This function summarizes GCM data by calculating various statistics for each variable.
Usage
summary_gcms(s, var_names = c("bio_1", "bio_12"), study_area = NULL)Arguments
- s
A list of stacks of General Circulation Models (GCMs).
- var_names
Character. A vector of names of the variables to include, or 'all' to include all variables.
- study_area
An Extent object, or any object from which an Extent object can be extracted. Defines the study area for cropping and masking the rasters.
Examples
var_names <- c("bio_1", "bio_12")
s <- import_gcms(system.file("extdata", package = "chooseGCM"), var_names = var_names)[1:5]
study_area <- terra::ext(c(-80, -70, -50, -40)) |>
terra::vect(crs="+proj=longlat +datum=WGS84 +no_defs")
summary_gcms(s, var_names, study_area)
#> CRS from s and study_area are not identical. Reprojecting study area.
#> $ae
#> min quantile_0.25 median mean quantile_0.75 max
#> bio_1 7.734 9.8545 10.7390 10.23763 11.3395 11.543
#> bio_12 149.629 213.8605 367.1815 379.01250 536.2582 652.387
#> sd NAs n_cells
#> bio_1 1.554092 0 8
#> bio_12 194.889090 0 8
#>
#> $cc
#> min quantile_0.25 median mean quantile_0.75 max sd
#> bio_1 9.632 12.14625 13.336 12.7050 14.11125 14.298 1.901372
#> bio_12 157.307 233.37199 389.552 398.5404 542.65027 690.179 202.486461
#> NAs n_cells
#> bio_1 0 8
#> bio_12 0 8
#>
#> $ch
#> min quantile_0.25 median mean quantile_0.75 max
#> bio_1 9.519 11.50675 12.5290 11.91413 12.88625 13.052
#> bio_12 165.665 248.83649 418.8595 440.43950 585.03526 816.399
#> sd NAs n_cells
#> bio_1 1.424861 0 8
#> bio_12 240.108269 0 8
#>
#> $cr
#> min quantile_0.25 median mean quantile_0.75 max
#> bio_1 8.963 10.84175 11.8815 11.24463 12.1130 12.378
#> bio_12 158.755 233.62600 394.3315 417.01825 556.8452 766.791
#> sd NAs n_cells
#> bio_1 1.358478 0 8
#> bio_12 228.173183 0 8
#>
#> $ev
#> min quantile_0.25 median mean quantile_0.75 max
#> bio_1 9.135 11.1355 12.0870 11.43975 12.24975 12.520
#> bio_12 159.130 233.5620 413.5025 422.31275 592.57750 741.645
#> sd NAs n_cells
#> bio_1 1.371565 0 8
#> bio_12 222.794772 0 8
#>