Herbie Accessors

🏗 Some features are under construction

Herbie comes with custom xarray DataSet accessors.

# Usage
ds.herbie.<method>

Some of these tools require the Carpenter Workshop package.

from herbie import Herbie

H = Herbie("2022-12-05 06:00", fxx=6, model="hrrr")
ds = H.xarray("TMP:2 m")

✅ Found ┊ model=hrrr ┊ product=sfc ┊ 2022-Dec-05 06:00 UTC F06 ┊ GRIB2 @ aws ┊ IDX @ aws
👨🏻‍🏭 Created directory: [/home/blaylock/data/hrrr/20221205]

ds

<xarray.Dataset>
Dimensions:              (y: 1059, x: 1799)
Coordinates:
    time                 datetime64[ns] 2022-12-05T06:00:00
    step                 timedelta64[ns] 06:00:00
    heightAboveGround    float64 2.0
    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84
    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1
    valid_time           datetime64[ns] 2022-12-05T12:00:00
Dimensions without coordinates: y, x
Data variables:
    t2m                  (y, x) float32 294.4 294.4 294.4 ... 273.0 273.0 273.0
    gribfile_projection  object None
Attributes:
    GRIB_edition:            2
    GRIB_centre:             kwbc
    GRIB_centreDescription:  US National Weather Service - NCEP
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             US National Weather Service - NCEP
    model:                   hrrr
    product:                 sfc
    description:             High-Resolution Rapid Refresh - CONUS
    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....
    local_grib:              /home/blaylock/data/hrrr/20221205/subset_0cb2fd5...
    searchString:            TMP:2 m

xarray.Dataset

• Dimensions:
  • y: 1059
  • x: 1799
• Coordinates: (6)
  • time
    ()
    datetime64[ns]
    2022-12-05T06:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2022-12-05T06:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    06:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(21600000000000, dtype='timedelta64[ns]')

  • heightAboveGround
    ()
    float64
    2.0

    long_name :

    height above the surface

    units :

    m

    positive :

    up

    standard_name :

    height

    array(2.)

  • latitude
    (y, x)
    float64
    21.14 21.15 21.15 ... 47.85 47.84

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    array([[21.138123  , 21.14511004, 21.1520901 , ..., 21.1545089 ,
            21.14753125, 21.14054663],
           [21.16299459, 21.1699845 , 21.17696744, ..., 21.17938723,
            21.1724067 , 21.16541921],
           [21.18786863, 21.19486142, 21.20184723, ..., 21.20426802,
            21.19728462, 21.19029425],
           ...,
           [47.78955926, 47.799849  , 47.81012868, ..., 47.81369093,
            47.80341474, 47.79312849],
           [47.81409316, 47.82438621, 47.8346692 , ..., 47.83823259,
            47.8279531 , 47.81766354],
           [47.8386235 , 47.84891986, 47.85920615, ..., 47.86277069,
            47.85248789, 47.84219502]])

  • longitude
    (y, x)
    float64
    237.3 237.3 237.3 ... 299.0 299.1

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    array([[237.280472  , 237.30713868, 237.3338097 , ..., 287.6569408 ,
            287.68361332, 287.71028151],
           [237.27297501, 237.29964881, 237.32632695, ..., 287.66442108,
            287.69110073, 287.71777603],
           [237.26547368, 237.2921546 , 237.31883986, ..., 287.6719057 ,
            287.69859247, 287.7252749 ],
           ...,
           [225.9351904 , 225.97171577, 226.00825329, ..., 298.97907406,
            299.0156158 , 299.05214538],
           [225.91986142, 225.95639874, 225.99294822, ..., 298.99437498,
            299.03092868, 299.06747022],
           [225.90452027, 225.94106954, 225.97763099, ..., 299.00968806,
            299.04625373, 299.08280723]])

  • valid_time
    ()
    datetime64[ns]
    2022-12-05T12:00:00

    standard_name :

    time

    long_name :

    time

    array('2022-12-05T12:00:00.000000000', dtype='datetime64[ns]')

• Data variables: (2)
  • t2m
    (y, x)
    float32
    294.4 294.4 294.4 ... 273.0 273.0

    GRIB_paramId :

    167

    GRIB_dataType :

    fc

    GRIB_numberOfPoints :

    1905141

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    lambert

    GRIB_DxInMetres :

    3000.0

    GRIB_DyInMetres :

    3000.0

    GRIB_LaDInDegrees :

    38.5

    GRIB_Latin1InDegrees :

    38.5

    GRIB_Latin2InDegrees :

