I need to work with these data in R: https://zenodo.org/records/1209296 in particular "irrigation water use v2.7z". I opened the netcdf inside R both with terra and raster library. I should have a lon lat grid over the world with 480 layers (months). But the format when I open them is the following.
class : RasterLayer
dimensions : 480, 64028, 30733440 (nrow, ncol, ncell)
resolution : 0.007481219, 1 (x, y)
extent : 0.9962594, 480.0037, 0.5, 480.5 (xmin, xmax, ymin, ymax)
crs : NA
source : withd_irr_h08.nc
names : withd_irr
zvar : withd_irr
How can I move to a raster with two dimension (lat, lon) and 480 layers? The resolution is 0.5°.
Your data is completely non-standard and not self-descriptive. In other words, no library will give you a one-stop solution.
With package ncdfCF I see the following file structure:
> library(ncdfCF)
> irr <- open_ncdf("~/withd_irr_h08.nc")
> irr
<Dataset> withd_irr_h08
Resource : withd_irr_h08.nc
Format : classic
Conventions: (not indicated)
Keep open : FALSE
Variables:
name units data_type axes
withd_irr mm/month NC_DOUBLE grid_num, month
lon degree NC_DOUBLE grid_num
lat degree NC_DOUBLE grid_num
Axes:
id axis name length values unit
1 T month 480 [1971-02-01 ... 2011-01-01] months since 1971-1
0 grid_num 64028 [1 ... 64028]
The data variable withd_irr does not use a longitude-latitude grid, instead it has an axis grid_num which holds 64,028 locations, same as the lon and lat variables (which you want to be axes if terra should recognise them, but they are not).
The solution to your problem is to extract the data for the 3 variables, put them in a data.frame, then convert that to a terra::SpatRaster. You will have to do the conversion for each month individually because the various steps are available for matrices but not for arrays:
# Read entire data arrays
> lon <- irr[["lon"]][]
> lat <- irr[["lat"]][]
> withd <- irr[["withd_irr"]][]
# Make a data.frame with lon, lat and all 480 months of withd_irr
> df <- data.frame(lon, lat, withd, check.names = FALSE)
# Convert a month of data to a SpatRaster
> r <- rast(df[c("lon", "lat", "1971-02-01")])
> r
class : SpatRaster
dimensions : 279, 720, 1 (nrow, ncol, nlyr)
resolution : 0.5, 0.5 (x, y)
extent : -180, 180, -56, 83.5 (xmin, xmax, ymin, ymax)
coord. ref. :
source(s) : memory
name : 1971-02-01
min value : 0.00000
max value : 96.28087
Putting it all together and making a single SpatRaster:
> library(ncdfCF)
> irr <- open_ncdf("~/withd_irr_h08.nc")
> lon <- irr[["lon"]][]
> lat <- irr[["lat"]][]
> withd <- irr[["withd_irr"]][]
> df <- data.frame(lon, lat, withd, check.names = FALSE)
> mon_str <- names(df)[-(1:2)] # drop lon, lat
# Build the SpatRaster structure from the first month
> r <- rast(df[c("lon", "lat", mon_str[1])])
# Now add the remaining months
> for (i in 2:length(mon_str)) add(r) <- rast(df[c("lon", "lat", mon_str[i])])
> r
class : SpatRaster
dimensions : 279, 720, 480 (nrow, ncol, nlyr)
resolution : 0.5, 0.5 (x, y)
extent : -180, 180, -56, 83.5 (xmin, xmax, ymin, ymax)
coord. ref. :
source(s) : memory
names : 1971-02-01, 1971-03-01, 1971-04-01, 1971-05-01, 1971-06-01, 1971-07-01, ...
min values : 0.00000, 0.0000, 0.0000, 0.0000, 0.0000, 0.000, ...
max values : 96.28087, 150.5525, 491.3734, 448.1106, 269.3665, 331.089, ...