Notebook for Camryn and Cassidy¶

In [2]:

import cmocean.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr

#from salishsea_tools import viz_tools

Looking at Horizontal Slices of SalishSeaCast for Sep 29, 2022¶

First lets open the file that has the physical tracers in (salinity called vosaline and temperature called votemper)

In [3]:

phys = xr.open_dataset('/results2/SalishSea/nowcast-green.201905/29sep22/SalishSea_1h_20220929_20220929_grid_T.nc')
phys

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/file_manager.py:201, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    200 try:
--> 201     file = self._cache[self._key]
    202 except KeyError:

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/lru_cache.py:55, in LRUCache.__getitem__(self, key)
     54 with self._lock:
---> 55     value = self._cache[key]
     56     self._cache.move_to_end(key)

KeyError: [<class 'netCDF4._netCDF4.Dataset'>, ('/results2/SalishSea/nowcast-green.201905/29sep22/SalishSea_1h_20220929_20220929_grid_T.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))]

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
Cell In [3], line 1
----> 1 phys = xr.open_dataset('/results2/SalishSea/nowcast-green.201905/29sep22/SalishSea_1h_20220929_20220929_grid_T.nc')
      2 phys

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/api.py:531, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, backend_kwargs, **kwargs)
    519 decoders = _resolve_decoders_kwargs(
    520     decode_cf,
    521     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)
    527     decode_coords=decode_coords,
    528 )
    530 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 531 backend_ds = backend.open_dataset(
    532     filename_or_obj,
    533     drop_variables=drop_variables,
    534     **decoders,
    535     **kwargs,
    536 )
    537 ds = _dataset_from_backend_dataset(
    538     backend_ds,
    539     filename_or_obj,
   (...)
    547     **kwargs,
    548 )
    549 return ds

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:555, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)
    534 def open_dataset(
    535     self,
    536     filename_or_obj,
   (...)
    551     autoclose=False,
    552 ):
    554     filename_or_obj = _normalize_path(filename_or_obj)
--> 555     store = NetCDF4DataStore.open(
    556         filename_or_obj,
    557         mode=mode,
    558         format=format,
    559         group=group,
    560         clobber=clobber,
    561         diskless=diskless,
    562         persist=persist,
    563         lock=lock,
    564         autoclose=autoclose,
    565     )
    567     store_entrypoint = StoreBackendEntrypoint()
    568     with close_on_error(store):

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:384, in NetCDF4DataStore.open(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose)
    378 kwargs = dict(
    379     clobber=clobber, diskless=diskless, persist=persist, format=format
    380 )
    381 manager = CachingFileManager(
    382     netCDF4.Dataset, filename, mode=mode, kwargs=kwargs
    383 )
--> 384 return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:332, in NetCDF4DataStore.__init__(self, manager, group, mode, lock, autoclose)
    330 self._group = group
    331 self._mode = mode
--> 332 self.format = self.ds.data_model
    333 self._filename = self.ds.filepath()
    334 self.is_remote = is_remote_uri(self._filename)

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:393, in NetCDF4DataStore.ds(self)
    391 @property
    392 def ds(self):
--> 393     return self._acquire()

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:387, in NetCDF4DataStore._acquire(self, needs_lock)
    386 def _acquire(self, needs_lock=True):
--> 387     with self._manager.acquire_context(needs_lock) as root:
    388         ds = _nc4_require_group(root, self._group, self._mode)
    389     return ds

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/contextlib.py:135, in _GeneratorContextManager.__enter__(self)
    133 del self.args, self.kwds, self.func
    134 try:
--> 135     return next(self.gen)
    136 except StopIteration:
    137     raise RuntimeError("generator didn't yield") from None

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/file_manager.py:189, in CachingFileManager.acquire_context(self, needs_lock)
    186 @contextlib.contextmanager
    187 def acquire_context(self, needs_lock=True):
    188     """Context manager for acquiring a file."""
--> 189     file, cached = self._acquire_with_cache_info(needs_lock)
    190     try:
    191         yield file

File ~/opt/anaconda3/envs/analysis-camryn/lib/python3.10/site-packages/xarray/backends/file_manager.py:207, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    205     kwargs = kwargs.copy()
    206     kwargs["mode"] = self._mode
--> 207 file = self._opener(*self._args, **kwargs)
    208 if self._mode == "w":
    209     # ensure file doesn't get overridden when opened again
    210     self._mode = "a"

File src/netCDF4/_netCDF4.pyx:2463, in netCDF4._netCDF4.Dataset.__init__()

File src/netCDF4/_netCDF4.pyx:2026, in netCDF4._netCDF4._ensure_nc_success()

FileNotFoundError: [Errno 2] No such file or directory: b'/results2/SalishSea/nowcast-green.201905/29sep22/SalishSea_1h_20220929_20220929_grid_T.nc'

And look at the specific variables. Note the full names and the units

In [5]:

phys.vosaline

In [6]:

phys.votemper

A naive plot, note that we have chosen the second time step (1 == 01:30 UTC) and the near surface (0 == 0.5 m depth)

In [8]:

phys.vosaline[1, 0].plot();

Okay but we could do better.

shape is distorted
where the land is, we have 0 values, except where we are not computing which are NaN's.

