GDPS 🅱

BETA Requires MetPy >=1.6

This demonstrates using data from Canada’s GEM Global or Global Deterministic Prediction System (GDPS).

GDPS Model Description

Data Sources

prioriy=	Data source	Archive Duration
"mcs"	Meteorological Service of Canada	Last 24 hours

Model Initialization

Model cyles every twelve hours.

Forecast Hour

For the most recent version of GDPS…

fxx=	Forecast lead time
0 through 240, step=3	3-hourly forecasts available

Products

product=	Product Description
"15km/grib2/lat_lon"	Global domain

Variable and Level

You will need to specify the variable and level for each request.

NOTE: The organization of these files is different than other NWP products.

1. There are no index files provided.

2. Each GRIB2 file only contains one message. The variable name and level is in the file’s name.

Herbie requires you provide a keyword argument for both variable and level. Pay special attention to model description (linked above) to understand how the model data is organized. If you don’t provide input for variable or level, Herbie will give you some ideas. For example, variable=TMP and level=TGL_2 will give you the filename that contains

TMP_TGL_2

Note: This requires MetPy version 1.6 or greater which has the capability to parse the rotated latitude longitude map projection type (see MetPy/#3123).

from herbie import Herbie
import xarray as xr
import numpy as np

import matplotlib.pyplot as plt
from herbie.toolbox import EasyMap, pc
import cartopy.crs as ccrs
import cartopy.feature as feature
import pandas as pd

recent = pd.Timestamp("now").floor("12h") - pd.Timedelta("12h")

recent

Timestamp('2026-04-16 12:00:00')

# Some examples

H = Herbie(
    recent,  # Datetime
    model="gdps",
    fxx=30,
    variable="TMP",
    level="TGL_2",
)
H.grib

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F30 ┊ GRIB2 @ msc ┊ IDX @ None

'https://dd.weather.gc.ca/20260416/WXO-DD/model_gem_global/15km/grib2/lat_lon/12/030/CMC_glb_TMP_TGL_2_latlon.15x.15_2026041612_P030.grib2'

H = Herbie(
    recent,  # Datetime
    model="gdps",
    fxx=12,
    variable="HGT",
    level="ISBL_500",
)
H.grib

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F12 ┊ GRIB2 @ msc ┊ IDX @ None

'https://dd.weather.gc.ca/20260416/WXO-DD/model_gem_global/15km/grib2/lat_lon/12/012/CMC_glb_HGT_ISBL_500_latlon.15x.15_2026041612_P012.grib2'

Get the 2-metre temperature

H = Herbie(
    recent,
    model="gdps",
    fxx=0,
    variable="TMP",
    level="TGL_2",
)
ds = H.xarray()
ds

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F00 ┊ GRIB2 @ msc ┊ IDX @ None
👨🏻‍🏭 Created directory: [/home/meteo/kps5442/data/gdps/20260416]

/home/kps5442/mapwall_dev/herbie-dev/src/herbie/core.py:1306: UserWarning: Will not remove GRIB file because Herbie will only remove subsetted files (not full files).
  warnings.warn(

<xarray.Dataset> Size: 12MB
Dimensions:              (latitude: 1201, longitude: 2400)
Coordinates:
  * latitude             (latitude) float64 10kB -90.0 -89.85 ... 89.85 90.0
  * longitude            (longitude) float64 19kB -180.0 -179.8 ... 179.7 179.8
    time                 datetime64[ns] 8B 2026-04-16T12:00:00
    step                 timedelta64[ns] 8B 00:00:00
    heightAboveGround    float64 8B 2.0
    valid_time           datetime64[ns] 8B ...
    gribfile_projection  object 8B None
Data variables:
    t2m                  (latitude, longitude) float32 12MB ...
Attributes:
    GRIB_edition:            2
    GRIB_centre:             cwao
    GRIB_centreDescription:  Canadian Meteorological Service - Montreal
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             Canadian Meteorological Service - Montreal
    model:                   gdps
    product:                 15km/grib2/lat_lon
    description:             Canada's Global Deterministic Prediction System ...
    remote_grib:             /home/meteo/kps5442/data/gdps/20260416/CMC_glb_T...
    local_grib:              /home/meteo/kps5442/data/gdps/20260416/CMC_glb_T...
    search:                  None

xarray.Dataset

• Dimensions:
  • latitude: 1201
  • longitude: 2400
• Coordinates: (7)
  • latitude
    (latitude)
    float64
    -90.0 -89.85 -89.7 ... 89.85 90.0

