PACE ocean-colour chlorophyll (NASA Earthdata)¶

Download a daily PACE OCI Level-3 mapped chlorophyll-a granule from the OB.DAAC and map it on a log scale. This is a gridded raster product, fetched through one Earthdata Login.

Live query — needs the [earthdata] extra and EDL credentials. Each fetch and plot step is wrapped in a try/except so the notebook degrades gracefully (nbval-lax safe) when run offline or without credentials.

Setup¶

Import the unified EarthLens entry point and prepare a local output directory for the downloaded granule.

In [ ]:

from pathlib import Path

from earthlens import EarthLens

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

from pathlib import Path from earthlens import EarthLens OUT_DIR = Path('earthdata_output') OUT_DIR.mkdir(exist_ok=True)

1 · Download the chlorophyll granule¶

Earthdata is a raster backend, so download() writes the granule(s) to disk and returns the list of written paths. We build the request first — the PACE OCI Level-3 mapped chlorophyll dataset, the chlor_a variable, a single day, and a global-ish bounding box.

In [ ]:

ocean = EarthLens(
    data_source='earthdata',
    dataset='PACE_OCI_L3M_CHL_31',
    variables=['chlor_a'],
    start='2024-06-01',
    end='2024-06-01',
    aoi=[-180.0, -60.0, 180.0, 60.0],
    path=str(OUT_DIR),
)

ocean = EarthLens( data_source='earthdata', dataset='PACE_OCI_L3M_CHL_31', variables=['chlor_a'], start='2024-06-01', end='2024-06-01', aoi=[-180.0, -60.0, 180.0, 60.0], path=str(OUT_DIR), )

The download is run in its own step, wrapped in a try/except so the notebook keeps going (printing a skip message) when EDL credentials or the [earthdata] extra are unavailable.

In [ ]:

paths = None
try:
    paths = ocean.download(progress_bar=False)
    print(len(paths), 'granule(s):', [Path(p).name for p in paths])
except Exception as exc:
    print(f'skipped live query: {type(exc).__name__}: {exc}')

paths = None try: paths = ocean.download(progress_bar=False) print(len(paths), 'granule(s):', [Path(p).name for p in paths]) except Exception as exc: print(f'skipped live query: {type(exc).__name__}: {exc}')

2 · Map the chlorophyll field¶

Open the granule with xarray and plot chlor_a on a logarithmic colour scale — chlorophyll spans several orders of magnitude, so LogNorm keeps both clear open-ocean water and productive coastal blooms legible. The plot is guarded by if paths: and its own try/except so it is skipped cleanly when the download did not run.

In [ ]:

if paths:
    try:
        import matplotlib.pyplot as plt
        import xarray as xr
        from matplotlib.colors import LogNorm

        ds = xr.open_dataset(paths[0])
        chl = ds['chlor_a']
        fig, ax = plt.subplots(figsize=(10, 5))
        chl.plot(ax=ax, norm=LogNorm(vmin=0.01, vmax=20), cmap='viridis')
        ax.set_title('PACE OCI chlorophyll-a, 2024-06-01')
        plt.tight_layout()
        plt.show()
    except Exception as exc:
        print(f'plot step skipped: {type(exc).__name__}: {exc}')

if paths: try: import matplotlib.pyplot as plt import xarray as xr from matplotlib.colors import LogNorm ds = xr.open_dataset(paths[0]) chl = ds['chlor_a'] fig, ax = plt.subplots(figsize=(10, 5)) chl.plot(ax=ax, norm=LogNorm(vmin=0.01, vmax=20), cmap='viridis') ax.set_title('PACE OCI chlorophyll-a, 2024-06-01') plt.tight_layout() plt.show() except Exception as exc: print(f'plot step skipped: {type(exc).__name__}: {exc}')