NetCDF Variable Naming: File Name vs. Metadata Name (NETCDF_VARNAME) Inconsistency

[alexyshr]

When reading a NetCDF file that contains only one variable, the variable in the stars object is automatically named after the file itself. However, the actual name of the variable in the metadata is different—for example, NETCDF_VARNAME=tp.

Wouldn't it be more accurate or helpful if the default variable name used matched the actual metadata-defined variable name (tp in this case), rather than defaulting to the file name?

Also, when I use gdal_utils(util = "info", ...), the output is extremely long. Is this expected behavior (e.g., due to the structure of my file), or could this be an issue in how the metadata is being parsed or displayed?

If the URL in the reprex doen't work, please download the file idalia_2024_accum.nc from here
https://drive.google.com/file/d/1A6cK-TDGalR8DC-6_WVL_zHU6_XR0fio/view?usp=sharing

or here
https://github.com/alexyshr/sof

myurl <- "https://geocorp.co/wind/idalia_2024_accum.nc"
filename <- "idalia_2024_accum.nc"
download.file(myurl, filename, mode = "wb")
library(stars)
#> Loading required package: abind
#> Loading required package: sf
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE
gdalinfo_a <- gdal_utils(util = "info", "idalia_2024_accum.nc")
#> Driver: netCDF/Network Common Data Format
#> Files: idalia_2024_accum.nc
#> Size is 35, 29
#> Origin = (-88.125000000000000,31.625000000000000)
#> Pixel Size = (0.250000000000000,-0.250000000000000)
#> Metadata:
..
#>     long_name=Total precipitation
#>     NETCDF_DIM_valid_time=1690848000
#>     NETCDF_VARNAME=tp
#>     standard_name=unknown
#>     units=m
..
long_name=Total precipitation\n    NETCDF_DIM_valid_time=1696114800\n    NETCDF_VARNAME=tp\n    standard_name=unknown\n    units=m\n    _FillValue=nan\n"
a <- read_stars("idalia_2024_accum.nc")
a
#> stars object with 3 dimensions and 1 attribute
#> attribute(s), summary of first 1e+05 cells:
#>                          Min. 1st Qu.       Median         Mean      3rd Qu.
#> idalia_2024_accum.nc [m]    0       0 4.768372e-07 8.301466e-05 2.002716e-05
#>                                Max.
#> idalia_2024_accum.nc [m] 0.02074099
#> dimension(s):
#>            from   to                               offset
#> x             1   35                               -88.12
#> y             1   29                                31.62
#> valid_time    1 1464 1.691e+09 [seconds since 1970-01-01]
#>                                      delta x/y
#> x                                     0.25 [x]
#> y                                    -0.25 [y]
#> valid_time 3600 [seconds since 1970-01-01]

^{Created on 2025-04-12 with reprex v2.1.1}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.3 (2025-02-28 ucrt)
#>  os       Windows 10 x64 (build 19045)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  English_United States.utf8
#>  ctype    English_United States.utf8
#>  tz       America/New_York
#>  date     2025-04-12
#>  pandoc   3.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version date (UTC) lib source
#>  abind       * 1.4-8   2024-09-12 [1] CRAN (R 4.4.1)
#>  class         7.3-23  2025-01-01 [1] CRAN (R 4.4.2)
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#> ──────────────────────────────────────────────────────────────────────────────

[edzer]

Have you tried read_mdim()?

library(stars)
# Loading required package: abind
# Loading required package: sf
# Linking to GEOS 3.12.2, GDAL 3.9.3, PROJ 9.4.1; sf_use_s2() is TRUE
filename <- "idalia_2024_accum.nc"
(a <- read_mdim("idalia_2024_accum.nc"))
# stars object with 3 dimensions and 1 attribute
# attribute(s), summary of first 1e+05 cells:
#        Min. 1st Qu.       Median         Mean      3rd Qu.       Max.
# tp [m]    0       0 4.768372e-07 8.301466e-05 2.002716e-05 0.02074099
# dimension(s):
#            from   to         offset   delta         refsys x/y
# longitude     1   35         -88.12    0.25 WGS 84 (CRS84) [x]
# latitude      1   29          31.62   -0.25 WGS 84 (CRS84) [y]
# valid_time    1 1464 2023-08-01 UTC 1 hours        POSIXct    

[edzer]

or read_stars(filename) |> setNames("tp")

[alexyshr]

Since I am reading multiple files in a loop, I use read_mdim to avoid writing customized code for each file or variable name. The program expects all the files to have the same unknown attribute.

[edzer]

close?

[alexyshr]

Thank you. Yes! Have a good day!

…

On Sat, 3 May 2025, 9:48 am Edzer Pebesma, ***@***.***> wrote: *edzer* left a comment (r-spatial/stars#744) <#744 (comment)> close? — Reply to this email directly, view it on GitHub <#744 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AGMIQHLYSW2HFJZCL7ER3T324TCJNAVCNFSM6AAAAAB3AMF2R2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDQNBYGYZTMMJSG4> . You are receiving this because you authored the thread.Message ID: ***@***.***>