SHIPS intensity forecast — Hurricane Ian (2022)¶

Fetch SHIPS statistical intensity-forecast guidance (product='ships') for one forecast cycle of Hurricane Ian and plot the forecast intensity curve.

ships is storm + forecast-cycle keyed (variables=[storm id], ships_time=<cycle>) and is tabular: download() returns a pandas DataFrame (one row per forecast hour), not a FeatureCollection.

Needs pip install earthlens[tropycal]; SHIPS guidance is archived for recent storms.

In [ ]:

from pathlib import Path

from earthlens import EarthLens

OUT_DIR = Path('tropycal_output')
OUT_DIR.mkdir(exist_ok=True)

ships = None
try:
    ships = EarthLens(
        data_source='tropycal',
        product='ships',
        variables=['AL092022'],
        basin='north_atlantic',
        source='hurdat',
        ships_time='2022-09-27 00:00',
        start='2022-09-20',
        end='2022-10-01',
        aoi=[-180, -90, 180, 90],
        path=str(OUT_DIR),
    ).download(progress_bar=False)
    print('SHIPS table shape:', None if ships is None else ships.shape)
except Exception as exc:
    print(f'skipped live query: {type(exc).__name__}: {exc}')

from pathlib import Path from earthlens import EarthLens OUT_DIR = Path('tropycal_output') OUT_DIR.mkdir(exist_ok=True) ships = None try: ships = EarthLens( data_source='tropycal', product='ships', variables=['AL092022'], basin='north_atlantic', source='hurdat', ships_time='2022-09-27 00:00', start='2022-09-20', end='2022-10-01', aoi=[-180, -90, 180, 90], path=str(OUT_DIR), ).download(progress_bar=False) print('SHIPS table shape:', None if ships is None else ships.shape) except Exception as exc: print(f'skipped live query: {type(exc).__name__}: {exc}')

Inspect the guidance table¶

In [ ]:

if ships is not None and len(ships):
    display(
        ships[['storm_id', 'forecast_init', 'fhr', 'vmax_noland_kt', 'shear_kt']].head()
    )

if ships is not None and len(ships): display( ships[['storm_id', 'forecast_init', 'fhr', 'vmax_noland_kt', 'shear_kt']].head() )

Plot the forecast intensity curve¶

In [ ]:

if ships is not None and len(ships):
    import matplotlib.pyplot as plt

    fig, ax = plt.subplots(figsize=(8, 5))
    ax.plot(ships['fhr'], ships['vmax_noland_kt'], marker='o')
    ax.set_title('Ian (2022) SHIPS forecast intensity — init 2022-09-27 00z')
    ax.set_xlabel('Forecast hour')
    ax.set_ylabel('Max wind (kt)')
    ax.grid(True, alpha=0.3)
    plt.tight_layout()
    plt.show()

if ships is not None and len(ships): import matplotlib.pyplot as plt fig, ax = plt.subplots(figsize=(8, 5)) ax.plot(ships['fhr'], ships['vmax_noland_kt'], marker='o') ax.set_title('Ian (2022) SHIPS forecast intensity — init 2022-09-27 00z') ax.set_xlabel('Forecast hour') ax.set_ylabel('Max wind (kt)') ax.grid(True, alpha=0.3) plt.tight_layout() plt.show()