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    array([-90.  , -89.85, -89.7 , ...,  89.7 ,  89.85,  90.  ], shape=(1201,))

  • longitude
    (longitude)
    float64
    -180.0 -179.8 ... 179.7 179.8

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    array([-180.  , -179.85, -179.7 , ...,  179.55,  179.7 ,  179.85],
          shape=(2400,))

  • time
    ()
    datetime64[ns]
    2026-04-16T12:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2026-04-16T12:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    00:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(0, dtype='timedelta64[ns]')

  • heightAboveGround
    ()
    float64
    2.0

    long_name :

    height above the surface

    units :

    m

    positive :

    up

    standard_name :

    height

    array(2.)

  • valid_time
    ()
    datetime64[ns]
    ...

    standard_name :

    time

    long_name :

    time

    [1 values with dtype=datetime64[ns]]

  • gribfile_projection
    ()
    object
    None

    crs_wkt :

    GEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]],CS[ellipsoidal,2],AXIS["longitude",east,ORDER[1],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]],AXIS["latitude",north,ORDER[2],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]]]

    semi_major_axis :

    6371229.0

    semi_minor_axis :

    6371229.0

    inverse_flattening :

    0.0

    reference_ellipsoid_name :

    unknown

    longitude_of_prime_meridian :

    0.0

    prime_meridian_name :

    Greenwich

    geographic_crs_name :

    unknown

    horizontal_datum_name :

    unknown

    grid_mapping_name :

    latitude_longitude

    long_name :

    GDPS model grid projection

    array(None, dtype=object)

• Data variables: (1)
  • t2m
    (latitude, longitude)
    float32
    ...

    GRIB_paramId :

    167

    GRIB_dataType :

    af

    GRIB_numberOfPoints :

    2882400

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    regular_ll

    GRIB_uvRelativeToGrid :

    0

    GRIB_NV :

    0

    GRIB_Nx :

    2400

    GRIB_Ny :

    1201

    GRIB_cfName :

    air_temperature

    GRIB_cfVarName :

    t2m

    GRIB_gridDefinitionDescription :

    Latitude/longitude

    GRIB_iDirectionIncrementInDegrees :

    0.15

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.15

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    -90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    180.0

    GRIB_longitudeOfLastGridPointInDegrees :

    179.85

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    2 metre temperature

    GRIB_parameterName :

    Temperature

    GRIB_parameterUnits :

    K

    GRIB_shapeOfTheEarth :

    6

    GRIB_shortName :

    2t

    GRIB_stepRange :

    0

    GRIB_units :

    K

    long_name :

    2 metre temperature

    units :

    K

    standard_name :

    air_temperature

    grid_mapping :

    gribfile_projection

    [2882400 values with dtype=float32]

• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  cwao

  GRIB_centreDescription :

  Canadian Meteorological Service - Montreal

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  Canadian Meteorological Service - Montreal

  model :

  gdps

  product :

  15km/grib2/lat_lon

  description :

  Canada's Global Deterministic Prediction System (GDPS)

  remote_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_TMP_TGL_2_latlon.15x.15_2026041612_P000.grib2

  local_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_TMP_TGL_2_latlon.15x.15_2026041612_P000.grib2

  search :

  None

Plot data on Plate Carree projection

ax = EasyMap("50m").BORDERS().STATES(alpha=0.5).ax
p = ax.pcolormesh(ds.longitude, ds.latitude, ds.t2m, transform=pc, cmap="Spectral_r")
plt.colorbar(p, ax=ax, orientation="horizontal", pad=0.01, shrink=0.8)
ax.set_title(
    f"2-m Temperature\nValid {ds.valid_time.dt.strftime('%Y-%m-%d %H:%M').item()} UTC",
    loc="right",
    fontsize=10,
)
ax.set_title(f"{ds.model.upper()}: {H.product_description}", loc="left")
ax.gridlines()

<cartopy.mpl.gridliner.Gridliner at 0x764b2a5874d0>

Get 10-m U and 10-m V wind

# loading more than one variable requires a loop, because the
# data is stored in multiple files (and a Herbie object only
# represents a single file).

