A data preparation tool for meteorological data in CEMC/CMA.
Load GRIB2 data using eccodes or cfgrib.
中文文档 (Chinese documentation): https://reki.readthedocs.io/
Install the latest release from pip:
pip install rekior download the latest source code from GitHub and install using pip.
The reki library includes built-in config files to locate data files in CMA-HPC2023-SC1 shared file system (/g3/COMMONDATA).
The codes below finds the GRIB2-ORIG file path for CMA-GFS:
>>> from reki.data_finder import find_local_file
>>> gfs_grib2_file_path = find_local_file(
... "cma_gfs_gmf/grib2/orig",
... start_time="2025081900",
... forecast_time="24h",
... )
>>> gfs_grib2_file_path
PosixPath('/g3/COMMONDATA/OPER/CEMC/GFS_GMF/Prod-grib/2025081900/ORIG/gmf.gra.2025081900024.grb2')The find_local_file function supports additional parameters for more specific file selection.
For instance, using number to indicate ensemble member:
>>> geps_grib2_file_path = find_local_file(
... "cma_geps/grib2/orig",
... start_time="2025081900",
... forecast_time="24h",
... number=2,
... )
>>> geps_grib2_file_path
PosixPath('/g3/COMMONDATA/OPER/CEMC/GEPS/Prod-grib/2025081900/grib2/gef.gra.002.2025081900024.grb2')reki also supports locating intermediate model output files. The example below find path of the 240-hour model-level binary data file for CMA-GFS:
>>> gfs_modelvar_file_path = find_local_file(
... "cma_gfs_gmf/bin/modelvar",
... start_time="2025081900",
... forecast_time="240h",
... )
>>> gfs_modelvar_file_path
PosixPath('/g3/COMMONDATA/OPER/CEMC/GFS_GMF/Fcst-long/2025081900/modelvar2025081900_240')Built-in configuration files are located in the reki/data_finder/conf directory.
Use eccodes to retrieve a field from a GRIB2 file and return an xarray.DataArray object.
This example loads the 850 hPa temperature field from a CMA-GFS GRIB2-ORIG data:
>>> from reki.format.grib import load_field_from_file
>>> field = load_field_from_file(
... gfs_grib2_file_path,
... parameter="t",
... level_type="pl",
... level=850,
... )
>>> field
<xarray.DataArray 't' (latitude: 1440, longitude: 2880)> Size: 33MB
array([[270.49505859, 270.50505859, 270.50505859, ..., 270.49505859,
270.49505859, 270.49505859],
[270.69505859, 270.70505859, 270.71505859, ..., 270.70505859,
270.70505859, 270.69505859],
[270.84505859, 270.85505859, 270.85505859, ..., 270.84505859,
270.84505859, 270.84505859],
...,
[247.60505859, 247.58505859, 247.74505859, ..., 247.62505859,
247.63505859, 247.61505859],
[247.26505859, 247.26505859, 247.25505859, ..., 247.25505859,
247.25505859, 247.25505859],
[246.84505859, 246.84505859, 246.84505859, ..., 246.85505859,
246.84505859, 246.84505859]], shape=(1440, 2880))
Coordinates:
time datetime64[ns] 8B 2025-08-19
step timedelta64[ns] 8B 1 days
valid_time datetime64[ns] 8B 2025-08-20
pl float64 8B 850.0
* latitude (latitude) float64 12kB 89.94 89.81 89.69 ... -89.81 -89.94
* longitude (longitude) float64 23kB 0.0 0.125 0.25 ... 359.6 359.8 359.9
Attributes: (12/17)
GRIB_edition: 2
GRIB_centre: babj
GRIB_subCentre: 0
GRIB_tablesVersion: 4
GRIB_localTablesVersion: 0
GRIB_dataType: fc
... ...
GRIB_stepType: instant
GRIB_stepUnits: 1
GRIB_stepRange: 24
GRIB_endStep:int: 24
GRIB_count: 109
long_name: discipline=0 parmcat=0 parm=0Quick plotting:
>>> (field - 273.15).plot()Load variables from model-level data.
