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- Problem opening unstructured grid ocean forecasts with 4D vertical coordinates · 7 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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1078439763 | https://github.com/pydata/xarray/issues/2233#issuecomment-1078439763 | https://api.github.com/repos/pydata/xarray/issues/2233 | IC_kwDOAMm_X85AR69T | rsignell-usgs 1872600 | 2022-03-24T22:26:07Z | 2023-07-16T15:13:39Z | NONE | https://github.com/pydata/xarray/issues/2233#issuecomment-397602084 Would the new xarray index/coordinate internal refactoring now allow us to address this issue? cc @kthyng |
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
1171375793 | https://github.com/pydata/xarray/issues/2233#issuecomment-1171375793 | https://api.github.com/repos/pydata/xarray/issues/2233 | IC_kwDOAMm_X85F0cax | kthyng 3487237 | 2022-06-30T15:40:34Z | 2022-06-30T15:40:34Z | NONE | @benbovy Ah, I see you mean under "Relax all constraints related to “dimension (index) coordinates” in Xarray". Ok, thank you for clarifying that for me! (I wasn't sure what the second item meant in the list of lists.) |
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
1171342518 | https://github.com/pydata/xarray/issues/2233#issuecomment-1171342518 | https://api.github.com/repos/pydata/xarray/issues/2233 | IC_kwDOAMm_X85F0US2 | kthyng 3487237 | 2022-06-30T15:11:00Z | 2022-06-30T15:11:00Z | NONE | I've looked through the github issues associated with the explicit indices, but can't quite tell if I can use them to load FVCOM model output. In any case I just updated and tried without doing anything new and it didn't work:
Same error message as before:
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
1066784566 | https://github.com/pydata/xarray/issues/2233#issuecomment-1066784566 | https://api.github.com/repos/pydata/xarray/issues/2233 | IC_kwDOAMm_X84_ldc2 | iuryt 5797727 | 2022-03-14T13:27:00Z | 2022-03-14T13:30:24Z | NONE | Hi For now, I found a workaround loading and renaming the problematic coordinates with For now, you could try: ``` import xarray as xr from netCDF4 import Dataset define year and month to be readyear = 2019 month = 5 we could use this to run a loop through the years/months we needlist problematic coordinatesdrop_variables = ['siglay','siglev'] base url for openDAP serverurl = "".join(["http://www.smast.umassd.edu:8080/thredds/dodsC/models/fvcom/", f"NECOFS/Archive/NECOFS_GOM/{year}/gom4_{year}{month:02d}.nc?"]) lazy load of the datads = xr.open_dataset(url,drop_variables=drop_variables,decode_times=False) load data with netCDF4nc = Dataset(url) load the problematic coordinatescoords = {name:nc[name] for name in drop_variables} function to extract ncattrs from
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
641410484 | https://github.com/pydata/xarray/issues/2233#issuecomment-641410484 | https://api.github.com/repos/pydata/xarray/issues/2233 | MDEyOklzc3VlQ29tbWVudDY0MTQxMDQ4NA== | angelra 6598749 | 2020-06-09T16:18:21Z | 2020-06-09T16:18:21Z | NONE | I had to go around this issue and not use xarray but pandas instead or plain netdcf4 nc = netCDF4.Dataset(input_file) h = nc.variables[vname] times = nc.variables['time'] jd = netCDF4.num2date(times[:],times.units) hs = pd.Series(h[:,station],index=jd) I would love to know if there is a way to do it over xarray since it is so nice to use. Best regards |
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
629248902 | https://github.com/pydata/xarray/issues/2233#issuecomment-629248902 | https://api.github.com/repos/pydata/xarray/issues/2233 | MDEyOklzc3VlQ29tbWVudDYyOTI0ODkwMg== | stale[bot] 26384082 | 2020-05-15T13:53:58Z | 2020-05-15T13:53:58Z | NONE | In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity If this issue remains relevant, please comment here or remove the |
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 | |
397596002 | https://github.com/pydata/xarray/issues/2233#issuecomment-397596002 | https://api.github.com/repos/pydata/xarray/issues/2233 | MDEyOklzc3VlQ29tbWVudDM5NzU5NjAwMg== | rsignell-usgs 1872600 | 2018-06-15T11:44:35Z | 2018-06-15T11:44:35Z | NONE | @rabernat , this unstructured grid model output follows the UGRID Conventions, which layer on top of the CF Conventions. The issue Xarray is having here is with the vertical coordinate however, so this issue could arise with any CF convention model where the vertical stretching function varies over the domain. As requested, here is the ncdump of this URL: ``` jovyan@jupyter-rsignell-2dusgs:~$ ncdump -h http://www.smast.umassd.edu:8080/thredds/dodsC/FVCOM/NECOFS/Forecasts/NECOFS_GOM3_FORECAST.nc netcdf NECOFS_GOM3_FORECAST { dimensions: time = UNLIMITED ; // (145 currently) maxStrlen64 = 64 ; nele = 99137 ; node = 53087 ; siglay = 40 ; three = 3 ; variables: float lon(node) ; lon:long_name = "nodal longitude" ; lon:standard_name = "longitude" ; lon:units = "degrees_east" ; float lat(node) ; lat:long_name = "nodal latitude" ; lat:standard_name = "latitude" ; lat:units = "degrees_north" ; float xc(nele) ; xc:long_name = "zonal x-coordinate" ; xc:units = "meters" ; float yc(nele) ; yc:long_name = "zonal y-coordinate" ; yc:units = "meters" ; float lonc(nele) ; lonc:long_name = "zonal longitude" ; lonc:standard_name = "longitude" ; lonc:units = "degrees_east" ; float latc(nele) ; latc:long_name = "zonal latitude" ; latc:standard_name = "latitude" ; latc:units = "degrees_north" ; float siglay(siglay, node) ; siglay:long_name = "Sigma Layers" ; siglay:standard_name = "ocean_sigma_coordinate" ; siglay:positive = "up" ; siglay:valid_min = -1. ; siglay:valid_max = 0. ; siglay:formula_terms = "sigma: siglay eta: zeta depth: h" ; float h(node) ; h:long_name = "Bathymetry" ; h:standard_name = "sea_floor_depth_below_geoid" ; h:units = "m" ; h:coordinates = "lat lon" ; h:type = "data" ; h:mesh = "fvcom_mesh" ; h:location = "node" ; int nv(three, nele) ; nv:long_name = "nodes surrounding element" ; nv:cf_role = "face_node_connnectivity" ; nv:start_index = 1 ; float time(time) ; time:long_name = "time" ; time:units = "days since 1858-11-17 00:00:00" ; time:format = "modified julian day (MJD)" ; time:time_zone = "UTC" ; time:standard_name = "time" ; float zeta(time, node) ; zeta:long_name = "Water Surface Elevation" ; zeta:units = "meters" ; zeta:standard_name = "sea_surface_height_above_geoid" ; zeta:coordinates = "time lat lon" ; zeta:type = "data" ; zeta:missing_value = -999. ; zeta:field = "elev, scalar" ; zeta:coverage_content_type = "modelResult" ; zeta:mesh = "fvcom_mesh" ; zeta:location = "node" ; int nbe(three, nele) ; nbe:long_name = "elements surrounding each element" ; float u(time, siglay, nele) ; u:long_name = "Eastward Water Velocity" ; u:units = "meters s-1" ; u:type = "data" ; u:missing_value = -999. ; u:field = "ua, scalar" ; u:coverage_content_type = "modelResult" ; u:standard_name = "eastward_sea_water_velocity" ; u:coordinates = "time siglay latc lonc" ; u:mesh = "fvcom_mesh" ; u:location = "face" ; float v(time, siglay, nele) ; v:long_name = "Northward Water Velocity" ; v:units = "meters s-1" ; v:type = "data" ; v:missing_value = -999. ; v:field = "va, scalar" ; v:coverage_content_type = "modelResult" ; v:standard_name = "northward_sea_water_velocity" ; v:coordinates = "time siglay latc lonc" ; v:mesh = "fvcom_mesh" ; v:location = "face" ; float ww(time, siglay, nele) ; ww:long_name = "Upward Water Velocity" ; ww:units = "meters s-1" ; ww:type = "data" ; ww:coverage_content_type = "modelResult" ; ww:standard_name = "upward_sea_water_velocity" ; ww:coordinates = "time siglay latc lonc" ; ww:mesh = "fvcom_mesh" ; ww:location = "face" ; float ua(time, nele) ; ua:long_name = "Vertically Averaged x-velocity" ; ua:units = "meters s-1" ; ua:type = "data" ; ua:missing_value = -999. ; ua:field = "ua, scalar" ; ua:coverage_content_type = "modelResult" ; ua:standard_name = "barotropic_eastward_sea_water_velocity" ; ua:coordinates = "time latc lonc" ; ua:mesh = "fvcom_mesh" ; ua:location = "face" ; float va(time, nele) ; va:long_name = "Vertically Averaged y-velocity" ; va:units = "meters s-1" ; va:type = "data" ; va:missing_value = -999. ; va:field = "va, scalar" ; va:coverage_content_type = "modelResult" ; va:standard_name = "barotropic_northward_sea_water_velocity" ; va:coordinates = "time latc lonc" ; va:mesh = "fvcom_mesh" ; va:location = "face" ; float temp(time, siglay, node) ; temp:long_name = "temperature" ; temp:standard_name = "sea_water_potential_temperature" ; temp:units = "degrees_C" ; temp:coordinates = "time siglay lat lon" ; temp:type = "data" ; temp:coverage_content_type = "modelResult" ; temp:mesh = "fvcom_mesh" ; temp:location = "node" ; float salinity(time, siglay, node) ; salinity:long_name = "salinity" ; salinity:standard_name = "sea_water_salinity" ; salinity:units = "0.001" ; salinity:coordinates = "time siglay lat lon" ; salinity:type = "data" ; salinity:coverage_content_type = "modelResult" ; salinity:mesh = "fvcom_mesh" ; salinity:location = "node" ; int fvcom_mesh ; fvcom_mesh:cf_role = "mesh_topology" ; fvcom_mesh:topology_dimension = 2 ; fvcom_mesh:node_coordinates = "lon lat" ; fvcom_mesh:face_coordinates = "lonc latc" ; fvcom_mesh:face_node_connectivity = "nv" ; // global attributes: :title = "NECOFS GOM3 (FVCOM) - Northeast US - Latest Forecast" ; :institution = "School for Marine Science and Technology" ; :source = "FVCOM_3.0" ; :Conventions = "CF-1.0, UGRID-1.0" ; :summary = "Latest forecast from the FVCOM Northeast Coastal Ocean Forecast System using an newer, higher-resolution GOM3 mesh (GOM2 was the preceding mesh)" ; ``` |
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Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780 |
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