I'm trying to convert grib files to NetCDF. The grib files contains subdata sets which are time related. Using the netcdfAll Java library with the NetCDF-4 C library works fine.
java -Xmx1g -classpath netcdfAll-4.5.jar ucar.nc2.dataset.NetcdfDataset -in ECM_DSD_2015021700_0000 -out ECM_DSD_2015021700_0000.nc -isLargeFile -netcdf4
The resulting NetCDF-4 file:
gdalinfo ECM_DSD_2015021700_0000.nc is listing all subdata sets like
Subdatasets:
SUBDATASET_1_NAME=HDF5:"ECM_DSD_2015021700_0000.nc"://GaussianLatLon_1280X2560-p07028S-179p9W/100_metre_U_wind_component_surface
SUBDATASET_1_DESC=[1x1280x2560] //GaussianLatLon_1280X2560-p07028S-179p9W/100_metre_U_wind_component_surface (32-bit floating-point)
SUBDATASET_2_NAME=HDF5:"ECM_DSD_2015021700_0000.nc"://GaussianLatLon_1280X2560-p07028S-179p9W/100_metre_V_wind_component_surface
SUBDATASET_2_DESC=[1x1280x2560] //GaussianLatLon_1280X2560-p07028S-179p9W/100_metre_V_wind_component_surface (32-bit floating-point)
The metatada of one subset shows an empty dimension list and a missing time dimension:
gdalinfo HDF5:"ECM_DSD_2015021700_0000.nc"://GaussianLatLon_1280X2560-p07028S-179p9/100_metre_U_wind_component_surface
Band 1 Block=2560x25 Type=Float32, ColorInterp=Undefined
Min=-25.970 Max=30.284
Minimum=-25.970, Maximum=30.284, Mean=0.493, StdDev=7.106
Metadata:
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface__Netcdf4Dimid=15
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_coordinates=time
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_DIMENSION_LIST=
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Center=98
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Level_Desc=Ground or water surface
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Level_Type=1
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Parameter=246
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Parameter_Name=100u
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_Subcenter=0
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib1_TableVersion=228
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_Grib_Variable_Id=VAR_98-0-228-246_L1
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_long_name=100 metre U wind component @ Ground or water surface
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_missing_value=1.#QNAN
GaussianLatLon_1280X2560-p07028S-179p9W_100_metre_U_wind_component_surface_units=m s**-1
STATISTICS_MAXIMUM=30.284362792969
STATISTICS_MEAN=0.49316239946346
STATISTICS_MINIMUM=-25.969543457031
STATISTICS_STDDEV=7.1061257055032
So what is the trick to convert the data with the time dimension? I found some python scripts[1] and the ncks tool[2], need I switch to one of them?
After I want to convert each subdataset to a single GeoTiff but this should be more easy when the time dimension was rescued once :-)
I am working with GDAL 1.11 and netcdfAll 4.5
[1] http://pysclint.sourceforge.net/pycdf/pycdf.html and https://readchunks.wordpress.com/ [2] http://linux.die.net/man/1/ncks