HRRR

This tutorial shows you how to download HRRR data from Amazon (and other sources) with the Herbie Python package.

Data Sources

prioriy=	Data source	Archive Duration
"aws"	Amazon Web Services	2014-07-30 to present
"nomads"	NOMADS	Yesterday and today
"google"	Google Cloud Platform	2014-07-30 to present
"azure"	Microsoft Azure	2021-03-21 to present
"pando"	University of Utah Pando archive	varies

Model Initialization

Model cyles every hour.

Forecast Hour

For the most recent version of HRRR…

fxx=	Forecast lead time
0 through 48, step=1	available for runs initialized at 00z, 06z, 12z, 18z
0 through 18, step=1	available for runs initialized at all other hours.

Products

product=	Product Description
"sfc"	surface fields
"prs"	pressure levels
"nat"	native levels
"subh"	subhourly products

from herbie import Herbie
from toolbox import EasyMap, pc
from paint.standard2 import cm_tmp

import matplotlib.pyplot as plt
import cartopy.crs as ccrs

H = Herbie(
    "2021-07-19",
    model="hrrr",
    product="sfc",
    fxx=0,
)

✅ Found ┊ model=hrrr ┊ product=sfc ┊ 2021-Jul-19 00:00 UTC F00 ┊ GRIB2 @ aws ┊ IDX @ aws

# Show available products
H.PRODUCTS

{'sfc': '2D surface level fields; 3-km resolution',
 'prs': '3D pressure level fields; 3-km resolution',
 'nat': 'Native level fields; 3-km resolution',
 'subh': 'Subhourly grids; 3-km resolution'}

ds = H.xarray("TMP:2 m above")
ds

<xarray.Dataset>
Dimensions:              (y: 1059, x: 1799)
Coordinates:
    time                 datetime64[ns] 2021-07-19
    step                 timedelta64[ns] 00:00:00
    heightAboveGround    float64 2.0
    latitude             (y, x) float64 ...
    longitude            (y, x) float64 ...
    valid_time           datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
    t2m                  (y, x) float32 ...
    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:              C:\Users\blaylock\data\hrrr\20210719\subset_6eef...
    search:            TMP:2 m above

xarray.Dataset

• Dimensions:
  • y: 1059
  • x: 1799
• Coordinates: (6)
  • time
    ()
    datetime64[ns]
    2021-07-19

    long_name :

    initial time of forecast

    standard_name :

    forecast_reference_time

    array('2021-07-19T00:00:00.000000000', 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.)

  • latitude
    (y, x)
    float64
    ...

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    [1905141 values with dtype=float64]

  • longitude
    (y, x)
    float64
    ...

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    [1905141 values with dtype=float64]

  • valid_time
    ()
    datetime64[ns]
    ...

    standard_name :

    time

    long_name :

    time

    [1 values with dtype=datetime64[ns]]

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

    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 :

    0

    GRIB_units :

    K

    long_name :

    2 metre temperature

    units :

    K

    standard_name :

    air_temperature

    grid_mapping :

    gribfile_projection

    [1905141 values with 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.20210719/conus/hrrr.t00z.wrfsfcf00.grib2

  local_grib :

  C:\Users\blaylock\data\hrrr\20210719\subset_6eeffd54__hrrr.t00z.wrfsfcf00.grib2

  search :

  TMP:2 m above

ax = EasyMap("50m", crs=ds.herbie.crs, figsize=[10, 8]).STATES().ax

p = ax.pcolormesh(
    ds.longitude,
    ds.latitude,
    ds.t2m,
    transform=pc,
    **cm_tmp(units="K").cmap_kwargs,
)
plt.colorbar(
    p,
    ax=ax,
    orientation="horizontal",
    pad=0.01,
    shrink=0.8,
    **cm_tmp(units="K").cbar_kwargs,
)

ax.set_title(
    f"{ds.model.upper()}: {H.product_description}\nValid: {ds.valid_time.dt.strftime('%H:%M UTC %d %b %Y').item()}",
    loc="left",
)
ax.set_title(ds.t2m.GRIB_name, loc="right")

Text(1.0, 1.0, '2 metre temperature')