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Cayula-Cornillon#

Ideal Jet#

A idealized meandering jets with rings, as a 2D numpy array (embeded in Xarray).

[2]:

import matplotlib.pyplot as plt
import xarray as xr
from fronts_toolbox._fields import ideal_jet, sample
from fronts_toolbox.cayula_cornillon import cayula_cornillon_xarray

[3]:

# A colormap for overlaying the detected fronts
from matplotlib.colors import ListedColormap

cmap_fronts = ListedColormap([(0, 0, 0, 0), (0, 0, 0, 1)])

[4]:

sst = xr.DataArray(ideal_jet(), name="sst", dims=("lat", "lon"))
fronts = cayula_cornillon_xarray(sst)

[5]:

fig, ax = plt.subplots(dpi=150)

sst.plot.imshow(ax=ax, cmap="inferno", add_labels=False)
fronts.plot.imshow(
    ax=ax, cmap=cmap_fronts, add_labels=False, add_colorbar=False
)
ax.set_aspect("equal")
../_images/gallery_cayula-cornillon_5_0.png

ESA-SST-CCI / C3S Data#

SST of the North Atlantic, as a Dask array embeded in Xarray.

[6]:

sst = (
    sample("ESA-CCI-C3S")
    .analysed_sst.sel(lat=slice(15, 55), lon=slice(-82, -40))
    .chunk(lat=256, lon=256)
)
fronts = cayula_cornillon_xarray(sst)

fig, ax = plt.subplots(dpi=200)

sst.isel(time=0).plot.imshow(
    ax=ax, cmap="inferno", add_labels=False, center=False
)
fronts.isel(time=0).plot.imshow(
    ax=ax, cmap=cmap_fronts, add_labels=False, add_colorbar=False
)

ax.set_aspect("equal")

/home/docs/checkouts/readthedocs.org/user_builds/fronts-toolbox/envs/stable/lib/python3.11/site-packages/fronts_toolbox/_fields.py:236: FutureWarning: In a future version of xarray the default value for data_vars will change from data_vars='all' to data_vars=None. This is likely to lead to different results when multiple datasets have matching variables with overlapping values. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set data_vars explicitly.
  return xr.open_mfdataset(files, **kwargs)
../_images/gallery_cayula-cornillon_7_1.png

MODIS Data - Overlap#

An example off the Californian coast with a window step smaller than its size, ie there is overlap between windows.

[7]:

sst = (
    sample("MODIS")
    .sst4.isel(time=0)
    .sel(lat=slice(20, 15), lon=slice(-110, -100))
    .chunk(lat=256, lon=256)
)
fronts = cayula_cornillon_xarray(sst, window_size=32, window_step=8)

fig, axes = plt.subplots(1, 2, layout="constrained", dpi=200)

im_kw = dict(add_labels=False, cbar_kwargs=dict(location="top"))
sst.plot.imshow(ax=axes[0], cmap="inferno", center=False, **im_kw)
fronts.plot.imshow(ax=axes[1], cmap="viridis", **im_kw)

for ax in axes:
    ax.set_aspect("equal")

/home/docs/checkouts/readthedocs.org/user_builds/fronts-toolbox/envs/stable/lib/python3.11/site-packages/fronts_toolbox/_fields.py:236: FutureWarning: In a future version of xarray the default value for data_vars will change from data_vars='all' to data_vars=None. This is likely to lead to different results when multiple datasets have matching variables with overlapping values. To opt in to new defaults and get rid of these warnings now use `set_options(use_new_combine_kwarg_defaults=True) or set data_vars explicitly.
  return xr.open_mfdataset(files, **kwargs)
../_images/gallery_cayula-cornillon_9_1.png
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