    38.5

    GRIB_LoVInDegrees :

    262.5

    GRIB_NV :

    0

    GRIB_Nx :

    1799

    GRIB_Ny :

    1059

    GRIB_cfName :

    air_temperature

    GRIB_cfVarName :

    t2m

    GRIB_gridDefinitionDescription :

    Lambert Conformal can be secant or tangent, conical or bipolar

    GRIB_iScansNegatively :

    0

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    21.138123

    GRIB_latitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    237.280472

    GRIB_longitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    2 metre temperature

    GRIB_parameterName :

    Temperature

    GRIB_parameterUnits :

    K

    GRIB_shortName :

    2t

    GRIB_stepRange :

    6

    GRIB_units :

    K

    long_name :

    2 metre temperature

    units :

    K

    standard_name :

    air_temperature

    grid_mapping :

    gribfile_projection

    array([[294.3877, 294.3877, 294.3877, ..., 299.7002, 299.7002, 299.7002],
           [294.3877, 294.3252, 294.2627, ..., 299.6377, 299.6377, 299.7002],
           [294.3877, 294.3252, 294.2627, ..., 299.5752, 299.6377, 299.6377],
           ...,
           [281.5127, 281.4502, 281.4502, ..., 272.8877, 272.9502, 273.0127],
           [281.5127, 281.4502, 281.4502, ..., 272.8877, 272.8877, 273.0127],
           [281.4502, 281.4502, 281.4502, ..., 272.9502, 273.0127, 273.0127]],
          dtype=float32)

  • gribfile_projection
    ()
    object
    None

    crs_wkt :

    PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Lambert Conic Conformal (2SP)",ID["EPSG",9802]],PARAMETER["Latitude of false origin",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8821]],PARAMETER["Longitude of false origin",262.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8822]],PARAMETER["Latitude of 1st standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8823]],PARAMETER["Latitude of 2nd standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8824]],PARAMETER["Easting at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8826]],PARAMETER["Northing at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8827]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]

    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

    projected_crs_name :

    unknown

    grid_mapping_name :

    lambert_conformal_conic

    standard_parallel :

    (38.5, 38.5)

    latitude_of_projection_origin :

    38.5

    longitude_of_central_meridian :

    262.5

    false_easting :

    0.0

    false_northing :

    0.0

    long_name :

    HRRR model grid projection

    array(None, dtype=object)

• Indexes: (0)
• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  kwbc

  GRIB_centreDescription :

  US National Weather Service - NCEP

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  US National Weather Service - NCEP

  model :

  hrrr

  product :

  sfc

  description :

  High-Resolution Rapid Refresh - CONUS

  remote_grib :

  https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20221205/conus/hrrr.t06z.wrfsfcf06.grib2

  local_grib :

  /home/blaylock/data/hrrr/20221205/subset_0cb2fd54__hrrr.t06z.wrfsfcf06.grib2

  searchString :

  TMP:2 m

Cartopy Coordinate Reference System

Derive the Cartopy coordinate reference system.

This is helpful if you want to plot the data on the map.

Requires Metpy and Pygrib

ds.herbie.crs

/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/cartopy/io/__init__.py:241: DownloadWarning: Downloading: https://naturalearth.s3.amazonaws.com/110m_physical/ne_110m_coastline.zip
  warnings.warn(f'Downloading: {url}', DownloadWarning)

<cartopy.crs.LambertConformal object at 0x7ff7a822fb50>

Model domain boundary

Returns the model domain boundary as a polygon. 1. Polygon in model coordinate system. 1. Polygon in latitude/longitude coordinates.

ds.herbie.polygon[0]

ds.herbie.polygon[1]

Extract nearest points

Extract the value nearest a latitude/longitude point.

The points argument accepts several different inputs.

• a tuple of (lon, lat)

• a list of tuples [(lon, lat), (lon, lat), (lon, lat)]

• a Pandas DataFrame with columns longitude and latitude (Index will be used to name the points).

• a Shapely geometry Point or MultiPoint object.

