Season track map — one basin, one season¶

Plot all storm tracks for the 2005 North Atlantic season as LineStrings, coloured by each storm's maximum Saffir-Simpson category, and annotate the strongest storm.

Uses geometry='track', which returns one LineString per storm with summary attributes (max_vmax_kt, min_mslp_hpa, max_category, ace). Needs pip install earthlens[tropycal].

Setup¶

First the imports. earthlens provides the unified EarthLens entry point; matplotlib draws the track map at the end.

In [ ]:

from pathlib import Path

import matplotlib.pyplot as plt

from earthlens import EarthLens

from pathlib import Path import matplotlib.pyplot as plt from earthlens import EarthLens

Output directory¶

Tropycal is a vector backend, so download() writes the storm tracks to disk as well as returning them. Create the folder it writes into.

In [ ]:

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

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

All storm tracks for the 2005 North Atlantic season¶

Build the request¶

We build the request first — the basin (variables), the season window, a bounding box over the North Atlantic, the hurdat best-track source, and geometry='track' so each storm comes back as a single LineString with summary attributes.

In [ ]:

season = EarthLens(
    variables=['north_atlantic'],
    data_source='tropycal',
    start='2005-06-01',
    end='2005-12-01',
    aoi=[-110.0, 0.0, -10.0, 60.0],
    source='hurdat',
    geometry='track',
    path=str(OUT_DIR),
)

season = EarthLens( variables=['north_atlantic'], data_source='tropycal', start='2005-06-01', end='2005-12-01', aoi=[-110.0, 0.0, -10.0, 60.0], source='hurdat', geometry='track', path=str(OUT_DIR), )

Download the tracks¶

download() is kept on its own line so the construct and the fetch read separately. The call is wrapped in a guard so the notebook degrades gracefully if the live best-track download is unavailable.

In [ ]:

tracks = None
try:
    tracks = season.download(progress_bar=False)
    print(len(tracks), 'storm tracks')
except Exception as exc:
    print(f'skipped live query: {type(exc).__name__}: {exc}')

tracks = None try: tracks = season.download(progress_bar=False) print(len(tracks), 'storm tracks') except Exception as exc: print(f'skipped live query: {type(exc).__name__}: {exc}')

Strongest storm of the season¶

Sorting the tracks by peak wind speed surfaces the season's strongest storm along with its minimum central pressure.

In [ ]:

if tracks is not None and len(tracks):
    strongest = tracks.sort_values('max_vmax_kt', ascending=False).iloc[0]
    print(
        strongest['name'],
        '- max wind',
        strongest['max_vmax_kt'],
        'kt,' ' min pressure',
        strongest['min_mslp_hpa'],
        'hPa',
    )

if tracks is not None and len(tracks): strongest = tracks.sort_values('max_vmax_kt', ascending=False).iloc[0] print( strongest['name'], '- max wind', strongest['max_vmax_kt'], 'kt,' ' min pressure', strongest['min_mslp_hpa'], 'hPa', )

Map all tracks coloured by max category¶

Each track is drawn as a LineString, coloured by the storm's maximum Saffir-Simpson category, with the strongest storm labelled at its centroid.

In [ ]:

if tracks is not None and len(tracks):
    fig, ax = plt.subplots(figsize=(10, 6))
    tracks.plot(ax=ax, column='max_category', cmap='YlOrRd', legend=True, linewidth=1.5)
    strongest = tracks.sort_values('max_vmax_kt', ascending=False).iloc[0]
    cx, cy = strongest.geometry.centroid.x, strongest.geometry.centroid.y
    ax.annotate(strongest['name'], xy=(cx, cy), fontsize=11, fontweight='bold')
    ax.set_title('North Atlantic storm tracks, 2005 (coloured by max category)')
    ax.set_xlabel('Longitude')
    ax.set_ylabel('Latitude')
    plt.tight_layout()
    plt.show()

if tracks is not None and len(tracks): fig, ax = plt.subplots(figsize=(10, 6)) tracks.plot(ax=ax, column='max_category', cmap='YlOrRd', legend=True, linewidth=1.5) strongest = tracks.sort_values('max_vmax_kt', ascending=False).iloc[0] cx, cy = strongest.geometry.centroid.x, strongest.geometry.centroid.y ax.annotate(strongest['name'], xy=(cx, cy), fontsize=11, fontweight='bold') ax.set_title('North Atlantic storm tracks, 2005 (coloured by max category)') ax.set_xlabel('Longitude') ax.set_ylabel('Latitude') plt.tight_layout() plt.show()