cmsafops: fldcor – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

fldcor

Determine correlations in grid space.

Description

The function determines correlations in grid space from data of two CM SAF NetCDF input files. This function is applicable to 3-dimensional NetCDF data.

Usage

fldcor(
  var1,
  infile1,
  var2,
  infile2,
  outfile,
  nc34 = 4,
  overwrite = FALSE,
  verbose = FALSE
)

Arguments

`var1`	Name of NetCDF variable of the first data set (character).
`infile1`	Filename of first input NetCDF file. This may include the directory (character).
`var2`	Name of NetCDF variable of the second data set (character).
`infile2`	Filename of second input NetCDF file. This may include the directory (character).
`outfile`	Filename of output NetCDF file. This may include the directory (character).
`nc34`	NetCDF version of output file. If `nc34 = 3` the output file will be in NetCDFv3 format (numeric). Default output is NetCDFv4.
`overwrite`	logical; should existing output file be overwritten?
`verbose`	logical; if TRUE, progress messages are shown

Value

A NetCDF file including a time series of correlations in grid space is written.

Examples

## Create two example NetCDF files with a similar structure as used by CM
## SAF. The files are created with the ncdf4 package.  Alternatively
## example data can be freely downloaded here: <https://wui.cmsaf.eu/>

library(ncdf4)

## create some (non-realistic) example data
lon <- seq(5, 15, 0.5)
lat <- seq(45, 55, 0.5)
time <- as.Date("2000-05-31")
origin <- as.Date("1983-01-01 00:00:00")
time <- as.numeric(difftime(time, origin, units = "hour"))
data1 <- array(250:350, dim = c(21, 21, 1))
data2 <- array(230:320, dim = c(21, 21, 1))

## create example NetCDF
x <- ncdim_def(name = "lon", units = "degrees_east", vals = lon)
y <- ncdim_def(name = "lat", units = "degrees_north", vals = lat)
t <- ncdim_def(name = "time", units = "hours since 1983-01-01 00:00:00",
             vals = time, unlim = TRUE)
var1 <- ncvar_def("SIS", "W m-2", list(x, y, t), -999, prec = "float")
vars <- list(var1)
ncnew_1 <- nc_create(file.path(tempdir(), "CMSAF_example_file_1.nc"), vars)
ncnew_2 <- nc_create(file.path(tempdir(), "CMSAF_example_file_2.nc"), vars)

ncvar_put(ncnew_1, var1, data1)
ncvar_put(ncnew_2, var1, data2)

ncatt_put(ncnew_1, "lon", "standard_name", "longitude", prec = "text")
ncatt_put(ncnew_1, "lat", "standard_name", "latitude", prec = "text")

ncatt_put(ncnew_2, "lon", "standard_name", "longitude", prec = "text")
ncatt_put(ncnew_2, "lat", "standard_name", "latitude", prec = "text")
nc_close(ncnew_1)
nc_close(ncnew_2)

## Determine the correlations in grid space of the example CM SAF NetCDF files and
## write the output to a new file.
fldcor(var1 = "SIS", infile1 = file.path(tempdir(),"CMSAF_example_file_1.nc"), 
      var2 = "SIS", infile2 = file.path(tempdir(), "CMSAF_example_file_2.nc"),
      outfile = file.path(tempdir(),"CMSAF_example_file_fldcor.nc"))

unlink(c(file.path(tempdir(),"CMSAF_example_file_1.nc"), 
      file.path(tempdir(),"CMSAF_example_file_2.nc"),
      file.path(tempdir(),"CMSAF_example_file_fldcor.nc")))

cmsafops

Tools for CM SAF NetCDF Data

v1.1.1

GPL (>= 3)

Authors

Steffen Kothe [aut, cre]

Initial release