Comments (13)
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Just to add to this... The following maps should show the same (I created some monthly mean data with cdo):
The units are unfortunately not the same, but even the patterns look different. The files look OK. Very weird.
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Maybe it's just a fluke with lustre and if we ran the experiment again it might work?
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Processing model maps for IFS-ESUITE (concpm10)
Searching database for ECMWF_ESUITE
/lustre/storeB/project/aerocom/aerocom-users-database/ECMWF/ECMWF_ESUITE has subdir renamed. Using that one
Found match for ID ECMWF_ESUITE
Did not find concpm10 field but sconcpm10. Using the latter instead
Invalid time dimension coordinate in file:
/lustre/storeB/project/aerocom/aerocom-users-database/ECMWF/ECMWF_ESUITE/renamed/aerocom3_ECMWF_ESUITE_sconcpm10_Surface_2022_daily.nc.
Error: repr(Cube does not contain time dimension)
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But this is from all comps, ie.:
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Yes, just making notes to myself. This is typical although look suspicious at first glance
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Iris cube after rearranging longitude coords to [180, 180) seems fine
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the iris cube before being written to geojson. Between pyaerocom/io/iris_io.py(208)check_and_regrid_lons_cube()
and pyaerocom/aeroval/modelmaps_engine.py(158)_process_map_var() the problem occurs
Trackback...
(Pdb) traceback.print_stack()
File "/lustre/storeB/users/lewisb/Python/Evaluations/aeroval/config/config_files/cfg_fix_864.py", line 428, in <module>
res = ana.run()
File "/lustre/storeB/users/lewisb/Python/Evaluations/pyaerocom/pyaerocom/aeroval/experiment_processor.py", line 130, in run
engine.run(model_list=model_list, var_list=var_list)
File "/lustre/storeB/users/lewisb/Python/Evaluations/pyaerocom/pyaerocom/aeroval/modelmaps_engine.py", line 45, in run
files = self._run_model(model, var_list)
File "/lustre/storeB/users/lewisb/Python/Evaluations/pyaerocom/pyaerocom/aeroval/modelmaps_engine.py", line 85, in _run_model
_files = self._process_map_var(model_name, var, self.reanalyse_existing)
File "/lustre/storeB/users/lewisb/Python/Evaluations/pyaerocom/pyaerocom/aeroval/modelmaps_engine.py", line 158, in _process_map_var
contourjson = calc_contour_json(data, cmap=varinfo.cmap, cmap_bins=varinfo.cmap_bins)
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iris cube before being put into GriddedData
object. Still looks okay
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After becoming a GriddedData
object it gets messed up.
pyaerocom/io/readgridded.py line 2123.
data = GriddedData(
input=cube,
from_files=from_files,
data_id=self.data_id,
concatenated=is_concat,
convert_unit_on_init=try_convert_units,
**meta,
)
There are unit conversions occurring so look into that
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Before calling iris.grid.convert_units():
After calling iris.grid.convert_units():
Happens in pyaerocom/gridded_data.py::convert_unit() line 849. Seems like the issue is with iris
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BTW, in pyaerocom/io/iris_io.py line 535 has cube.attributes["timedim-corrected"] = True
which is technically wrong because netcdf can't have boolean attributes when saving an iris cube.
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Using iris 3.5.0 pyhd8ed1ab_0 conda-forge. Iris 3.5.0 was released April 27th. 3.4.1 was released Feb 21
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Related Issues (20)
- In pyaeroval_config.py: regrid_res_deg is expected to be a float (not a dictionary)
- EBAS reader: Handle time step sizes that differ over the provided time series HOT 2
- Testdata minimal should be user-specific
- EBAS reader: open sqlite3 db in read-only mode only
- illogical signatures and input tests in mscw/addtional-variables HOT 1
- Update caching strategy for ungridded data HOT 3
- Mandatory data_revision on all obs-readers, disable last-file check in caching
- DataCoverageError when running pyaeroval ana.run with var_list and multiple obs-setups
- MSCW-reader reads in trends of all available year rather than only years selected with periods HOT 1
- add_maps tries to read min-maximum from model even if min-max is configured in glob_defaults.py
- Rename coarse to pm10 and fine to pm25 HOT 1
- pyaeroval: splitting of pyaerocom/aeroval and pyaerocom HOT 2
- Define ranges by frequency in var_scale_colmap
- Incorrect map frequencies: ModelMapsSetup's maps_freq is not being picked up in ModelMapsEngine::_process_map_var
- Model maps shown for EMEP should use the frequency of the Base_*.nc file rather than the colocated data and then resampling HOT 2
- MDA8 calculation for single year results in ts of two years
- MDA8 daily values have wrong timestamp
- MDA8 values not shown on Overall Evaluation HOT 3
- pyaerocom/aeroval output should use aerovaldb-locking for all output
- Milestones are removed when issues are added from the AeroTools/Backlog HOT 2
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