store = []
for var, lev in zip(["UGRD", "VGRD"], ["TGL_10", "TGL_10"]):
    _ds = Herbie(
        recent,
        model="gdps",
        fxx=0,
        product="15km/grib2/lat_lon",
        variable=var,
        level=lev,
    ).xarray()
    store.append(_ds)

ds = xr.merge(store)
ds

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F00 ┊ GRIB2 @ msc ┊ IDX @ None

/home/kps5442/mapwall_dev/herbie-dev/src/herbie/core.py:1306: UserWarning: Will not remove GRIB file because Herbie will only remove subsetted files (not full files).
  warnings.warn(

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F00 ┊ GRIB2 @ msc ┊ IDX @ None

/home/kps5442/mapwall_dev/herbie-dev/src/herbie/core.py:1306: UserWarning: Will not remove GRIB file because Herbie will only remove subsetted files (not full files).
  warnings.warn(
/tmp/ipykernel_2515008/1831517428.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1831517428.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1831517428.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1831517428.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1831517428.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)

<xarray.Dataset> Size: 23MB
Dimensions:              (latitude: 1201, longitude: 2400)
Coordinates:
  * latitude             (latitude) float64 10kB -90.0 -89.85 ... 89.85 90.0
  * longitude            (longitude) float64 19kB -180.0 -179.8 ... 179.7 179.8
    time                 datetime64[ns] 8B 2026-04-16T12:00:00
    step                 timedelta64[ns] 8B 00:00:00
    heightAboveGround    float64 8B 10.0
    valid_time           datetime64[ns] 8B 2026-04-16T12:00:00
    gribfile_projection  object 8B None
Data variables:
    u10                  (latitude, longitude) float32 12MB ...
    v10                  (latitude, longitude) float32 12MB ...
Attributes:
    GRIB_edition:            2
    GRIB_centre:             cwao
    GRIB_centreDescription:  Canadian Meteorological Service - Montreal
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             Canadian Meteorological Service - Montreal
    model:                   gdps
    product:                 15km/grib2/lat_lon
    description:             Canada's Global Deterministic Prediction System ...
    remote_grib:             /home/meteo/kps5442/data/gdps/20260416/CMC_glb_U...
    local_grib:              /home/meteo/kps5442/data/gdps/20260416/CMC_glb_U...
    search:                  None

xarray.Dataset

• Dimensions:
  • latitude: 1201
  • longitude: 2400
• Coordinates: (7)
  • latitude
    (latitude)
    float64
    -90.0 -89.85 -89.7 ... 89.85 90.0

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    array([-90.  , -89.85, -89.7 , ...,  89.7 ,  89.85,  90.  ], shape=(1201,))

  • longitude
    (longitude)
    float64
    -180.0 -179.8 ... 179.7 179.8

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    array([-180.  , -179.85, -179.7 , ...,  179.55,  179.7 ,  179.85],
          shape=(2400,))

  • time
    ()
    datetime64[ns]
    2026-04-16T12:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2026-04-16T12:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    00:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(0, dtype='timedelta64[ns]')

  • heightAboveGround
    ()
    float64
    10.0

    long_name :

    height above the surface

    units :

    m

    positive :

    up

    standard_name :

    height

    array(10.)

  • valid_time
    ()
    datetime64[ns]
    2026-04-16T12:00:00

    standard_name :

    time

    long_name :

    time

    array('2026-04-16T12:00:00.000000000', dtype='datetime64[ns]')

  • gribfile_projection
    ()
    object
    None

    crs_wkt :

    GEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]],CS[ellipsoidal,2],AXIS["longitude",east,ORDER[1],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]],AXIS["latitude",north,ORDER[2],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]]]

    semi_major_axis :

    6371229.0

    semi_minor_axis :

    6371229.0

    inverse_flattening :

    0.0

    reference_ellipsoid_name :

    unknown

    longitude_of_prime_meridian :

    0.0

    prime_meridian_name :

    Greenwich

    geographic_crs_name :

    unknown

    horizontal_datum_name :

    unknown

    grid_mapping_name :

    latitude_longitude

    long_name :

    GDPS model grid projection

    array(None, dtype=object)

• Data variables: (2)
  • u10
    (latitude, longitude)
    float32
    ...

