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/40c5b9daa99ecb37852261bcb3077e125571cd6839ef8a8a60ad5710f6def13c.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/4a64e72bd5cef86320640562e72fd1985a5df39902679d34c96e5ac1b6b223e3.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/4ae0a015e1bb7685ea09564be53e61993f8b5768542c77124dbf5942690043a3.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/1ee3f72e43cf33159916ac1ce1e27893d0f5c8377fd5c1ac3e19aa4fc378500f.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/b64039dafe80e102399928303e07337fad28c7b0bbde9e510af66e962c5a48be.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/a45a8af5877497dd261b5f3347879538a6f31d6f161434a12029ef602eaa3041.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/cb0eab8aeb63462e2d51c65f8e10054485ea0588bef51bde48c7be56e3d410be.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/e2408684bae58068d6afd1ea9d0ac688e30735ed28213fe39c84e95cef90a9c4.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/e4f8b93e4cac78e927d4c3ae95776421757c3a306c98693804d934d65a6f15ce.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/81060cea90273c3380db3e2d6dab4bfb98212fb3a3b615b2397f4e78482bb61b.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/8bfb967c78000cea352e960208e44fbe327d556cc1b8a7cf54473ff16d631a41.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/fe765708a6b1d4f403dd9c4346c12051a42063a96ea772644cef4bd4175d60af.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 '063' 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/8356c46470e4f5386322e65f624349c8f3c5c3c8343ee964461f669cab7aa9f0.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/c7e929b0452fc813511e59d83690a0c2790639c81cf063a9c2049c2f69f967e6.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/d510ff5c9bfde6c97bd773fe42e9a800d5a6ee9433fbac21aac0bbf35bbaf07e.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/dd92a381a7a7d20d3237e31e53b148e855ee9766f9e68be1a9cfc65708481bc3.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/312f242d16b907c9c86111d1a23abe67c1dd53eb8544793fde9dfbfa21f72423.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/f744491691b4a7d5e4bd2b0dd7f8877e49732bb21558cdfef556575ee7306945.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/a359fbe3e637859fa0f7f08c1b6c14398e5fcba8fe2e77a93d6de3066d2811e5.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 '063' 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/b2041c24f088c1e7e531306ad00787793a890bda3321ca3941718a80b2f4d923.png