Compute seasonal climate data spatial probability distributions.

clim_dist_seasonal(in_dir = snapdef()$ar5dir_dist_monthly,
  out_dir = snapdef()$ar5dir_dist_seasonal, variable, rcp,
  density.args = list(n = 200, adjust = 0.1), mc.cores = 32)

Arguments

in_dir

input directory, e.g., snapdef()$ar5dir_dist_monthly.

out_dir

output directory, e.g., snapdef()$ar5dir_dist_seasonal

variable

character, optional, to split into smaller file batches. See details.

rcp

character, optional, to split into smaller file batches. See details.

density.args

arguments list passed to density.

mc.cores

number of CPUs when processing years in parallel. Defaults to 32 assuming Atlas compute node context.

Details

Seasons are DJF, MAM, JJA and SON 3-month averages. A fifth "season" of full annual averages is also included. For efficiency, this function operates on outputs from clim_dist_monthly. It does not need to redundantly access source downscaled geotiffs.

Use variable to optionally specify a climate variable file identifier: "pr", "tas", "tasmin" or "tasmax". This will be used for pattern matching when listing files inside in_dir. Similarly, use rcp to process a smaller batch. These are helpful when there are many files, such that there could be RAM or time limitations.

Examples

# NOT RUN {
clim_dist_seasonal() # all variables
clim_dist_seasonal(variable = "pr") # precipitation
clim_dist_seasonal(variable = "pr", rcp = "rcp60") # precipitation and RCP 6.0
# }