Adding code to run the shallow-water and barotropic vorticity equation sets

.gitignore

@@ -79,6 +79,8 @@ coverage.xml
 .pytest_cache/
 test/.cache
 test/results.xml
+*.sh.e*
+*.sh.o*
 
 # Translations
 *.mo

exp/test_cases/barotropic_vorticity_equation/barotropic_vor_eq_stirring_test.py

@@ -0,0 +1,116 @@
+import os
+
+import numpy as np
+
+from isca import BarotropicCodeBase, DiagTable, Experiment, Namelist, GFDL_BASE
+
+NCORES = 8
+base_dir = os.path.dirname(os.path.realpath(__file__))
+# a CodeBase can be a directory on the computer,
+# useful for iterative development
+cb = BarotropicCodeBase.from_directory(GFDL_BASE)
+
+# or it can point to a specific git repo and commit id.
+# This method should ensure future, independent, reproducibility of results.
+# cb = DryCodeBase.from_repo(repo='https://github.com/isca/isca', commit='isca1.1')
+
+# compilation depends on computer specific settings.  The $GFDL_ENV
+# environment variable is used to determine which `$GFDL_BASE/src/extra/env` file
+# is used to load the correct compilers.  The env file is always loaded from
+# $GFDL_BASE and not the checked out git repo.
+
+cb.compile()  # compile the source code to working directory $GFDL_WORK/codebase
+
+# create an Experiment object to handle the configuration of model parameters
+# and output diagnostics
+exp = Experiment('barotropic_stirring_test_experiment', codebase=cb)
+
+#Tell model how to write diagnostics
+diag = DiagTable()
+diag.add_file('atmos_monthly', 30, 'days', time_units='days')
+
+#Tell model which diagnostics to write
+diag.add_field('barotropic_diagnostics', 'ucomp', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'vcomp', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'vor', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'pv', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'stream', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'trs', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'tr', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'eddy_vor', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'delta_u', time_avg=True)
+diag.add_field('stirring_mod', 'stirring', time_avg=True)
+diag.add_field('stirring_mod', 'stirring_amp', time_avg=True)
+diag.add_field('stirring_mod', 'stirring_sqr', time_avg=True)
+
+exp.diag_table = diag
+
+#Empty the run directory ready to run
+exp.clear_rundir()
+
+#Define values for the 'core' namelist
+exp.namelist = namelist = Namelist({
+    'main_nml':{
+     'days'   : 30,
+     'hours'  : 0,
+     'minutes': 0,
+     'seconds': 0,
+     'dt_atmos': 1200,
+     'calendar': 'no_calendar',
+    },
+
+ 'atmosphere_nml':{
+   'print_interval': 86400,
+    },
+
+'fms_io_nml':{
+   'threading_write' :'single',
+   'fileset_write': 'single'
+    },
+
+ 'fms_nml':{
+   'print_memory_usage':True,
+   'domains_stack_size': 200000,
+    },
+
+ 'barotropic_dynamics_nml':{
+   'triang_trunc'   : True,
+   'num_lat'        : 128,
+   'num_lon'        : 256,
+   'num_fourier'    : 85,
+   'num_spherical'  : 86,
+   'fourier_inc'    : 1,
+   'damping_option' : 'resolution_dependent',
+   'damping_order'  : 2,
+   'damping_coeff'  : 1.157E-4,
+   'damping_coeff_r': 1.929E-6,
+   'grid_tracer'    : True,
+   'spec_tracer'    : True,
+   'm_0'            : 6,
+   'zeta_0'         : 0.0,
+   'eddy_lat'       : 45.0,
+   'eddy_width'     : 10.0,
+   'robert_coeff'   : 0.04,
+   'initial_zonal_wind' : 'zero',
+    },
+
+ 'barotropic_physics_nml':{
+   },
+
+ 'stirring_nml': {
+   'decay_time':172800,
+   'amplitude':3.e-11,
+   'lat0':45.,
+   'lon0':180.,
+   'widthy':12.,
+   'widthx':45.,
+   'B':1.0,
+   },
+
+})
+
+#Lets do a run!
+if __name__=="__main__":
+    exp.run(1, use_restart=False, num_cores=NCORES)
+    for i in range(2,121):
+        exp.run(i, num_cores=NCORES)

