RRFS 🅱#

BETA

The Rapid Refresh Forecast System (RRFS) is undergoing rapid development. There are some prototype products and forecasts available on the cloud on AWS. Some files have an index file, others do not.

[1]:

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

import matplotlib.pyplot as plt

[5]:

H = Herbie(
    "2024-08-15 12:00",
    model="rrfs",
    fxx=1,
    member="control",
    domain="conus",
    # product="testbed",
)

H.SOURCES

✅ Found ┊ model=rrfs ┊ product=prslev ┊ 2024-Aug-15 12:00 UTC F01 ┊ GRIB2 @ aws_0 ┊ IDX @ aws_0

[5]:

{'aws_0': 'https://noaa-rrfs-pds.s3.amazonaws.com/rrfs_a/rrfs_a.20240815/12/control/rrfs.t12z.prslev.f001.conus.grib2',
 'aws_1': 'https://noaa-rrfs-pds.s3.amazonaws.com/rrfs_a/rrfs_a.20240815/12/control/rrfs.t12z.prslev.f001.conus_3km.grib2'}

[3]:

H.help()

╭─ Herbie ────────────────────────────────
│ Help for model='rrfs'
│
│ Rapid Refresh Forecast System (RRFS) Ensemble
│  aws product description: https://registry.opendata.aws/noaa-rrfs/
│
│ Herbie(date, model='rrfs', ...)
│
│ fxx : int
│ product : {"prs", "nat", "testbed", "ififip"}
│ member : {"control", int}
│ domain : {"conus", "alaska", "hawaii", "puerto rico", None}
│
│ If product="natlev', then domain must be None
│
╰─────────────────────────────────────────

[6]:

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

[7]:

ax = EasyMap("50m", crs=ds.herbie.crs, figsize=[10, 8]).STATES().ax
p = ax.pcolormesh(
    ds.longitude,
    ds.latitude,
    ds.t2m - 273.15,
    transform=pc,
    **paint.NWSTemperature.kwargs2,
)
plt.colorbar(
    p, ax=ax, orientation="horizontal", pad=0.05, **paint.NWSTemperature.cbar_kwargs2
)

ax.set_title(
    f"{ds.t2m.GRIB_name}\n{ds.time.dt.strftime('%H:%M UTC %d %b %Y').item()} F{int(ds.step.dt.total_seconds() / 60 / 60):02d}",
    loc="right",
)
ax.set_title(
    f"{H.model.upper()}: member={H.member} {H.product_description}", loc="left"
)

[7]:

Text(0.0, 1.0, 'RRFS: member=control ')

../../_images/gallery_noaa_models_rrfs_5_1.png

Other products#

Reading natlev data into xarray causes my kernel to crash

[8]:

H = Herbie("2024-06-22", model="rrfs", product="natlev", member="control", domain=None)
H

✅ Found ┊ model=rrfs ┊ product=natlev ┊ 2024-Jun-22 00:00 UTC F00 ┊ GRIB2 @ aws_0 ┊ IDX @ aws_0

[8]:

▌▌Herbie RRFS model natlev product initialized 2024-Jun-22 00:00 UTC F00 ┊ source=aws_0

[9]:

H.inventory("TMP:5 hybrid")

[9]:

	grib_message	start_byte	end_byte	range	reference_time	valid_time	variable	level	forecast_time	?	??	search_this
91	92	467606623	478003639.0	467606623-478003639	2024-06-22	2024-06-22	TMP	5 hybrid level	anl	NaN	NaN	:TMP:5 hybrid level:anl:nan

[10]:

ds = H.xarray("TMP:5 hybrid")
ds

[11]:

ds.t.plot()

[11]:

<matplotlib.collections.QuadMesh at 0x7f57e651ce60>

../../_images/gallery_noaa_models_rrfs_10_1.png

The Kernel crashed while executing code in the current cell or a previous cell.

Please review the code in the cell(s) to identify a possible cause of the failure.

Click <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info.

View Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details.

[12]:

ax = EasyMap("50m", crs=ds.herbie.crs, figsize=[10, 8]).STATES().ax
p = ax.pcolormesh(
    ds.longitude,
    ds.latitude,
    ds.t - 273.15,
    transform=pc,
    **paint.NWSTemperature.kwargs2,
)
plt.colorbar(
    p, ax=ax, orientation="horizontal", pad=0.05, **paint.NWSTemperature.cbar_kwargs2
)

ax.set_title(
    f"{ds.t.GRIB_name}\n{ds.time.dt.strftime('%H:%M UTC %d %b %Y').item()} F{int(ds.step.dt.total_seconds() / 60 / 60):02d}",
    loc="right",
)
ax.set_title(
    f"{H.model.upper()}: member={H.member} {H.product_description}", loc="left"
)