In [1]:
import netCDF4 as nc
import numpy as np
import matplotlib.pyplot as plt
import datetime
from nowcast import analyze
from salishsea_tools import viz_tools, psu_tools, grid_tools, tidetools
import conversion, pressure
import glob
%matplotlib inline
In [2]:
grid = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')
mesh_mask = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/mesh_mask_SalishSea2.nc')
In [3]:
def conversion_in_region_and_time(jss,iss, d1, d2, grid, mesh_mask):
#load grids
bathy, lons, lats = tidetools.get_bathy_data(grid)
bathy = bathy[jss[0]:jss[-1]+1, iss[0]:iss[-1]+1]
lons = lons[jss[0]:jss[-1]+1, iss[0]:iss[-1]+1]
lats = lats[jss[0]:jss[-1]+1, iss[0]:iss[-1]+1]
grids = conversion.load_grids_subdomain(mesh_mask, jss, iss)
# load files
numdays = (d2-d1).days
dates = [d1 + datetime.timedelta(days=num)
for num in range(0, numdays+1)]
dates.sort()
filest = []
filesu = []
filesv = []
for d in dates:
dtstr =d.strftime('%Y%m%d')
filest.append(glob.glob('/results/SalishSea/nowcast/*/SalishSea_1h_{}_{}_grid_T.nc'.format(dtstr,dtstr))[0])
filesu.append(glob.glob('/results/SalishSea/nowcast/*/SalishSea_1h_{}_{}_grid_U.nc'.format(dtstr,dtstr))[0])
filesv.append(glob.glob('/results/SalishSea/nowcast/*/SalishSea_1h_{}_{}_grid_V.nc'.format(dtstr,dtstr))[0])
# data
sal, time = analyze.combine_files(filest,'vosaline',np.arange(40), jss, iss)
temp, time = analyze.combine_files(filest,'votemper',np.arange(40),jss, iss)
v, time = analyze.combine_files(filesv,'vomecrty',np.arange(40),jss, iss)
u, time = analyze.combine_files(filesu,'vozocrtx',np.arange(40),jss, iss)
ssh, time = analyze.combine_files(filest,'sossheig','None', jss, iss)
rho = psu_tools.calculate_density(temp,sal)
wb = conversion.barotropic_w(u, v, ssh, bathy, grids)
# time dependent grids
grids_t = grid_tools.calculate_time_dependent_grid(grids['e3t_0'][0,...],
grids['tmask'][0,...],
ssh,
{'e3t_0': grids['e3t_0'],
'gdept_0': grids['gdept_0']} )
#pressure
p = pressure.hydrostatic_pressure(rho,
grids_t['e3t_t'],
grids_t['gdept_t'],
grids['tmask'])
p = p - p.mean(axis=0)
p_it = pressure.internal_tide_pressure(p,
grids_t['e3t_t'],
grids['tmask'])
# conversion
mbathy = mesh_mask.variables['mbathy'][0,jss[0]:jss[-1]+1,iss[0]:iss[-1]+1]
CT = conversion.conversion_CT(wb, p_it, mbathy)
return CT, lons, lats,
Time period¶
In [4]:
d1=datetime.datetime(2015,1,1)
d2=datetime.datetime(2015,1,31)
CODAR region¶
In [5]:
jmin = 379
jmax = 461
imin = 236
imax = 321
jss = np.arange(jmin, jmax)
iss = np.arange(imin, imax)
In [6]:
CTs={}
lons_sub = {}
lats_sub = {}
CTs['CODAR'], lons_sub['CODAR'], lats_sub['CODAR'] = conversion_in_region_and_time(jss,iss,d1,d2,grid,mesh_mask)
/data/nsoontie/MEOPAR/tools/SalishSeaNowcast/nowcast/analyze.py:171: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison if kss == 'None':
Boundary Pass¶
In [7]:
jmin = 200
jmax = 380
imin = 250
imax = 330
jss = np.arange(jmin, jmax)
iss = np.arange(imin, imax)
CTs['BP'], lons_sub['BP'], lats_sub['BP'] = conversion_in_region_and_time(jss,iss,d1,d2,grid,mesh_mask)
/data/nsoontie/MEOPAR/tools/SalishSeaNowcast/nowcast/analyze.py:171: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison if kss == 'None':
Victoria¶
In [8]:
jmin = 200
jmax = 380
imin = 171
imax = 251
jss = np.arange(jmin, jmax)
iss = np.arange(imin, imax)
CTs['Victoria'], lons_sub['Victoria'], lats_sub['Victoria'] = conversion_in_region_and_time(jss,iss,d1,d2,grid,mesh_mask)
/data/nsoontie/MEOPAR/tools/SalishSeaNowcast/nowcast/analyze.py:171: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison if kss == 'None':
Juan de Fuca¶
In [9]:
jmin = 220
jmax = 360
imin = 100
imax = 172
jss = np.arange(jmin, jmax)
iss = np.arange(imin, imax)
CTs['JDF'], lons_sub['JDF'], lats_sub['JDF'] = conversion_in_region_and_time(jss,iss,d1,d2,grid,mesh_mask)
/data/nsoontie/MEOPAR/tools/SalishSeaNowcast/nowcast/analyze.py:171: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison if kss == 'None':
North SoG¶
In [10]:
jmin = 462
jmax = 600
imin = 100
imax = 300
jss = np.arange(jmin, jmax)
iss = np.arange(imin, imax)
CTs['NSoG'], lons_sub['NSoG'], lats_sub['NSoG'] = conversion_in_region_and_time(jss,iss,d1,d2,grid,mesh_mask)
/data/nsoontie/MEOPAR/tools/SalishSeaNowcast/nowcast/analyze.py:171: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison if kss == 'None':
Plot
In [11]:
fig,ax = plt.subplots(1,1,figsize=(10,10))
for key in CTs:
#Average over 6 M2 tidal cycles
mean_CT = np.mean(CTs[key][:75], axis=0)
mesh= ax.pcolormesh(lons_sub[key],
lats_sub[key],
mean_CT,
vmin = -2000,
vmax=2000,
cmap = 'viridis')
viz_tools.plot_coastline(ax,grid,coords='map')
plt.colorbar(mesh,ax=ax)
ax.set_xlim([-124.5,-122.8])
ax.set_ylim([47.5, 49.8])
viz_tools.plot_coastline(ax, grid, coords='map', isobath=100,color='lightgray')
viz_tools.plot_coastline(ax, grid, coords='map', isobath=125,color='lightgray')
viz_tools.plot_coastline(ax, grid, coords='map', isobath=200,color='lightgray')
Out[11]:
<matplotlib.contour.QuadContourSet at 0x7f754ffef3c8>
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