exp/test_cases/barotropic_vorticity_equation/barotropic_vor_eq_test.py

@@ -0,0 +1,100 @@
+import os
+
+import numpy as np
+
+from isca import BarotropicCodeBase, DiagTable, Experiment, Namelist, GFDL_BASE
+
+NCORES = 8
+base_dir = os.path.dirname(os.path.realpath(__file__))
+# a CodeBase can be a directory on the computer,
+# useful for iterative development
+cb = BarotropicCodeBase.from_directory(GFDL_BASE)
+
+# or it can point to a specific git repo and commit id.
+# This method should ensure future, independent, reproducibility of results.
+# cb = DryCodeBase.from_repo(repo='https://github.com/isca/isca', commit='isca1.1')
+
+# compilation depends on computer specific settings.  The $GFDL_ENV
+# environment variable is used to determine which `$GFDL_BASE/src/extra/env` file
+# is used to load the correct compilers.  The env file is always loaded from
+# $GFDL_BASE and not the checked out git repo.
+
+cb.compile()  # compile the source code to working directory $GFDL_WORK/codebase
+
+# create an Experiment object to handle the configuration of model parameters
+# and output diagnostics
+exp = Experiment('barotropic_test_experiment', codebase=cb)
+
+#Tell model how to write diagnostics
+diag = DiagTable()
+diag.add_file('atmos_monthly', 30, 'days', time_units='days')
+
+#Tell model which diagnostics to write
+diag.add_field('barotropic_diagnostics', 'ucomp', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'vcomp', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'vor', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'pv', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'stream', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'trs', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'tr', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'eddy_vor', time_avg=True)
+diag.add_field('barotropic_diagnostics', 'delta_u', time_avg=True)
+
+exp.diag_table = diag
+
+#Empty the run directory ready to run
+exp.clear_rundir()
+
+#Define values for the 'core' namelist
+exp.namelist = namelist = Namelist({
+    'main_nml':{
+     'days'   : 30,
+     'hours'  : 0,
+     'minutes': 0,
+     'seconds': 0,
+     'dt_atmos': 1200,
+     'calendar': 'no_calendar',
+    },
+
+ 'atmosphere_nml':{
+   'print_interval': 86400,
+    },
+
+'fms_io_nml':{
+   'threading_write' :'single',
+   'fileset_write': 'single'
+    },
+
+ 'fms_nml':{
+   'print_memory_usage':True,
+   'domains_stack_size': 200000,
+    },
+
+ 'barotropic_dynamics_nml':{
+   'triang_trunc'   : True,
+   'num_lat'        : 128,
+   'num_lon'        : 256,
+   'num_fourier'    : 85,
+   'num_spherical'  : 86,
+   'fourier_inc'    : 1,
+   'damping_option' : 'resolution_dependent',
+   'damping_order'  : 4,
+   'damping_coeff'  : 1.e-04,
+   'grid_tracer'    : True,
+   'spec_tracer'    : True,
+   'm_0'            : 4,
+   'zeta_0'         : 8.e-05,
+   'eddy_lat'       : 45.0,
+   'eddy_width'     : 15.0,
+   'robert_coeff'   : 0.04,
+    },
+
+ 'barotropic_physics_nml':{
+   },
+})
+
+#Lets do a run!
+if __name__=="__main__":
+    exp.run(1, use_restart=False, num_cores=NCORES)
+    for i in range(2,121):
+        exp.run(i, num_cores=NCORES)

