04. Trajectories on the map - Argo · tutorial / tutorial

An Argo float drifts for years. Mapping the track gives intuition about the regional circulation and the spatial representativeness of the profiles.

%run _style.py
import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from argopy import DataFetcher
from _style import PALETTE

ds_point = DataFetcher(src='erddap', mode='standard').float(5905141).to_xarray()
ds = ds_point.argo.point2profile()

lons = ds.LONGITUDE.values
lats = ds.LATITUDE.values
times = ds.TIME.values
print(f'{len(lons)} cycles · from {str(times.min())[:10]} a {str(times.max())[:10]}')
print(f'lat {lats.min():.1f} a {lats.max():.1f} · lon {lons.min():.1f} a {lons.max():.1f}')

312 cycles · from 2017-10-24 a 2022-01-13
lat -36.5 a -32.4 · lon -47.6 a -25.3

Cartopy map¶

proj = ccrs.PlateCarree()
fig, ax = plt.subplots(figsize=(11, 8), subplot_kw={'projection': proj})

pad = 4
ax.set_extent([lons.min()-pad, lons.max()+pad,
               lats.min()-pad, lats.max()+pad], crs=proj)

ax.add_feature(cfeature.LAND, color=PALETTE['land'], zorder=1)
ax.add_feature(cfeature.COASTLINE, lw=0.5, color=PALETTE['deep'])
ax.add_feature(cfeature.BORDERS, lw=0.3, color=PALETTE['gray'], alpha=0.6)
ax.gridlines(draw_labels=True, alpha=0.25, lw=0.4, color=PALETTE['gray'])

ax.plot(lons, lats, '-', color=PALETTE['blue'], lw=0.8, alpha=0.6, transform=proj)

t_num = (times - times.min()) / np.timedelta64(1, 'D')
sc = ax.scatter(lons, lats, c=t_num, cmap='viridis', s=15,
                edgecolor='white', lw=0.25, transform=proj)

ax.plot(lons[0], lats[0], 'o', color=PALETTE['warm'], ms=11,
        markeredgecolor='white', mew=1.5, label='deployed', transform=proj)
ax.plot(lons[-1], lats[-1], 's', color=PALETTE['orange'], ms=11,
        markeredgecolor='white', mew=1.5, label='last cycle', transform=proj)

plt.colorbar(sc, ax=ax, label='days since deployment', shrink=0.7)
ax.legend(loc='upper left', frameon=False)
ax.set_title(f'Trajectory of float 5905141. {len(lons)} ciclos', loc='left')
plt.tight_layout()
plt.show()

/Users/daniela/Documents/argo-tutorial/.venv/lib/python3.12/site-packages/cartopy/mpl/feature_artist.py:143: UserWarning: facecolor will have no effect as it has been defined as "never".
  warnings.warn('facecolor will have no effect as it has been '

Dynamical context¶

This float was deployed in the South Atlantic, a region dominated by the Brazil-Malvinas confluence: the Brazil Current carries warm, salty subtropical water southward; the Malvinas Current carries cold, fresh subantarctic water northward. Their encounter forms one of the most energetic ocean fronts on the planet.

The track reflects this dynamics: during the ~9 days the float drifts at 1000 m, the local current advects it. Over months you see loops, recirculations, and eastward transport by the South Atlantic Current.

Multiple floats in a region¶

For decent spatial coverage, download all floats active in a box:

box = [-60, -30, -45, -25, 0, 100, '2022-01-01', '2022-12-31']
ds_reg = DataFetcher(src='erddap', mode='standard').region(box).to_xarray()
ds_reg_prof = ds_reg.argo.point2profile()

wmos = np.unique(ds_reg_prof.PLATFORM_NUMBER.values)
print(f'{len(wmos)} distinct floats · {ds_reg_prof.sizes["N_PROF"]} total profiles')

97 distinct floats · 2090 total profiles

fig, ax = plt.subplots(figsize=(11, 8), subplot_kw={'projection': proj})
ax.set_extent([-62, -28, -48, -22], crs=proj)
ax.add_feature(cfeature.LAND, color=PALETTE['land'], zorder=1)
ax.add_feature(cfeature.COASTLINE, lw=0.5, color=PALETTE['deep'])
ax.add_feature(cfeature.BORDERS, lw=0.3, color=PALETTE['gray'], alpha=0.6)
ax.gridlines(draw_labels=True, alpha=0.25, lw=0.4, color=PALETTE['gray'])

cmap = plt.get_cmap('tab20')
for k, wmo in enumerate(wmos):
    m = ds_reg_prof.PLATFORM_NUMBER == wmo
    lo = ds_reg_prof.LONGITUDE.where(m, drop=True).values
    la = ds_reg_prof.LATITUDE.where(m, drop=True).values
    color = cmap(k % 20)
    ax.plot(lo, la, '-', color=color, lw=0.35, alpha=0.7, transform=proj)
    ax.scatter(lo, la, color=color, s=2.5, alpha=0.8, transform=proj)

ax.set_title(f'Active Argo floats in the South Atlantic. 2022 ({len(wmos)} floats)', loc='left')
plt.tight_layout()
plt.show()

/Users/daniela/Documents/argo-tutorial/.venv/lib/python3.12/site-packages/cartopy/mpl/feature_artist.py:143: UserWarning: facecolor will have no effect as it has been defined as "never".
  warnings.warn('facecolor will have no effect as it has been '

This shows the program’s typical coverage: the South Atlantic is reasonably sampled, with floats spread out and concentrated in active areas like the confluence.

Summary¶

LONGITUDE, LATITUDE, TIME live at the profile level (not the pressure level).
cartopy for maps: subplot_kw={'projection': ccrs.PlateCarree()} and transform=ccrs.PlateCarree() on all plots.
For multiple floats, group by PLATFORM_NUMBER.
The track with scatter colored by time shows the regional dynamics.