In [14]:

# set up a proper set of axes and chose a better size
fig, ax = plt.subplots(1, 1, figsize=(5, 9))
phys.vosaline[1, 0].plot(ax=ax);
# fix the aspect ratio
viz_tools.set_aspect(ax);

In [15]:

# open the mesh mask and use it to mask the land
mesh = xr.open_dataset('/home/sallen/MEOPAR/grid/mesh_mask202108.nc')
# the mask is 1 where there is water, we want the opposite.  The meshmask has an extra dimension, hence the [0]
tmask = 1 - mesh.tmask[0]

In [19]:

fig, ax = plt.subplots(1, 1, figsize=(5, 9))
salinity = np.ma.masked_array(phys.vosaline[1, 0], mask=tmask[0])
ax.pcolormesh(salinity)
viz_tools.set_aspect(ax);

In [23]:

# note that switching to pcolormesh from xarray we lost our colorbar and our title
# Here I will also improve the colormap
cmap = cm.haline
cmap.set_bad('gray')
fig, ax = plt.subplots(1, 1, figsize=(5, 9))
salinity = np.ma.masked_array(phys.vosaline[1, 0], mask=tmask[0])
colours = ax.pcolormesh(salinity, cmap=cmap)
cb = fig.colorbar(colours, ax=ax)
cb.set_label('Salinity (g/kg)')
viz_tools.set_aspect(ax);

In [38]:

# Zoom in on Rosario Strait and the Nooksack River

In [26]:

fig, ax = plt.subplots(1, 1, figsize=(7, 7))
colours = ax.pcolormesh(salinity[280:380, 280:380], cmap=cmap)
cb = fig.colorbar(colours, ax=ax)
cb.set_label('Salinity (g/kg)')
viz_tools.set_aspect(ax);

In [39]:

# Now do a vertical cross-section through Rosario Strait and into Bellingham Bay

In [40]:

fig, ax = plt.subplots(1, 1, figsize=(15, 5))
salinity = np.ma.masked_array(phys.vosaline[1, :, 305, 300:380], mask=tmask[:, 305, 300:380])
colours = ax.pcolormesh(phys.nav_lon[305, 300:380+1], phys.deptht, salinity[:39], cmap=cmap)
ax.set_ylim(0, 150)
ax.invert_yaxis();
cb = fig.colorbar(colours, ax=ax)
cb.set_label('Salinity (g/kg)');

In [41]:

# Velocity across the cross-section

In [43]:

vvel = xr.open_dataset('/results2/SalishSea/nowcast-green.201905/29sep22/SalishSea_1h_20220929_20220929_grid_V.nc')
vmask = 1 - mesh.vmask[0]

In [48]:

fig, ax = plt.subplots(1, 1, figsize=(15, 5))
cmap = cm.curl
cmap.set_bad('grey')
northvel = np.ma.masked_array(vvel.vomecrty[1, :, 305, 300:380], mask=vmask[:, 305, 300:380])
colours = ax.pcolormesh(vvel.nav_lon[305, 300:380+1], vvel.depthv, northvel[:39], cmap=cmap, vmax=1.0, vmin=-1.0)
ax.set_ylim(0, 150)
ax.invert_yaxis();
cb = fig.colorbar(colours, ax=ax)
cb.set_label('Velocity (m/s)');

In [47]:

# and six hours later
fig, ax = plt.subplots(1, 1, figsize=(15, 5))
northvel = np.ma.masked_array(vvel.vomecrty[7, :, 305, 300:380], mask=vmask[:, 305, 300:380])
colours = ax.pcolormesh(vvel.nav_lon[305, 300:380+1], vvel.depthv, northvel[:39], cmap=cmap, vmax=1.0, vmin=-1.0)
ax.set_ylim(0, 150)
ax.invert_yaxis();
cb = fig.colorbar(colours, ax=ax)
cb.set_label('Velocity (m/s)');

And Looking at the Rivers¶

In [50]:

# file for 2017 Sep 29 (Sorry, its in my space not on /results)
river = xr.open_dataset('/home/sallen/MEOPAR/tools/I_ForcingFiles/Rivers/ncfiles/R202108Dailies_y2017m09d29.nc')

In [51]:

# get the bathymetry file
bathy = xr.open_dataset('/home/sallen/MEOPAR/grid/bathymetry_202108.nc')

In [55]:

# exclude Fraser off the edge
jmax = 394
jj = range(jmax)
ii = range(898)
jjm, iim = np.meshgrid(jj, ii)
fluxarray = np.array(river.rorunoff[0, :, :jmax])
fig, ax = plt.subplots(1, 1, figsize=(4, 9))
ax.contourf(bathy.Bathymetry[:, :jmax], cmap='winter_r')
      
ax.scatter(jjm[fluxarray>0], iim[fluxarray>0], s=fluxarray[fluxarray>0]*1000, color='tab:orange')
                      
fig.suptitle(f'September 29, 2017 River Flux Excluding the Fraser River');

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