I have netCDF file obtained from here with name precip.mon.total.v6.nc. I am using ncdf package in R to open and analyse the file.
new <- open.ncdf("precip.mon.total.v6.nc")
> new
[1] "file precip.mon.total.v6.nc has 4 dimensions:"
[1] "lat Size: 360"
[1] "lon Size: 720"
[1] "nbnds Size: 2"
[1] "time Size: 1320"
[1] "------------------------"
[1] "file precip.mon.total.v6.nc has 1 variables:"
[1] "float precip[lon,lat,time] Longname:GPCC Monthly total of precipitation Missval:-9.96920996838687e+36"
But when I extract the variable, I got the error
> get.var.ncdf(new, "precip")
Error: cannot allocate vector of size 2.5 Gb
In addition: Warning messages:
1: In double(totvarsize) :
Reached total allocation of 2047Mb: see help(memory.size)
2: In double(totvarsize) :
Reached total allocation of 2047Mb: see help(memory.size)
3: In double(totvarsize) :
Reached total allocation of 2047Mb: see help(memory.size)
4: In double(totvarsize) :
Reached total allocation of 2047Mb: see help(memory.size)
My queries are: (a) How to handle memory issue? (b) How can I change the resolution of this netCDF file from 0.5*0.5 to 0.25*0.25 data? I have tried the similar problem in MATLAB. It can tackle memory issue better than R for netCDF files. But changing resolution is still a problem as I am not good at MATLAB. I will be very thankful for any help in this direction.
When you extract your variable, you need to specify which dimensions you want. Currently you're asking R to get everything and so I suspect it's creating a 3D array which will likely be enormous.
The ncdf4 package generally supersedes ncdf, you should try using that instead. You need to decide if you want to read data by location for time or by time step for location. This is easier to envisage on a plain 2D grid:
Yours is a 3D grid through time (albeit with the 3rd dimension only two bands), however it looks like your variable isn't using the bands dimension. Here's a 2D workflow based on ncdf4, ignoring your bands:
Package:
install.packages("ncdf4")
library(ncdf4)
Open connection:
nc = nc_open("~/dir/dir/file.nc")
For a grid at one time step
Read dimensions:
precip = list()
precip$x = ncvar_get(nc, "lon")
precip$y = ncvar_get(nc, "lat")
Read data (note start is the index in dimensions to begin and count is how many observations from that point, so here we read the whole grid at the first time step):
precip$z = ncvar_get(nc, "precip", start=c(1, 1, 1), count=c(-1, -1, 1))
# Convert to a raster if required
precip.r = raster(precip)
To read a single cell at all time steps
You need to find your cell index, precip$x and precip$y will help. Once you have it (e.g. cell x=5 and y=10):
precip.cell = ncvar_get(nc, "precip", start=c(5, 10, 1), count=c(1, 1, -1))