# Get value nearest single point
ds.herbie.nearest_points(points=(-100, 40))

/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "t2m".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'

<xarray.Dataset>
Dimensions:              (point: 1)
Coordinates:
    time                 datetime64[ns] 2022-12-05T06:00:00
    step                 timedelta64[ns] 06:00:00
    heightAboveGround    float64 2.0
    latitude             float64 40.01
    longitude            float64 260.0
    valid_time           datetime64[ns] 2022-12-05T12:00:00
    metpy_crs            object Projection: lambert_conformal_conic
    y                    float64 1.707e+05
    x                    float64 -2.135e+05
  * point                (point) object None
    point_latitude       (point) int64 40
    point_longitude      (point) int64 -100
Data variables:
    t2m                  (point) float32 271.0
    gribfile_projection  (point) object None
Attributes:
    GRIB_edition:            2
    GRIB_centre:             kwbc
    GRIB_centreDescription:  US National Weather Service - NCEP
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             US National Weather Service - NCEP
    model:                   hrrr
    product:                 sfc
    description:             High-Resolution Rapid Refresh - CONUS
    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....
    local_grib:              /home/blaylock/data/hrrr/20221205/subset_0cb2fd5...
    searchString:            TMP:2 m

xarray.Dataset

• Dimensions:
  • point: 1
• Coordinates: (12)
  • time
    ()
    datetime64[ns]
    2022-12-05T06:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2022-12-05T06:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    06:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(21600000000000, dtype='timedelta64[ns]')

  • heightAboveGround
    ()
    float64
    2.0

    long_name :

    height above the surface

    units :

    m

    positive :

    up

    standard_name :

    height

    _metpy_axis :

    vertical

    array(2.)

  • latitude
    ()
    float64
    40.01

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    _metpy_axis :

    latitude

    array(40.00871026)

  • longitude
    ()
    float64
    260.0

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    _metpy_axis :

    longitude

    array(259.9936499)

  • valid_time
    ()
    datetime64[ns]
    2022-12-05T12:00:00

    standard_name :

    time

    long_name :

    time

    array('2022-12-05T12:00:00.000000000', dtype='datetime64[ns]')

  • metpy_crs
    ()
    object
    Projection: lambert_conformal_conic

    array(<metpy.plots.mapping.CFProjection object at 0x7ff73fd99b50>,
          dtype=object)

  • y
    ()
    float64
    1.707e+05

    units :

    meter

    standard_name :

    projection_y_coordinate

    array(170693.84744334)

  • x
    ()
    float64
    -2.135e+05

    units :

    meter

    standard_name :

    projection_x_coordinate

    array(-213520.14252193)

  • point
    (point)
    object
    None

    array([None], dtype=object)

  • point_latitude
    (point)
    int64
    40

    array([40])

  • point_longitude
    (point)
    int64
    -100

    array([-100])

• Data variables: (2)
  • t2m
    (point)
    float32
    271.0

    GRIB_paramId :

    167

    GRIB_dataType :

    fc

    GRIB_numberOfPoints :

    1905141

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    lambert

    GRIB_DxInMetres :

    3000.0

    GRIB_DyInMetres :

    3000.0

    GRIB_LaDInDegrees :

    38.5

    GRIB_Latin1InDegrees :

    38.5

    GRIB_Latin2InDegrees :

    38.5

    GRIB_LoVInDegrees :

    262.5

    GRIB_NV :

    0

    GRIB_Nx :

    1799

    GRIB_Ny :

    1059

    GRIB_cfName :

    air_temperature

    GRIB_cfVarName :

    t2m

    GRIB_gridDefinitionDescription :

    Lambert Conformal can be secant or tangent, conical or bipolar

    GRIB_iScansNegatively :

    0

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    21.138123

    GRIB_latitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    237.280472

    GRIB_longitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    2 metre temperature

    GRIB_parameterName :

    Temperature

    GRIB_parameterUnits :

    K

    GRIB_shortName :

    2t

    GRIB_stepRange :

    6

    GRIB_units :

    K

    long_name :

    2 metre temperature

    units :

    K

    standard_name :

    air_temperature

    grid_mapping :

    gribfile_projection

    array([270.9502], dtype=float32)

  • gribfile_projection
    (point)
    object
    None

    crs_wkt :

    PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Lambert Conic Conformal (2SP)",ID["EPSG",9802]],PARAMETER["Latitude of false origin",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8821]],PARAMETER["Longitude of false origin",262.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8822]],PARAMETER["Latitude of 1st standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8823]],PARAMETER["Latitude of 2nd standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8824]],PARAMETER["Easting at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8826]],PARAMETER["Northing at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8827]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]

    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

    projected_crs_name :

    unknown

    grid_mapping_name :

    lambert_conformal_conic

    standard_parallel :

    (38.5, 38.5)

    latitude_of_projection_origin :

    38.5

    longitude_of_central_meridian :

    262.5

    false_easting :

    0.0

    false_northing :

    0.0

    long_name :

    HRRR model grid projection

    array([None], dtype=object)

• Indexes: (1)
  • point
    PandasIndex

    PandasIndex(Index([None], dtype='object', name='point'))

• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  kwbc

  GRIB_centreDescription :

  US National Weather Service - NCEP

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  US National Weather Service - NCEP

  model :

  hrrr

  product :

  sfc

  description :

  High-Resolution Rapid Refresh - CONUS

  remote_grib :

  https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20221205/conus/hrrr.t06z.wrfsfcf06.grib2

  local_grib :

  /home/blaylock/data/hrrr/20221205/subset_0cb2fd54__hrrr.t06z.wrfsfcf06.grib2

  searchString :

  TMP:2 m

import pandas as pd

# Get values nearest many points

df = pd.DataFrame(
    {
        "longitude": range(-100, -90, 2),
        "latitude": range(35, 45, 2),
    }
)

ds.herbie.nearest_points(points=df)

/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "t2m".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'

<xarray.Dataset>
Dimensions:              (point: 5)
Coordinates:
    time                 datetime64[ns] 2022-12-05T06:00:00
    step                 timedelta64[ns] 06:00:00
    heightAboveGround    float64 2.0
    latitude             (point) float64 34.99 37.01 39.0 41.01 43.01
    longitude            (point) float64 260.0 262.0 264.0 266.0 268.0
    valid_time           datetime64[ns] 2022-12-05T12:00:00
    metpy_crs            object Projection: lambert_conformal_conic
    y                    (point) float64 -3.873e+05 -1.653e+05 ... 5.157e+05
    x                    (point) float64 -2.285e+05 -4.552e+04 ... 4.495e+05
  * point                (point) int64 0 1 2 3 4
    point_latitude       (point) int64 35 37 39 41 43
    point_longitude      (point) int64 -100 -98 -96 -94 -92
Data variables:
    t2m                  (point) float32 282.1 274.5 274.0 272.5 271.2
    gribfile_projection  (point) object None None None None None
Attributes:
    GRIB_edition:            2
    GRIB_centre:             kwbc
    GRIB_centreDescription:  US National Weather Service - NCEP
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             US National Weather Service - NCEP
    model:                   hrrr
    product:                 sfc
    description:             High-Resolution Rapid Refresh - CONUS
    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....
    local_grib:              /home/blaylock/data/hrrr/20221205/subset_0cb2fd5...
    searchString:            TMP:2 m

xarray.Dataset

• Dimensions:
  • point: 5
• Coordinates: (12)
  • time
    ()
    datetime64[ns]
    2022-12-05T06:00:00

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2022-12-05T06:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    06:00:00

    long_name :

    time since forecast_reference_time

    standard_name :

    forecast_period

    array(21600000000000, dtype='timedelta64[ns]')

  • heightAboveGround
    ()
    float64
    2.0

    long_name :

    height above the surface

    units :

    m

    positive :

    up

    standard_name :

    height

    _metpy_axis :

    vertical

    array(2.)

  • latitude
    (point)
    float64
    34.99 37.01 39.0 41.01 43.01

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    _metpy_axis :

    latitude

    array([34.99120814, 37.0124461 , 39.00050324, 41.00929645, 43.01172233])

  • longitude
    (point)
    float64
    260.0 262.0 264.0 266.0 268.0

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    _metpy_axis :

    longitude

    array([259.99582767, 261.98751357, 263.98674757, 265.99495743,
           268.01375415])

  • valid_time
    ()
    datetime64[ns]
    2022-12-05T12:00:00

    standard_name :

    time

    long_name :

    time

    array('2022-12-05T12:00:00.000000000', dtype='datetime64[ns]')

  • metpy_crs
    ()
    object
    Projection: lambert_conformal_conic

    array(<metpy.plots.mapping.CFProjection object at 0x7ff73fd40e50>,
          dtype=object)

  • y
    (point)
    float64
    -3.873e+05 -1.653e+05 ... 5.157e+05

    units :

    meter

    standard_name :

    projection_y_coordinate

    array([-387306.15255666, -165306.15255666,   56693.84744334,
            284693.84744334,  515693.84744334])

  • x
    (point)
    float64
    -2.285e+05 -4.552e+04 ... 4.495e+05

    units :

    meter

    standard_name :

    projection_x_coordinate

    array([-228520.14252193,  -45520.14252193,  128479.85747807,
            293479.85747807,  449479.85747807])

  • point
    (point)
    int64
    0 1 2 3 4

    array([0, 1, 2, 3, 4])

  • point_latitude
    (point)
    int64
    35 37 39 41 43

    array([35, 37, 39, 41, 43])