The example below loads the u-component at model level 10 (ml) from CMA-GFS model-level GRIB2 data:
>>> gfs_model_grib2_file_path = find_local_file(
... "cma_gfs_gmf/grib2/modelvar",
... start_time="2025081900",
... forecast_time="24h",
... )
>>> gfs_model_grib2_file_path
PosixPath('/g3/COMMONDATA/OPER/CEMC/GFS_GMF/Prod-grib/2025081900/MODELVAR/modelvar2025081900024.grb2')
>>> field = load_field_from_file(
... gfs_model_grib2_file_path,
... parameter="u",
... level_type="ml",
... level=10,
... )
>>> field
<xarray.DataArray 'u' (latitude: 1440, longitude: 2880)> Size: 33MB
array([[ 9.09106934, 9.09106934, 9.10106934, ..., 9.09106934,
9.09106934, 9.09106934],
[ 8.00106934, 8.00106934, 8.00106934, ..., 8.01106934,
8.01106934, 8.01106934],
[ 7.97106934, 7.96106934, 7.96106934, ..., 7.97106934,
7.97106934, 7.97106934],
...,
[11.00106934, 10.99106934, 10.98106934, ..., 11.04106934,
11.03106934, 11.01106934],
[11.73106934, 11.72106934, 11.71106934, ..., 11.77106934,
11.75106934, 11.74106934],
[14.21106934, 14.20106934, 14.19106934, ..., 14.24106934,
14.23106934, 14.22106934]], shape=(1440, 2880))
Coordinates:
time datetime64[ns] 8B 2025-08-19
step timedelta64[ns] 8B 1 days
valid_time datetime64[ns] 8B 2025-08-20
ml int64 8B 10
* latitude (latitude) float64 12kB 89.94 89.81 89.69 ... -89.81 -89.94
* longitude (longitude) float64 23kB 0.0 0.125 0.25 ... 359.6 359.8 359.9
Attributes: (12/17)
GRIB_edition: 2
GRIB_centre: babj
GRIB_subCentre: 0
GRIB_tablesVersion: 4
GRIB_localTablesVersion: 0
GRIB_dataType: fc
... ...
GRIB_stepType: instant
GRIB_stepUnits: 1
GRIB_stepRange: 24
GRIB_endStep:int: 24
GRIB_count: 187
long_name: discipline=0 parmcat=2 parm=2The load_field_from_file function also supports passing GRIB key parameters directly via a dictionary.
The example below loads the radar reflectivity field at 850 hPa:
>>> field = load_field_from_file(
... gfs_grib2_file_path,
... parameter={
... "discipline": 0,
... "parameterCategory": 16,
... "parameterNumber": 225,
... },
... level_type="pl",
... level=850,
... )
>>> field
<xarray.DataArray '0_16_225' (latitude: 1440, longitude: 2880)> Size: 33MB
array([[-7.12, -7.17, -7.24, ..., -7.03, -7.04, -7.06],
[-7.71, -7.64, -7.65, ..., -7.82, -7.8 , -7.78],
[-6.03, -6.07, -6.08, ..., -6.07, -6.08, -6.08],
...,
[ 1.52, 1.37, 1.18, ..., 1.59, 1.22, 1.23],
[ 0.65, 0.68, 1.31, ..., 0.65, 0.67, 0.69],
[-0.22, -0.2 , -0.21, ..., -0.25, -0.24, -0.24]],
shape=(1440, 2880))
Coordinates:
time datetime64[ns] 8B 2025-08-19
step timedelta64[ns] 8B 1 days
valid_time datetime64[ns] 8B 2025-08-20
pl float64 8B 850.0
* latitude (latitude) float64 12kB 89.94 89.81 89.69 ... -89.81 -89.94
* longitude (longitude) float64 23kB 0.0 0.125 0.25 ... 359.6 359.8 359.9
Attributes: (12/17)
GRIB_edition: 2
GRIB_centre: babj
GRIB_subCentre: 0
GRIB_tablesVersion: 4
GRIB_localTablesVersion: 1
GRIB_dataType: fc
... ...
GRIB_stepType: instant
GRIB_stepUnits: 1
GRIB_stepRange: 24
GRIB_endStep:int: 24
GRIB_count: 790
long_name: discipline=0 parmcat=16 parm=225reki supports returning the raw GRIB message via the ecCodes Python API. For instance, loading the 850 hPa geopotential height field:
>>> from reki.format.grib import load_message_from_file
>>> message = load_message_from_file(
... gfs_grib2_file_path,
... parameter="gh",
... level_type="pl",
... level=850,
... )
>>> message
94257262686816
>>> import eccodes
>>> values = eccodes.codes_get_double_array(message, "values")
>>> ni = eccodes.codes_get_long(message, "Ni")
>>> nj = eccodes.codes_get_long(message, "Nj")
>>> values.reshape(nj, ni)
array([[1425.48203125, 1425.48203125, 1425.48203125, ..., 1425.48203125,
1425.48203125, 1425.48203125],
[1428.68203125, 1428.68203125, 1428.68203125, ..., 1428.68203125,
1428.68203125, 1428.68203125],
[1431.18203125, 1431.18203125, 1431.18203125, ..., 1431.18203125,
1431.18203125, 1431.18203125],
...,
[1311.18203125, 1311.28203125, 1310.38203125, ..., 1311.08203125,
1311.08203125, 1311.08203125],
[1311.88203125, 1311.78203125, 1311.88203125, ..., 1311.88203125,
1311.88203125, 1311.88203125],
[1313.38203125, 1313.38203125, 1313.38203125, ..., 1313.28203125,
1313.38203125, 1313.38203125]], shape=(1440, 2880))Finally, release the GRIB message object:
>>> eccodes.codes_release(message)See cemc-oper/data-notebook project for more examples.
Copyright © 2020-2026, developers at CMA Earth System Modeling And Prediction Centre.
reki is licensed under Apache License, Version 2.0