    GRIB_paramId :

    165

    GRIB_dataType :

    af

    GRIB_numberOfPoints :

    2882400

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    regular_ll

    GRIB_uvRelativeToGrid :

    0

    GRIB_NV :

    0

    GRIB_Nx :

    2400

    GRIB_Ny :

    1201

    GRIB_cfName :

    eastward_wind

    GRIB_cfVarName :

    u10

    GRIB_gridDefinitionDescription :

    Latitude/longitude

    GRIB_iDirectionIncrementInDegrees :

    0.15

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.15

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    -90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    180.0

    GRIB_longitudeOfLastGridPointInDegrees :

    179.85

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    10 metre U wind component

    GRIB_parameterName :

    u-component of wind

    GRIB_parameterUnits :

    m s-1

    GRIB_shapeOfTheEarth :

    6

    GRIB_shortName :

    10u

    GRIB_stepRange :

    0

    GRIB_units :

    m s**-1

    long_name :

    10 metre U wind component

    units :

    m s**-1

    standard_name :

    eastward_wind

    grid_mapping :

    gribfile_projection

    [2882400 values with dtype=float32]

  • v10
    (latitude, longitude)
    float32
    ...

    GRIB_paramId :

    166

    GRIB_dataType :

    af

    GRIB_numberOfPoints :

    2882400

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    regular_ll

    GRIB_uvRelativeToGrid :

    0

    GRIB_NV :

    0

    GRIB_Nx :

    2400

    GRIB_Ny :

    1201

    GRIB_cfName :

    northward_wind

    GRIB_cfVarName :

    v10

    GRIB_gridDefinitionDescription :

    Latitude/longitude

    GRIB_iDirectionIncrementInDegrees :

    0.15

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.15

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    -90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    180.0

    GRIB_longitudeOfLastGridPointInDegrees :

    179.85

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    10 metre V wind component

    GRIB_parameterName :

    v-component of wind

    GRIB_parameterUnits :

    m s-1

    GRIB_shapeOfTheEarth :

    6

    GRIB_shortName :

    10v

    GRIB_stepRange :

    0

    GRIB_units :

    m s**-1

    long_name :

    10 metre V wind component

    units :

    m s**-1

    standard_name :

    northward_wind

    grid_mapping :

    gribfile_projection

    [2882400 values with dtype=float32]

• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  cwao

  GRIB_centreDescription :

  Canadian Meteorological Service - Montreal

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  Canadian Meteorological Service - Montreal

  model :

  gdps

  product :

  15km/grib2/lat_lon

  description :

  Canada's Global Deterministic Prediction System (GDPS)

  remote_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_UGRD_TGL_10_latlon.15x.15_2026041612_P000.grib2

  local_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_UGRD_TGL_10_latlon.15x.15_2026041612_P000.grib2

  search :

  None

# MetPy version >= 1.6 is required to parse the map projection
ds.herbie.crs

<cartopy.crs.PlateCarree object at 0x764b30972150>

ax = (
    EasyMap("50m", crs=ds.herbie.crs, figsize=8, linewidth=1)
    .BORDERS()
    .STATES(alpha=0.5)
    .ax
)
p = ax.pcolormesh(
    ds.longitude,
    ds.latitude,
    np.hypot(ds.u10, ds.v10),  # Wind Speed
    transform=pc,
)
plt.colorbar(
    p, ax=ax, orientation="horizontal", pad=0.01, shrink=0.8, label="Wind speed (m/s)"
)

ax.set_title(
    f"10-m Wind Speed\nValid {ds.valid_time.dt.strftime('%Y-%m-%d %H:%M').item()} UTC",
    loc="center",
    fontsize=10,
)
ax.set_title(f"{ds.model.upper()}", loc="left")

Text(0.0, 1.0, 'GDPS')

500 hPa Humidity and Geopotential Height

# loading more than one variable requires a loop, because the
# data is stored in multiple files (and a Herbie object only
# represents a single file).

store = []
for var, lev in zip(["HGT", "RH"], ["ISBL_500", "ISBL_500"]):
    _ds = Herbie(
        recent,
        model="gdps",
        fxx=0,
        product="15km/grib2/lat_lon",
        variable=var,
        level=lev,
    ).xarray()
    store.append(_ds)

ds = xr.merge(store)
ds

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F00 ┊ GRIB2 @ msc ┊ IDX @ None

