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Description
While using xmitgcm.llcreader.ECCOPortalLLC4320Model() to load LLC4320 data, I encountered significant data anomalies in the Theta variable (sea surface temperature).`import xmitgcm.llcreader as llcreader
import matplotlib.pyplot as plt
import dask
import numpy as np
model = llcreader.ECCOPortalLLC4320Model()
dask.config.set(**{'array.slicing.split_large_chunks': False})
ds = model.get_dataset(
varnames=['Theta'],
k_levels=[0],
type='latlon',
iter_start=model.iter_start,
iter_stop=model.iter_start + model.iter_step,
read_grid=True
)
sst = ds.Theta.isel(time=0)
i_start, i_end = 1824, 4703
j_start, j_end = 4040, 6857
sst_cropped = sst.isel(i=slice(i_start, i_end), j=slice(j_start, j_end))
i_vals = np.arange(i_start, i_end)
j_vals = np.arange(j_start, j_end)
I, J = np.meshgrid(i_vals, j_vals)
plt.figure(figsize=(10, 6))
plt.pcolormesh(I, J, sst_cropped[0, :, :], cmap='coolwarm', shading='auto')
plt.colorbar(label='SST (°C)')
plt.title('SST (Theta k=0)')
plt.xlabel('i index')
plt.ylabel('j index')
plt.tight_layout()
plt.show()
`
- Python version: 3.11.5
- xmitgcm version: [0.5.2]
How can I solve this problem