  • point_longitude
    (point)
    int64
    -100 -98 -96 -94 -92

    array([-100,  -98,  -96,  -94,  -92])

• Data variables: (2)
  • t2m
    (point)
    float32
    282.1 274.5 274.0 272.5 271.2

    GRIB_paramId :

    167

    GRIB_dataType :

    fc

    GRIB_numberOfPoints :

    1905141

    GRIB_typeOfLevel :

    heightAboveGround

    GRIB_stepUnits :

    1

    GRIB_stepType :

    instant

    GRIB_gridType :

    lambert

    GRIB_DxInMetres :

    3000.0

    GRIB_DyInMetres :

    3000.0

    GRIB_LaDInDegrees :

    38.5

    GRIB_Latin1InDegrees :

    38.5

    GRIB_Latin2InDegrees :

    38.5

    GRIB_LoVInDegrees :

    262.5

    GRIB_NV :

    0

    GRIB_Nx :

    1799

    GRIB_Ny :

    1059

    GRIB_cfName :

    air_temperature

    GRIB_cfVarName :

    t2m

    GRIB_gridDefinitionDescription :

    Lambert Conformal can be secant or tangent, conical or bipolar

    GRIB_iScansNegatively :

    0

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    1

    GRIB_latitudeOfFirstGridPointInDegrees :

    21.138123

    GRIB_latitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    237.280472

    GRIB_longitudeOfSouthernPoleInDegrees :

    0.0

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    2 metre temperature

    GRIB_parameterName :

    Temperature

    GRIB_parameterUnits :

    K

    GRIB_shortName :

    2t

    GRIB_stepRange :

    6

    GRIB_units :

    K

    long_name :

    2 metre temperature

    units :

    K

    standard_name :

    air_temperature

    grid_mapping :

    gribfile_projection

    array([282.0752, 274.4502, 274.0127, 272.5127, 271.2002], dtype=float32)

  • gribfile_projection
    (point)
    object
    None None None None None

    crs_wkt :

    PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["unknown",ELLIPSOID["unknown",6371229,0,LENGTHUNIT["metre",1,ID["EPSG",9001]]]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Lambert Conic Conformal (2SP)",ID["EPSG",9802]],PARAMETER["Latitude of false origin",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8821]],PARAMETER["Longitude of false origin",262.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8822]],PARAMETER["Latitude of 1st standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8823]],PARAMETER["Latitude of 2nd standard parallel",38.5,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8824]],PARAMETER["Easting at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8826]],PARAMETER["Northing at false origin",0,LENGTHUNIT["metre",1],ID["EPSG",8827]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]

    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

    projected_crs_name :

    unknown

    grid_mapping_name :

    lambert_conformal_conic

    standard_parallel :

    (38.5, 38.5)

    latitude_of_projection_origin :

    38.5

    longitude_of_central_meridian :

    262.5

    false_easting :

    0.0

    false_northing :

    0.0

    long_name :

    HRRR model grid projection

    array([None, None, None, None, None], dtype=object)

• Indexes: (1)
  • point
    PandasIndex

    PandasIndex(Int64Index([0, 1, 2, 3, 4], dtype='int64', name='point'))

• Attributes: (12)

  GRIB_edition :

  2

  GRIB_centre :

  kwbc

  GRIB_centreDescription :

  US National Weather Service - NCEP

  GRIB_subCentre :

  0

  Conventions :

  CF-1.7

  institution :

  US National Weather Service - NCEP

  model :

  hrrr

  product :

  sfc

  description :

  High-Resolution Rapid Refresh - CONUS

  remote_grib :

  https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20221205/conus/hrrr.t06z.wrfsfcf06.grib2

  local_grib :

  /home/blaylock/data/hrrr/20221205/subset_0cb2fd54__hrrr.t06z.wrfsfcf06.grib2

  searchString :

  TMP:2 m

Create a quick map

ds.herbie.plot()

cfgrib variable: t2m
GRIB_cfName air_temperature
GRIB_cfVarName t2m
GRIB_name 2 metre temperature
GRIB_units K
GRIB_typeOfLevel heightAboveGround

/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "t2m".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'
/home/blaylock/miniconda3/envs/herbie-dev/lib/python3.11/site-packages/metpy/xarray.py:382: UserWarning: More than one time coordinate present for variable "gribfile_projection".
  warnings.warn('More than one ' + axis + ' coordinate present for variable'

<GeoAxesSubplot: title={'left': 'Run: 06:00 UTC 05 Dec 2022 F06', 'center': 'HRRR 2 m\n', 'right': 'Valid: 12:00 UTC 05 Dec 2022'}>