Learn R Programming

cmsaf (version 1.9.5)

mon.anomaly: Determine monthly anomalies.

Description

The function subtracts from a each timestep of a timeseries the corresponding multi-year monthly mean. To get monthly anomalies, the input file should contain monthly mean values.

Usage

mon.anomaly(var, infile, outfile, nc34)

Arguments

var

Name of NetCDF variable (character).

infile

Filename of 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=4 the output file will be in NetCDFv4 format (numeric). Default output is NetCDFv3.

Value

A NetCDF file including a timeseries of differences is written.

Examples

Run this code
# NOT RUN {
## Create an example NetCDF file with a similar structure
## as used by CM SAF. The file is 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 <- seq(as.Date('2000-01-01'), as.Date('2010-12-31'), 'month')
  origin <- as.Date('1983-01-01 00:00:00')
  time <- as.numeric(difftime(time,origin,units='hour'))
  data <- array(250:350,dim=c(21,21,132))

## 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),-1,prec='short')
   vars <- list(var1)
   ncnew <- nc_create('CMSAF_example_file.nc',vars)
   ncvar_put(ncnew,var1,data)
   ncatt_put(ncnew,'lon','standard_name','longitude',prec='text')
   ncatt_put(ncnew,'lat','standard_name','latitude',prec='text')
   nc_close(ncnew)

## Determine the monthly anomalies of the example CM SAF NetCDF file 
## and write the output to a new file.
   mon.anomaly('SIS','CMSAF_example_file.nc', 
   'CMSAF_example_file_mon.anomaly.nc')
# }

Run the code above in your browser using DataLab