R stack raster data through time dimension

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I would like to know how can I stack different raster datasets through time dimension in R.

Concretely:

I have a set of ncdf files that contain rain data per month. I want to merge these datasets through the time dimension so that I have a unique dataset but with time dimension. To do so I stacked these datasets so my nlayers are different periods of time. I would like to pass this nlayers to the time dimension, so if now I have 3 nlayers, I would like to have 3 periods of time.

   nc0298<- stack("3a12.19980201.7.nc", varname="sfcr")  #Rain in 02/1998
   nc0398<- stack("3a12.19980301.7.nc", varname="sfcr")  #Rain in 03/1998
   nc0498<- stack("3a12.19980401.7.nc", varname="sfcr")

  data <- raster::stack(nc0298, nc0398, nc0498)
  print(data)

Output: class : RasterStack dimensions : 22, 27, 594, 3 (nrow, ncol, ncell, nlayers) resolution : 0.5, 0.5 (x, y) extent : 2, 15.5, 3.5, 14.5 (xmin, xmax, ymin, ymax) coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 names : surface.rain..mm.hr..1, surface.rain..mm.hr..2, surface.rain..mm.hr..3

But instead of having it in nlayers I would like to have in time dimension: data@layers

Output: 3 dimensions: time Size:1 * is unlimited * units: hours since 1998-4-1 0 longitude Size:27 units: degrees_east long_name: Longitude latitude Size:22 units: degrees_north long_name: Latitude

here we can see that my time dimension is still size 1.

I have both conceptual problems and code ones, so any suggestion explanation will help.

The data files can be obtained at: link

Many thanks,

PD: I am an student of economics so I am an ignorant in spatial analysis and geography. I have intermediate knowledge in R but also in Matlab and Python. If someone have an answer for these programs it could also help me.

this is my first question in a community so sorry for my mistakes.

dimension raster stack r time
1 Answers

The link to your data files is dead unfortunately, so I can not test it myself, but one solution using Python could be:

from netCDF4 import MFDataset
import glob

ncfiles = glob.glob('*.nc', recursive=True)
data = MFDataset(ncfiles, aggdim='time')

With the aggdim argument set to your time variable it should create the additional dimension that you are looking for. globis simply useful for reading multiple ncdf files in a folder, make sure to set it to the directory where your files are located.

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