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 from pip:
pip install rekior download the latest source code from GitHub and install using pip.
reki uses ecCodes to decode GRIB files
(which is needed by eccodes and cfgrib).
Please install ecCodes through conda or other package source.
The reki library includes built-in config files to locate data files in the CMA National Meteorological Supercomputing System 1 (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.eccodes 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.eccodes 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 © 2020-2025, developers at cemc-oper.
reki is licensed under Apache License, Version 2.0