dist_gcms: Distance Between GCMs

Description

This function compares future climate projections from multiple General Circulation Models (GCMs) based on their similarity in terms of variables. It calculates distance metrics and plots the results on a heatmap.

Usage

dist_gcms(
  s,
  var_names = c("bio_1", "bio_12"),
  study_area = NULL,
  scale = TRUE,
  method = "euclidean"
)

Value

A list containing two items: distances (the calculated distances between GCMs) and heatmap (a plot displaying the heatmap).

Arguments

s: A list of stacks of General Circulation Models (GCMs).
var_names: Character. A vector of names of the variables to compare, 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.
scale: Logical. Whether to apply centering and scaling to the data. Default is TRUE.
method: Character. The correlation method to use. Default is "euclidean". Possible values are: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "pearson", "spearman", or "kendall".

Author

Luíz Fernando Esser (luizesser@gmail.com) https://luizfesser.wordpress.com

Examples

Run this code

var_names <- c("bio_1", "bio_12")
s <- import_gcms(system.file("extdata", package = "chooseGCM"), var_names = var_names)
study_area <- terra::ext(c(-80, -30, -50, 10)) |> terra::vect(crs="epsg:4326")
dist_gcms(s, var_names, study_area, method = "euclidean")