/home/kps5442/mapwall_dev/herbie-dev/src/herbie/core.py:1306: UserWarning: Will not remove GRIB file because Herbie will only remove subsetted files (not full files).
  warnings.warn(

✅ Found ┊ model=gdps ┊ product=15km/grib2/lat_lon ┊ 2026-Apr-16 12:00 UTC F00 ┊ GRIB2 @ msc ┊ IDX @ None

/home/kps5442/mapwall_dev/herbie-dev/src/herbie/core.py:1306: UserWarning: Will not remove GRIB file because Herbie will only remove subsetted files (not full files).
  warnings.warn(
/tmp/ipykernel_2515008/1199894210.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1199894210.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1199894210.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1199894210.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)
/tmp/ipykernel_2515008/1199894210.py:17: FutureWarning: In a future version of xarray the default value for compat will change from compat='no_conflicts' to compat='override'. This is likely to lead to different results when combining overlapping variables with the same name. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set compat explicitly.
  ds = xr.merge(store)

<xarray.Dataset> Size: 23MB
Dimensions:              (latitude: 1201, longitude: 2400)
Coordinates:
  * latitude             (latitude) float64 10kB -90.0 -89.85 ... 89.85 90.0
  * longitude            (longitude) float64 19kB -180.0 -179.8 ... 179.7 179.8
    time                 datetime64[ns] 8B 2026-04-16T12:00:00
    step                 timedelta64[ns] 8B 00:00:00
    isobaricInhPa        float64 8B 500.0
    valid_time           datetime64[ns] 8B 2026-04-16T12:00:00
    gribfile_projection  object 8B None
Data variables:
    gh                   (latitude, longitude) float32 12MB ...
    r                    (latitude, longitude) float32 12MB ...
Attributes:
    GRIB_edition:            2
    GRIB_centre:             cwao
    GRIB_centreDescription:  Canadian Meteorological Service - Montreal
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             Canadian Meteorological Service - Montreal
    model:                   gdps
    product:                 15km/grib2/lat_lon
    description:             Canada's Global Deterministic Prediction System ...
    remote_grib:             /home/meteo/kps5442/data/gdps/20260416/CMC_glb_H...
    local_grib:              /home/meteo/kps5442/data/gdps/20260416/CMC_glb_H...
    search:                  None

xarray.Dataset

• Dimensions:
  • latitude: 1201
  • longitude: 2400
• Coordinates: (7)
  • latitude
    (latitude)
    float64
    -90.0 -89.85 -89.7 ... 89.85 90.0

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    array([-90.  , -89.85, -89.7 , ...,  89.7 ,  89.85,  90.  ], shape=(1201,))

  • longitude
    (longitude)
    float64
    -180.0 -179.8 ... 179.7 179.8

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    array([-180.  , -179.85, -179.7 , ...,  179.55,  179.7 ,  179.85],
          shape=(2400,))

  • time
    ()
    datetime64[ns]
    2026-04-16T12:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2026-04-16T12:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    00:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(0, dtype='timedelta64[ns]')

  • isobaricInhPa
    ()
    float64
    500.0

    long_name :

    pressure

    units :

    hPa

    positive :

    down

    stored_direction :

    decreasing

    standard_name :

    air_pressure

    array(500.)

  • valid_time
    ()
    datetime64[ns]
    2026-04-16T12:00:00

    standard_name :

    time

    long_name :

    time

    array('2026-04-16T12:00:00.000000000', dtype='datetime64[ns]')

  • gribfile_projection
    ()
    object
    None

    crs_wkt :

    GEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]],CS[ellipsoidal,2],AXIS["longitude",east,ORDER[1],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]],AXIS["latitude",north,ORDER[2],ANGLEUNIT["degree",0.0174532925199433,ID["EPSG",9122]]]]

    semi_major_axis :

    6371229.0

    semi_minor_axis :

    6371229.0

    inverse_flattening :

    0.0

    reference_ellipsoid_name :

    unknown

    longitude_of_prime_meridian :

    0.0

    prime_meridian_name :

    Greenwich

    geographic_crs_name :

    unknown

    horizontal_datum_name :

    unknown

    grid_mapping_name :

    latitude_longitude

    long_name :

    GDPS model grid projection

    array(None, dtype=object)

• Data variables: (2)
  • gh
    (latitude, longitude)
    float32
    ...

