In [1]:

    

import matplotlib.pyplot as plt
import iris
import iris.plot as iplt
import numpy
import iris.coord_categorisation


    

In [2]:

    

%matplotlib inline


    

In [3]:

    

infile = '/g/data/ua6/DRSv2/CMIP5/CSIRO-Mk3-6-0/historical/mon/ocean/r1i1p1/msftmyz/latest/msftmyz_Omon_CSIRO-Mk3-6-0_historical_r1i1p1_185001-200512.nc'


    

In [4]:

    

cube = iris.load_cube(infile, 'ocean_meridional_overturning_mass_streamfunction')


    

    




/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/iris/fileformats/cf.py:1143: IrisDeprecation: NetCDF default loading behaviour currently does not expose variables which define reference surfaces for dimensionless vertical coordinates as independent Cubes. This behaviour is deprecated in favour of automatic promotion to Cubes. To switch to the new behaviour, set iris.FUTURE.netcdf_promote to True.
  warn_deprecated(msg)

In [5]:

    

print(cube)


    

    




ocean_meridional_overturning_mass_streamfunction / (kg s-1) (time: 1872; -- : 3; depth: 31; latitude: 189)
     Dimension coordinates:
          time                                                   x          -         -             -
          depth                                                  -          -         x             -
          latitude                                               -          -         -             x
     Attributes:
          Conventions: CF-1.4
          branch_time: 29200.0
          cmor_version: 2.6.0
          comment: Generated by script CMIP5_Mk36_msftmyz.ncl using CMIP5 parameters as i...
          contact: Project leaders: Stephen Jeffrey (Stephen.Jeffrey@qld.gov.au) & Leon Rotstayn...
          creation_date: 2011-07-27T03:00:00Z
          experiment: historical
          experiment_id: historical
          forcing: Ant,Nat (all forcings)
          frequency: mon
          history: Derived (not model generated) quantity.
          initialization_method: 1
          institute_id: CSIRO-QCCCE
          institution: Australian Commonwealth Scientific and Industrial Research Organization...
          model_id: CSIRO-Mk3-6-0
          modeling_realm: ocean
          original_name: None
          parent_experiment: piControl
          parent_experiment_id: piControl
          parent_experiment_rip: r1i1p1
          physics_version: 1
          product: output
          project_id: CMIP5
          realization: 1
          references: a) Rotstayn, L., Collier, M., Dix, M., Feng, Y., Gordon, H., O\'Farrell,...
          source: CSIRO-Mk3-6-0 2010 atmosphere: AGCM v7.3.8 (T63 spectral, 1.875 degrees...
          table_id: Table Omon (27 April 2011) 9e1a53e4873bf6f26879903e165fe4a0
          title: CSIRO-Mk3-6-0 model output prepared for CMIP5 historical
          tracking_id: ea6fa17f-c03d-4edf-bbe9-1e6e76984153
          version_number: v20110518
     Cell methods:
          mean: time
          mean: longitude

In [6]:

    

dim_coord_names = [coord.name() for coord in cube.dim_coords]
print(dim_coord_names)


    

    




['time', 'depth', 'latitude']

In [7]:

    

aux_coord_names = [coord.name() for coord in cube.aux_coords]
print(aux_coord_names)


    

    




[]

In [8]:

    

mf_cube = cube[:, 0, : ,:]


    

In [9]:

    

mf_cube


    

    
Out[9]:





<iris 'Cube' of ocean_meridional_overturning_mass_streamfunction / (kg s-1) (time: 1872; depth: 31; latitude: 189)>

In [10]:

    

mf_clim_cube = mf_cube.collapsed('time', iris.analysis.MEAN)


    

In [11]:

    

mf_clim_cube


    

    
Out[11]:





<iris 'Cube' of ocean_meridional_overturning_mass_streamfunction / (kg s-1) (depth: 31; latitude: 189)>

In [12]:

    

iplt.contour(mf_clim_cube, colors='k')
# plt.clabel(contour_plot) fmt='%.1f')
plt.show()


    

    




/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.minimum.reduce will be axis=0, not the current None, to match np.minimum.reduce. Explicitly pass 0 or None to silence this warning.
  return self.reduce(a)
/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.maximum.reduce will be axis=0, not the current None, to match np.maximum.reduce. Explicitly pass 0 or None to silence this warning.
  return self.reduce(a)






    

In [13]:

    

depth_constraint = iris.Constraint(depth= lambda cell: cell <= 250)
lat_constraint = iris.Constraint(latitude=lambda cell: -30.0 <= cell < 30.0)


    

In [14]:

    

tropics_cube = mf_clim_cube.extract(depth_constraint & lat_constraint)


    

In [18]:

    

iplt.contourf(tropics_cube, cmap='RdBu_r',
              levels=[-1.25e+10, -1.0e+10, -7.5e+9, -5.0e+9, -2.5e+9, 0, 2.5e+9, 5.0e+9, 7.5e+9, 1.0e+10, 1.25e+10],
              extend='both')
plt.colorbar()
plt.show()


    

    




/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.minimum.reduce will be axis=0, not the current None, to match np.minimum.reduce. Explicitly pass 0 or None to silence this warning.
  return self.reduce(a)
/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/numpy/ma/core.py:6385: MaskedArrayFutureWarning: In the future the default for ma.maximum.reduce will be axis=0, not the current None, to match np.maximum.reduce. Explicitly pass 0 or None to silence this warning.
  return self.reduce(a)






    

In [27]:

    

tropics_cube.data.max()


    

    
Out[27]:





5.9115131e+10

In [16]:

    

sh_lat_constraint = iris.Constraint(latitude=lambda cell: -30.0 <= cell < 0.0)
nh_lat_constraint = iris.Constraint(latitude=lambda cell: 0.0 < cell <= 30.0)


    

In [19]:

    

sh_cube = mf_cube.extract(depth_constraint & sh_lat_constraint)
nh_cube = mf_cube.extract(depth_constraint & nh_lat_constraint)


    

In [18]:

    

sh_cube


    

    
Out[18]:





<iris 'Cube' of ocean_meridional_overturning_mass_streamfunction / (kg s-1) (time: 1872; depth: 11; latitude: 32)>

In [21]:

    

def convert_to_annual(cube, full_months=False, aggregation='mean'):
    """Convert data to annual timescale.
    Args:
      cube (iris.cube.Cube)
      full_months(bool): only include years with data for all 12 months
    """

    iris.coord_categorisation.add_year(cube, 'time')
    iris.coord_categorisation.add_month(cube, 'time')

    if aggregation == 'mean':
        aggregator = iris.analysis.MEAN
    elif aggregation == 'sum':
        aggregator = iris.analysis.SUM

    cube = cube.aggregated_by(['year'], aggregator)

    if full_months:
        cube = cube.extract(iris.Constraint(month='Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec'))
  
    cube.remove_coord('year')
    cube.remove_coord('month')

    return cube


    

In [22]:

    

sh_cube = convert_to_annual(sh_cube)
nh_cube = convert_to_annual(nh_cube)


    

In [25]:

    

sh_metric = sh_cube.collapsed(['depth', 'latitude'], iris.analysis.MEAN) # weights=grid_areas)
nh_metric = nh_cube.collapsed(['depth', 'latitude'], iris.analysis.MEAN) # weights=grid_areas)


    

    




/g/data/r87/dbi599/miniconda3/envs/ocean/lib/python3.6/site-packages/iris/cube.py:3281: UserWarning: Collapsing spatial coordinate 'latitude' without weighting
  warnings.warn(msg.format(coord.name()))

In [27]:

    

iplt.plot(sh_metric)
iplt.plot(nh_metric)
plt.show()


    

In [28]:

    

iplt.plot(nh_metric - sh_metric)
plt.show()


    

In [ ]: