I have a netcdf file that has the dimensions of lat, lon, time and effect. The file also have 3 different variables: rn, prec and tair.

I want to read the file using terra, but I get unexpected results when I do so:

# store the url where the netcdf data is hosted
url = "https://github.com/qquusshh/data_so/raw/main/data.nc"

# download the netcdf data in the current directory with the name "data.nc"
download.file(url, "data.nc")

# read the file
terra::rast("data.nc")

output:

class       : SpatRaster 
dimensions  : 360, 3, 2160  (nrow, ncol, nlyr)
resolution  : 1, 1  (x, y)
extent      : -0.5, 2.5, -180, 180  (xmin, xmax, ymin, ymax)
coord. ref. :  
sources     : data.nc:rn  (720 layers) 
              data.nc:prec  (720 layers) 
              data.nc:tair  (720 layers) 
varnames    : rn 
              prec 
              tair 
names       : rn_ef~9.5_1, rn_ef~8.5_1, rn_ef~7.5_1, rn_ef~6.5_1, rn_ef~5.5_1, rn_ef~4.5_1, ... 

I would expect the nrow to be lat (180), ncol to be lon (360), nlyr to be time (3) and somehow another dimension containing the effect.

When I use xarray from python, everything works perfectly:

# import the xarray library
import xarray as xr

# open the data
xr.open_dataset("data.nc")

output:

<xarray.Dataset>
Dimensions:  (lat: 180, lon: 360, time: 3, effect: 4)
Coordinates:
  * lat      (lat) float32 89.5 88.5 87.5 86.5 85.5 ... -86.5 -87.5 -88.5 -89.5
  * lon      (lon) float64 -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5
  * time     (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31
  * effect   (effect) object 'inst' 'short' 'long' 'static'
Data variables:
    rn       (effect, lat, lon, time) float64 ...
    prec     (effect, lat, lon, time) float64 ...
    tair     (effect, lat, lon, time) float64 ...