Short-range land surface (ldasout)¶

A live pull of one recent short_range land file — the gridded Noah-MP land-surface output on the 1 km CONUS grid (~30 MB): soil moisture, snow water equivalent, snow depth, accumulated ET. Unlike chrtout, ldasout is a raster product.

Setup¶

Imports for the National Water Model pull: EarthLens is the unified entry point, and tempfile / Path give us a scratch directory for the downloaded NetCDF.

In [ ]:

import datetime as dt
import tempfile
from pathlib import Path

from earthlens import EarthLens

import datetime as dt import tempfile from pathlib import Path from earthlens import EarthLens

Pick a cycle and a scratch directory¶

We target a model cycle from three days ago (recent enough to still be in the bucket) and write the file into a fresh temporary directory.

In [ ]:

cycle_date = (dt.datetime.now() - dt.timedelta(days=3)).strftime('%Y-%m-%d')
out_dir = Path(tempfile.mkdtemp(prefix='nwm_land_'))

cycle_date = (dt.datetime.now() - dt.timedelta(days=3)).strftime('%Y-%m-%d') out_dir = Path(tempfile.mkdtemp(prefix='nwm_land_'))

Build the NWM request¶

Configure a short_range ldasout request for two land variables (SOIL_M, SNEQV) at cycle 0, forecast step 1, over the full grid. The constructor only describes the request — nothing is fetched yet.

In [ ]:

nwm = EarthLens(
    data_source="nwm",
    start=cycle_date,
    end=cycle_date,
    dataset='ldasout',
    variables=['SOIL_M', 'SNEQV'],
    aoi=[-180, -90, 180, 90],
    configuration='short_range',
    cycles=[0],
    steps=[1],
    path=str(out_dir),
)
print('OUTPUT_KIND:', nwm.OUTPUT_KIND)  # raster

nwm = EarthLens( data_source="nwm", start=cycle_date, end=cycle_date, dataset='ldasout', variables=['SOIL_M', 'SNEQV'], aoi=[-180, -90, 180, 90], configuration='short_range', cycles=[0], steps=[1], path=str(out_dir), ) print('OUTPUT_KIND:', nwm.OUTPUT_KIND) # raster

Download the file¶

download() fetches the gridded NetCDF to out_dir and returns the list of written paths; we print each name and its size.

In [ ]:

paths = nwm.download(progress_bar=False)
for p in paths:
    print(p.name, f'{p.stat().st_size / 1e6:.1f} MB')

paths = nwm.download(progress_bar=False) for p in paths: print(p.name, f'{p.stat().st_size / 1e6:.1f} MB')

The file is the native gridded NetCDF. Cropping it to a bounding box is a read (pyramids PY-G / pyramids.netcdf.NetCDF), so the MVP fetches the whole CONUS grid.

In [ ]:

assert paths, 'expected one land file for a recent short_range cycle'

assert paths, 'expected one land file for a recent short_range cycle'