Extract data

extract_data() takes an epw_cmip6_coord object generated using match_coord() and extracts CMIP6 data using the coordinates and years of interest specified.

extract_data(
  coord,
  years = NULL,
  unit = FALSE,
  out_dir = NULL,
  by = NULL,
  keep = is.null(out_dir),
  compress = 100
)

Arguments

coord

An epw_cmip6_coord object created using match_coord()

years

An integer vector indicating the target years to be included in the data file. All other years will be excluded. If NULL, no subsetting on years will be performed. Default: NULL.

unit

If TRUE, units will be added to values using units::set_units().

out_dir

The directory to save extracted data using fst::write_fst(). If NULL, all data will be kept in memory by default. Default: NULL.

by

A character vector of variable names used to split data during extraction. Should be a subset of:

• "experiment": root experiment identifiers

• "source": model identifiers

• "variable": variable identifiers

• "activity": activity identifiers

• "frequency": sampling frequency

• "variant": variant label

• "resolution": approximate horizontal resolution

If NULL and out_dir is given, file name data.fst will be used. Default: NULL.

keep

Whether keep extracted data in memory. Default: TRUE if out_dir is NULL, and FALSE otherwise.

compress

A single integer in the range 0 to 100, indicating the amount of compression to use. Lower values mean larger file sizes. Default: 100.

Value

An epw_cmip6_data object, which is basically a list of 3 elements:

• epw: An eplusr::Epw object whose longitude and latitude are used to extract CMIP6 data. It is the same object as created in match_coord()

• meta: A list containing basic metadata of input EPW, including city, state_province, country, latitude and longitude.

• data: An empty data.table::data.table() if keep is FALSE or a data.table::data.table() of 14 columns if keep is TRUE:

  No.	Column	Type	Description
  1	activity_drs	Character	Activity DRS (Data Reference Syntax)
  2	institution_id	Character	Institution identifier
  3	source_id	Character	Model identifier
  4	experiment_id	Character	Root experiment identifier
  5	member_id	Character	A compound construction from sub_experiment_id and variant_label
  6	table_id	Character	Table identifier
  7	lon	Double	Longitude of extracted location
  8	lat	Double	Latitude of extracted location
  9	dist	Double	The spherical distance in km between EPW location and grid coordinates
  10	datetime	POSIXct	Datetime for the predicted value
  11	variable	Character	Variable identifier
  12	description	Character	Variable long name
  13	units	Character	Units of variable
  14	value	Double	The actual predicted value

Details

extract_data() supports common calendars, including 365_day and 360_day, thanks to the PCICt package.

extract_data() uses future.apply underneath. You can use your preferable future backend to speed up data extraction in parallel. By default, extract_data() uses future::sequential backend, which runs things in sequential.

Examples

if (FALSE) {
coord <- match_coord("path_to_an_EPW")
extract_data(coord, years = 2030:2060)
}