    GRIB_paramId :

    156

    GRIB_dataType :

    af

    GRIB_numberOfPoints :

    2882400

    GRIB_typeOfLevel :

    isobaricInhPa

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    regular_ll

    GRIB_uvRelativeToGrid :

    0

    GRIB_NV :

    0

    GRIB_Nx :

    2400

    GRIB_Ny :

    1201

    GRIB_cfName :

    geopotential_height

    GRIB_cfVarName :

    gh

    GRIB_gridDefinitionDescription :

    Latitude/longitude

    GRIB_iDirectionIncrementInDegrees :

    0.15

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.15

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    -90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    180.0

    GRIB_longitudeOfLastGridPointInDegrees :

    179.85

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    Geopotential height

    GRIB_parameterName :

    Geopotential height

    GRIB_parameterUnits :

    gpm

    GRIB_shapeOfTheEarth :

    6

    GRIB_shortName :

    gh

    GRIB_stepRange :

    0

    GRIB_units :

    gpm

    long_name :

    Geopotential height

    units :

    gpm

    standard_name :

    geopotential_height

    grid_mapping :

    gribfile_projection

    [2882400 values with dtype=float32]

  • r
    (latitude, longitude)
    float32
    ...

    GRIB_paramId :

    157

    GRIB_dataType :

    af

    GRIB_numberOfPoints :

    2882400

    GRIB_typeOfLevel :

    isobaricInhPa

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    regular_ll

    GRIB_uvRelativeToGrid :

    0

    GRIB_NV :

    0

    GRIB_Nx :

    2400

    GRIB_Ny :

    1201

    GRIB_cfName :

    relative_humidity

    GRIB_cfVarName :

    r

    GRIB_gridDefinitionDescription :

    Latitude/longitude

    GRIB_iDirectionIncrementInDegrees :

    0.15

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.15

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    -90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    180.0

    GRIB_longitudeOfLastGridPointInDegrees :

    179.85

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    Relative humidity

    GRIB_parameterName :

    Relative humidity

    GRIB_parameterUnits :

    %

    GRIB_shapeOfTheEarth :

    6

    GRIB_shortName :

    r

    GRIB_stepRange :

    0

    GRIB_units :

    %

    long_name :

    Relative humidity

    units :

    %

    standard_name :

    relative_humidity

    grid_mapping :

    gribfile_projection

    [2882400 values with dtype=float32]

• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  cwao

  GRIB_centreDescription :

  Canadian Meteorological Service - Montreal

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  Canadian Meteorological Service - Montreal

  model :

  gdps

  product :

  15km/grib2/lat_lon

  description :

  Canada's Global Deterministic Prediction System (GDPS)

  remote_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_HGT_ISBL_500_latlon.15x.15_2026041612_P000.grib2

  local_grib :

  /home/meteo/kps5442/data/gdps/20260416/CMC_glb_HGT_ISBL_500_latlon.15x.15_2026041612_P000.grib2

  search :

  None

ax = (
    EasyMap("50m", crs=ds.herbie.crs, figsize=8, linewidth=1)
    .BORDERS()
    .STATES(alpha=0.5)
    .ax
)

# Draw Relative Humidity
p = ax.pcolormesh(
    ds.longitude, ds.latitude, ds.r, transform=pc, cmap="BrBG", vmin=0, vmax=100
)
plt.colorbar(
    p,
    ax=ax,
    orientation="horizontal",
    pad=0.01,
    shrink=0.8,
    label="Relative Humidity (%)",
)

# Draw Geopential Height Contours
ax.contour(
    ds.longitude,
    ds.latitude,
    ds.gh,
    colors="k",
    transform=pc,
    levels=range(0, 6000, 80),
)

ax.set_title(
    f"500 hPa RH and Geopotential height\nValid {ds.valid_time.dt.strftime('%Y-%m-%d %H:%M').item()} UTC",
    loc="center",
    fontsize=10,
)
ax.set_title(f"{ds.model.upper()}", loc="left")

Text(0.0, 1.0, 'GDPS')