fpPrep: Process netCDF4 Gridded Data into Format of the fingerprint()...

In LiYanStat/fingerprinting: Detection and Attribution Analysis of Climate Change

Process netCDF4 Gridded Data into Format of the fingerprint() Function

Description

This function detects the signal factors on the observed data via total least square linear regression model.

Usage

fpPrep(
  datafile,
  variable,
  region = "GL",
  target.year,
  average = 5,
  reference = c(1961, 1990),
  regridding = NULL
)

Arguments

datafile	path to the netCDF4 gridded datafile to be processed
variable	the climate variable to be extracted
region	the longitude and latitude boundary for selected region, should match the format of IPCC AR6 regions, the lon and lat of the vertices
target.year	vector of length 2, the starting and ending year of the selected time period for D&A analysis
average	number of years for average on each gridbox, default is 5-year average
reference	vector of length 2, the starting and ending year of reference time period for computing anomalies
regridding	whether the grid box should be regridded. Specify the size of the grid box, e.g., c(40, 30) for 40^\circ \times 30^\circ grid box. If no regridding, leave empty

Value

a dataset of the processed gridded climate variables for Y, Xtilde or control runs

Author(s)

Yan Li

LiYanStat/fingerprinting documentation built on June 12, 2025, 4:44 a.m.