fldcor: Determine correlations in grid space.

Description Usage Arguments Value See Also Examples

View source: R/fldcor.R

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

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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.

See Also

Other correlation and covariance: fldcovar(), timcor(), timcovar()

Examples

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## 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 documentation built on Sept. 6, 2021, 9:09 a.m.

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