exp/test_cases/shallow_water/shallow_water_stirring_test.py

@@ -0,0 +1,126 @@
+import os
+
+import numpy as np
+
+from isca import ShallowCodeBase, DiagTable, Experiment, Namelist, GFDL_BASE
+
+NCORES = 8
+base_dir = os.path.dirname(os.path.realpath(__file__))
+# a CodeBase can be a directory on the computer,
+# useful for iterative development
+cb = ShallowCodeBase.from_directory(GFDL_BASE)
+
+# or it can point to a specific git repo and commit id.
+# This method should ensure future, independent, reproducibility of results.
+# cb = DryCodeBase.from_repo(repo='https://github.com/isca/isca', commit='isca1.1')
+
+# compilation depends on computer specific settings.  The $GFDL_ENV
+# environment variable is used to determine which `$GFDL_BASE/src/extra/env` file
+# is used to load the correct compilers.  The env file is always loaded from
+# $GFDL_BASE and not the checked out git repo.
+
+cb.compile()  # compile the source code to working directory $GFDL_WORK/codebase
+
+# create an Experiment object to handle the configuration of model parameters
+# and output diagnostics
+exp = Experiment('shallow_stirring_test_experiment', codebase=cb)
+
+#Tell model how to write diagnostics
+diag = DiagTable()
+diag.add_file('atmos_monthly', 30, 'days', time_units='days')
+
+#Tell model which diagnostics to write
+diag.add_field('shallow_diagnostics', 'ucomp', time_avg=True)
+diag.add_field('shallow_diagnostics', 'vcomp', time_avg=True)
+diag.add_field('shallow_diagnostics', 'vor', time_avg=True)
+diag.add_field('shallow_diagnostics', 'div', time_avg=True)
+diag.add_field('shallow_diagnostics', 'h', time_avg=True)
+diag.add_field('shallow_diagnostics', 'pv', time_avg=True)
+diag.add_field('shallow_diagnostics', 'stream', time_avg=True)
+diag.add_field('shallow_diagnostics', 'trs', time_avg=True)
+diag.add_field('shallow_diagnostics', 'tr', time_avg=True)
+diag.add_field('stirring_mod', 'stirring', time_avg=True)
+diag.add_field('stirring_mod', 'stirring_amp', time_avg=True)
+diag.add_field('stirring_mod', 'stirring_sqr', time_avg=True)
+
+exp.diag_table = diag
+
+#Empty the run directory ready to run
+exp.clear_rundir()
+
+#Define values for the 'core' namelist
+exp.namelist = namelist = Namelist({
+    'main_nml':{
+     'days'   : 30,
+     'hours'  : 0,
+     'minutes': 0,
+     'seconds': 0,
+     'dt_atmos': 1200,
+     'calendar': 'no_calendar',
+    },
+
+ 'atmosphere_nml':{
+   'print_interval': 86400,
+    },
+
+'fms_io_nml':{
+   'threading_write' :'single',
+   'fileset_write': 'single'
+    },
+
+ 'fms_nml':{
+   'print_memory_usage':True,
+   'domains_stack_size': 200000,
+    },
+
+ 'shallow_dynamics_nml':{
+   'num_lon'             : 256,
+   'num_lat'             : 128,
+   'num_fourier'         : 85,
+   'num_spherical'       : 86,
+   'fourier_inc'         : 1,
+   'damping_option'      : 'resolution_dependent',
+   'damping_order'       : 4,
+   'damping_coeff'       : 1.e-04,
+   'h_0'                 : 3.e04,
+   'grid_tracer'         : True,
+   'spec_tracer'         : True,
+   'robert_coeff'        : 0.04,
+   'robert_coeff_tracer' : 0.04,
+    },
+
+ 'shallow_physics_nml':{
+   'fric_damp_time'  : -50.0,
+   'therm_damp_time' : -10.0,
+   'del_h'           :  2.e04,
+   'h_0'             :  3.e04,
+   'h_amp'           :  1.e05,
+   'h_lon'           :  90.0,
+   'h_lat'           :  25.0,
+   'h_width'         :  15.0,
+   'itcz_width'      :  4.0,
+   'h_itcz'          :  4.e04,
+   },
+
+#The below stirring parameters are those of Vallis et al 2004 DOI: 10.1175/1520-0469(2004)061<0264:AMASDM>2.0.CO;2
+#They have a decorrelation time set by 'decay_time', chosen to be 2 days by default. The forcing is also localised in
+#latitude and longitude, with the centre of the forcing set by lat0 and lon0, and the width of the gaussians set by 
+#'widthy and widthx'. B sets the variation in longitude, with ampx = 1 + B*exp(-xx/widthx**2)
+
+ 'stirring_nml': {
+   'decay_time':172800,
+   'amplitude':3.e-13,
+   'lat0':45.,
+   'lon0':180.,
+   'widthy':12.,
+   'widthx':45.,
+   'B':1.0,
+   },
+
+})
+
+#Lets do a run!
+if __name__=="__main__":
+    exp.run(1, use_restart=False, num_cores=NCORES)
+    for i in range(2,122):
+        exp.run(i, num_cores=NCORES)