where files are stored. Files must be named according to the convention described in details
out_folder: Character. Path where the processed files will be saved.
reproject: should the data be re-projected to lat/long? Not recommended.
overwrite: Logical. Whether to overwrite existing file(s)
scenario_name: Character. A string identifying the climate change scenario(s) that will be used as a suffix for the output files.
brks: List. Optionally supply brks_mat, brks_cmd and brks_ccei as a list.
brks_mat, brks_cmd, brks_ccei: a matrix containing breaks to use for classifying mat, cmd and ccei into 6, 6 and 4 classes, respectively. See reclassify for details on the matrix format. If NULL, the default, the breaks will be determined using the median and half the interquartile range
quiet: Logical. Whether to suppress progress messages.

Value

Returns a list of matrices with the breaks used to classify mat, cmd and ccei. Processed data is saved in out_folder

Details

Definition of input data sets and file names required in in_folder:

mat_norm:: "MAT" mean annual temperature for the historical normal period
mat_fut:: "MAT_2050" mean annual temperature for the future under climate change it can be any number eg 2050, 2100
cmd_norm:: "CMD" climate moisture deficit for the historical normal period
cmd_fut:: "CMD_2050" climate moisture deficit for the future under climate change it can be any number eg 2050, 2100
ccei:: "CCEI" Climate Change Exposure Index from NatureServe website
map:: "MAP" mean annual precipitation for the historical normal period
mwmt:: "MWMT" mean warmest month temperature for the historical normal period
mcmt:: "MCMT" mean coldest month temperature for the historical normal period
clim_poly:: An optional shapefile with a polygon of the range of the climate data. It will be created from the climate data if it is missing but it is faster to provide it.

Accepted raster file types are ".asc", ".tif", ".nc", ".grd", ".img", ".bil" and ".gpkg" (see spatial_file_raster()).

Examples

in_folder <- system.file("extdata/clim_files/raw", package = "ccviR")
pth_out <- fs::dir_create("processed_temp")

# Process both scenarios at once with the same set of breaks

prep_clim_data_multi(
  mat_norm = file.path(in_folder, "NB_norm_MAT.tif"),
  mat_fut = file.path(in_folder, c("NB_RCP.4.5_MAT.tif", "NB_RCP.8.5_MAT.tif")),
  cmd_norm = file.path(in_folder, "NB_norm_CMD.tif"),
  cmd_fut = file.path(in_folder, c("NB_RCP.4.5_CMD.tif", "NB_RCP.8.5_CMD.tif")),
  map = file.path(in_folder, "NB_norm_MAP.tif"),
  mwmt = file.path(in_folder, "NB_norm_MWMT.tif"),
  mcmt = file.path(in_folder, "NB_norm_MCMT.tif"),
  out_folder = pth_out,
  clim_poly = file.path(system.file("extdata", package = "ccviR"),
                        "assess_poly.shp"),
  scenario_name = c("RCP 4.5", "RCP 8.5"))
#> Preparing Scenario 1
#> Processing MAT
#> Processing CMD
#> Processing MAP
#> Processing MWMT and MCMT
#> Finished processing
#> Preparing Scenario 2
#> Processing MAT
#> Processing CMD
#> Finished processing
#> $brks_cmd
#>         [,1]    [,2] [,3]
#> [1,] -20.750 -13.970    6
#> [2,] -13.970 -12.175    5
#> [3,] -12.175 -10.380    4
#> [4,] -10.380  -8.585    3
#> [5,]  -8.585  -6.790    2
#> [6,]  -6.790   2.140    1
#> 
#> $brks_mat
#>        [,1]   [,2] [,3]
#> [1,] -4.105 -3.130    6
#> [2,] -3.130 -3.050    5
#> [3,] -3.050 -2.970    4
#> [4,] -2.970 -2.890    3
#> [5,] -2.890 -2.810    2
#> [6,] -2.810 -1.556    1
#> 
#> $brks_ccei
#> NULL
#> 

# Clean up
fs::dir_delete(pth_out)


# Process both scenarios at with CCEI
pth_out <- fs::dir_create("processed_temp")

prep_clim_data_multi(
  mat_norm = file.path(in_folder, "NB_norm_MAT.tif"),
  mat_fut = file.path(in_folder, c("NB_RCP.4.5_MAT.tif", "NB_RCP.8.5_MAT.tif")),
  cmd_norm = file.path(in_folder, "NB_norm_CMD.tif"),
  cmd_fut = file.path(in_folder, c("NB_RCP.4.5_CMD.tif", "NB_RCP.8.5_CMD.tif")),
  ccei = file.path(in_folder, c("ccei_ssp245_fl.tif", "ccei_ssp585_fl.tif")),
  map = file.path(in_folder, "NB_norm_MAP.tif"),
  mwmt = file.path(in_folder, "NB_norm_MWMT.tif"),
  mcmt = file.path(in_folder, "NB_norm_MCMT.tif"),
  out_folder = pth_out,
  clim_poly = file.path(system.file("extdata", package = "ccviR"),
                        "assess_poly.shp"),
  scenario_name = c("RCP 4.5", "RCP 8.5"))
#> Preparing Scenario 1
#> Processing MAT
#> Processing CMD
#> Processing CCEI
#> Processing MAP
#> Processing MWMT and MCMT
#> Finished processing
#> Preparing Scenario 2
#> Processing MAT
#> Processing CMD
#> Processing CCEI
#> Finished processing
#> $brks_cmd
#>         [,1]    [,2] [,3]
#> [1,] -20.750 -13.970    6
#> [2,] -13.970 -12.175    5
#> [3,] -12.175 -10.380    4
#> [4,] -10.380  -8.585    3
#> [5,]  -8.585  -6.790    2
#> [6,]  -6.790   2.140    1
#> 
#> $brks_mat
#>        [,1]   [,2] [,3]
#> [1,] -4.105 -3.130    6
#> [2,] -3.130 -3.050    5
#> [3,] -3.050 -2.970    4
#> [4,] -2.970 -2.890    3
#> [5,] -2.890 -2.810    2
#> [6,] -2.810 -1.556    1
#> 
#> $brks_ccei
#>      [,1] [,2] [,3]
#> [1,]    0    4    1
#> [2,]    4    5    2
#> [3,]    5    7    3
#> [4,]    7  Inf    4
#> 

# Clean up
fs::dir_delete(pth_out)

Usage

Arguments

Value

Details

See also

Examples