Input data for the bivariate climate change plot

Input data for the plot_bivariate() function. Since these inputs are time-consuming to generate, the purpose of conducting the generation of the input table in a separate function is to allow users to make multiple calls to plot_bivariate() (e.g., for comparing different climate variables) without needing to generate the inputs each time.

Usage

plot_bivariate_input(
  xyz,
  obs_period = list_obs_periods()[1],
  gcms = list_gcms()[c(1, 4, 5, 6, 7, 10, 11, 12)],
  ssps = list_ssps()[2],
  gcm_periods = list_gcm_periods(),
  max_run = 10,
  vars = list_vars(),
  db_option = "auto"
)

Arguments

xyz

a terra::SpatRaster with a single layer containing elevation values in metres, or a data.frame with the following columns "long", "lat", "elev", and a unique "id". Any extra columns will be ignored and not output.

gcms

character. Vector of global climate model names. Options are list_gcms().

ssps

character. Vector of SSP-RCP scenarios (representative concentration pathways paired with shared socioeconomic pathways). Options are list_ssps(). Defaults to all scenarios available.

gcm_periods

character. 20-year reference periods for GCM simulations. Options are list_gcm_periods().

max_run

integer. Maximum number of model runs to include, not including the ensemble mean. Runs are included in the order they are found in the models data until max_run is reached. Defaults to 0L.

vars

character. A vector of climate variables to compute. Supported variables can be obtained with list_vars(). Definitions can be found in this package variables dataset. Default to monthly PPT, Tmax, Tmin.

db_option

character. One of auto, database, or local. Default auto.

Value

data.table of downscaled climate variables for all locations.

Details

This function generates standardized inputs for one or multiple locations at any spatial scale.

Examples

if (FALSE) {
  # data frame of arbitrary points
  my_points <- data.frame(
    lon = c(-127.7300, -127.7500),
    lat = c(55.34114, 55.25),
    elev = c(711, 500),
    id = 1:2
  )

  # generate the input data
  my_data <- plot_bivariate_input(my_points)

  # use the input to create a plot
  plot_bivariate(my_data, xvar = "MAT", yvar = "PAS_an")
}
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