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/8b8fa1d7403cddff3cf9b992e94cfed56dad8da1f6cd1f29a91fa08777c28bfc.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/cafc351d44e7d236e2ad49d9e37fd6cfaba8309348b4a4537523cacc255c1b6c.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/cf20a0505591360017f80ecfa5d4754e2d74a0dd1a7131d08882976599676657.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/64d030de2ee19ec64fd6793f1b5d90bc1efece595b23521db99c189ec24bf579.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/949c8f39fbe9346f2132e255bec6f326dcf82931127d816d6711b76efda97d84.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/f043d08157829da9936c592b561e26b62bc725318edd473c9a42e216934e69f0.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/83b6918af8fbe993e1672e81c01ec65b64cd725dc8e9d41d773086b759a562d5.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/4bb405bb4dcb02c6db3c0270227746a8d74543135feeb63c4a1b8825fe44203f.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/857325d96fa58d206a4f9731c8069d3482cd50fd838b755b58917bc6692717aa.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/933a6536390ab8c35ffe0a1898897e4ce80767d2c28ec0ff01de01082d9cff55.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/a4177069683dfa66983e96b14b25e38b5924a6c380bbb6b9517a97375d792194.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/aab4bf131aafeb681c82ee6db3621a0b92cca7eae14f1debc38e0f1574f7557a.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 '127' 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/4436c50fb753950ec3c28717c326cbe0829b05a96fa6ec8896a73208b085a4a2.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/9afdc392635e900009e3e30bb024b81f789f04588a1e1a80fd24f1855695cff9.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/1761dc3996ce1ce47119641e4451df5ff64408afbeb107605012c22251c98f34.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/8bc381c232feecb8fd0a1aae4ec8456d5b3dee7bd10ebe6872c974e0bdf01574.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/3c23202ea6c3ca2bdad5deef6e0063b6b6c050b555971ecbd4298afe66c69255.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/3894630d1e8ad1e844f4bcdd1622cf07b4890915389411a07e3e9ba988adb5fc.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/cc7f38059d92c9b12efbf7f12d5e0c7b6ce58033c57606f43be89a35e8d7e450.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 '127' 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/6ff69a0f5130d04276e3250133ab639a090974d5a4659898997f5e7a68b1de6d.png