🖥️ MITgcm tutorial#
This tutorial will show how to run a 3D simulation with output from the MITgcm model. The key thing about MITgcm is that its output is on a C-grid, which means that the U and V velocity components are not defined at the same location as the particle positions. Parcels has built-in functionality to deal with C-grid data. See also the Nemo tutorial for another example of C-grid data.
import matplotlib.pyplot as plt
import numpy as np
import parcels
import parcels.tutorial
ds_fields = parcels.tutorial.open_dataset(
"MITgcm_example_data/mitgcm_UV_surface_zonally_reentrant"
)
We can use a combination of parcels.convert.mitgcm_to_sgrid() and parcels.FieldSet.from_sgrid_conventions() to read in the data. See below for an example.
ds_fset = parcels.convert.mitgcm_to_sgrid(
fields={"U": ds_fields.UVEL, "V": ds_fields.VVEL}, coords=ds_fields
)
fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
INFO: Depth dimension appears to be decreasing upward (i.e., from positive to negative values). Swapping depth dimension to be increasing upward for Parcels simulation.
We can then run a simulation on this zonally re-entrant dataset as follows:
perc = np.arange(5, 100, 10)
lon_vals = np.percentile(fieldset.UV.grid.lon, perc)
lat_vals = np.percentile(fieldset.UV.grid.lat, perc)
X, Y = np.meshgrid(
lon_vals,
lat_vals,
)
Z = np.zeros_like(X)
def DeleteParticle(particles, fieldset):
any_error = particles.state >= 50
particles[any_error].state = parcels.StatusCode.Delete
pset = parcels.ParticleSet(fieldset=fieldset, x=X, y=Y, z=Z)
outputfile = parcels.ParticleFile(
path="mitgcm_particles.parquet",
outputdt=np.timedelta64(5000, "s"),
)
pset.execute(
[parcels.kernels.AdvectionRK2, DeleteParticle],
runtime=np.timedelta64(10, "D"),
dt=np.timedelta64(1, "h"),
output_file=outputfile,
)
Show code cell output
Hide code cell output
INFO: Output files are stored in mitgcm_particles.parquet
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And make a simple plot of the particle trajectories:
df = parcels.read_particlefile("mitgcm_particles.parquet")
for traj in df.partition_by("particle_id", maintain_order=True):
plt.plot(traj["x"], traj["y"], ".-")
plt.show()
