Section transports#

%load_ext autoreload
%autoreload 2
%%capture 
# comment above line to see details about the run(s) displayed
from misc import *
import nc_time_axis
%matplotlib inline
transports = []
for path, case in zip(ocn_path, casename):
  ds = xr.open_dataset(path+case+'_section_transports.nc').sel(time=slice('0001-01-01',end_date))
  transports.append(ds)

Agulhas#

section_name = 'Agulhas_Section'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/3e18bc238d81b26a6e2d2b5c39aea816b866dca11f85ae932361fd4026b5bc3a.png

Barents Opening#

section_name = 'Barents_Opening'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/dcb62fc04e9a7f011a1a39dd4b9bd4799d017f8e78e66c9d47ade89b5fb7d3d1.png

Bering Strait#

section_name = 'Bering_Strait'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/6b149b5ae4857cd2e5bb2be35cf4b60d24eb652684f413e2e80abbfefadf541b.png

Davis Strait#

section_name = 'Davis_Strait'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/e4a1462bae2b2135a1622cb80fac42bbba60d1a0ecb7d01b7516e72a91d19cf6.png

Denmark Strait#

section_name = 'Denmark_Strait'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/e9be5127d91f6bba825734d4410580298879b0e4e3600069c04ea5daf3ef6435.png

Drake_Passage#

section_name = 'Drake_Passage'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/962fe281f96f94cf4b8fbf6e48772d31436ba5679f347812daec5990141cdea3.png

English Channel#

section_name = 'English_Channel'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/2fefa362f3955eb5322fe76690a794787777562f4c85cc6b19b4aa915a80e243.png

Fram Strait#

section_name = 'Fram_Strait'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/c3bd666a8ef5530542c74d3e7def4ccdc7268087011463533fabf11960c12603.png

Florida Bahamas#

section_name = 'Florida_Bahamas'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/9b248f2236234f018107b8d17ad1980f4aa616775ae4c82a84871a3eedc90986.png

Florida Bahamas extended#

section_name = 'Florida_Bahamas_extended'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/5e0fe6daa180f073639665abcfbc3536732e4e749a57a100e05f3a9ca90d4300.png

Florida Cuba#

section_name = 'Florida_Cuba'
vals = None#get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/9e61cb0b9ae7695548398df741443cf6bee5d516738ea40543308705305f6404.png

Gibraltar Strait#

section_name = 'Gibraltar_Strait'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/584abc426f9f4862f8de934c91c5a7afce8ea262b8a6b814b4b47641ca9f2ff6.png

Iceland Norway#

section_name = 'Iceland_Norway'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
Section 'Iceland_Norway' not found in the '070' dataset. Skipping plot.
<Figure size 1000x600 with 0 Axes>

Indonesian Throughflow#

section_name = 'Indonesian_Throughflow'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/663d8d1d9ac206df2f5100634f7186b968abe03bcb677f913b8740334fa5ac20.png

Mozambique Channel#

section_name = 'Mozambique_Channel'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/0f0be141bef1bc49c0d295fee56c515fb312ebf518974445a9fbb117730d3d07.png

Pacific undercurrent#

section_name = 'Pacific_undercurrent'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/ccc311f12e6acd4f159760726d3ae550287359309c40bdb8db729525c85df744.png

Taiwan Luzon#

section_name = 'Taiwan_Luzon'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/6f0ae1ebb44457d68422022475f4c2e9507e312a58cbc4f8a3abb6201984dcc5.png

Windward Passage#

section_name = 'Windward_Passage'
vals = get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/d7e962b7df8305fbdf26e9912a286c3e85a4926f553bf1a4b154614f58a7e6a3.png

Robeson Channel#

section_name = 'Robeson_Channel'
vals = None #get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/191bf6eef7cc959a846c9826cf5b1b64262ea12a29f634999421c676649da05d.png

Yucatan Channel#

section_name = 'Yucatan_Channel'
vals = None #get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
_images/059ee90879cfe083e7a5df7dc8eca162493fecbcd0161c1dc087de5ebf0efa6d.png

Bosporus Strait#

section_name = 'Bosporus_Strait'
vals = None #get_transport_range_or_mean(diag_config_yml['Transports']['sections']['h.'+section_name])
plot_transport_time_series(transports, section_name, label, to_yearly=True, observed_values=vals)
Section 'Bosporus_Strait' not found in the '070' dataset. Skipping plot.
<Figure size 1000x600 with 0 Axes>

All sections#

def plotPanel(section,n,label):
    ax = plt.subplot(7,3,n+1)
    plt.plot(section.time,section.values, lw=2, label=label)
    plt.title(section.sections.values,fontsize=12)
    plt.grid()
    if n in [0,3,6,9,12,15,18]: plt.ylabel('Transport (Sv)')
    
    return
fig = plt.figure(figsize=(18,18))
for n in range(0,len(ds.sections)): 
  for i in range(0,len(casename)):
    plotPanel(transports[i].transport[n,:],n,label[i])
    
fig.text(0.5,0.9,'Case = '+str(casename[0]),horizontalalignment='center',fontsize=14)
plt.subplots_adjust(hspace=0.3)
plt.legend(fontsize=12);
_images/b84785d57d5e9c39f5bb412daa08ec3069538ce8adeb957abea72c1aaeeb2a7e.png