def get_gpp_expected_results():
land_weights = SURFACE_FRACS * AREA_WEIGHTS
world_values = np.sum(np.sum(RAW_DATA * land_weights, axis=2),
axis=1) / np.sum(land_weights)
world_land_values = world_values
nh_area_weights = np.copy(AREA_WEIGHTS)
nh_area_weights[2, :] = 0
# we do these by hand: yes they're very slow but that's the point
world_nh_land_values = np.array([
(40 * 30 + 60 * 10) * 1.2 + (110 * 80 + 120 * 100 + 260 * 50) * 2,
(15 * 30 + 90 * 10) * 1.2 + (300 * 80 + 350 * 100 + 270 * 50) * 2,
(120 * 30 + 60 * 10) * 1.2 + (510 * 80 + 432 * 100 + 280 * 50) * 2,
]) / ((30 + 10) * 1.2 + (80 + 100 + 50) * 2)
world_nh_values = world_nh_land_values
sh_area_weights = np.copy(AREA_WEIGHTS)
sh_area_weights[:2, :] = 0
world_sh_land_values = np.array([
(3 * 20 + 60 * 10 + 20 * 51 + 40 * 15) * 1.1,
(10 * 20 + 70 * 10 + 90 * 51 + 130 * 15) * 1.1,
(50 * 20 + 60 * 10 + 55 * 51 + 60 * 15) * 1.1,
]) / ((20 + 10 + 51 + 15) * 1.1)
world_sh_values = world_sh_land_values
data = np.vstack([
world_values,
world_land_values,
world_nh_values,
world_sh_values,
world_nh_land_values,
world_sh_land_values,
]).T
exp = ScmDataFrame(
data=data,
index=SCMDF_TIME,
columns={
"model":
"unspecified",
"scenario":
"experiment",
"region": [
"World",
"World|Land",
"World|Northern Hemisphere",
"World|Southern Hemisphere",
"World|Northern Hemisphere|Land",
"World|Southern Hemisphere|Land",
],
"variable":
"gpp",
"unit":
"kg m^-2 s^-1",
"climate_model":
"model",
"activity_id":
"cmip5",
"member_id":
"realisation",
"variable_standard_name":
"gross_primary_productivity_of_carbon",
"mip_era":
"CMIP5",
},
)
exp.metadata = {
"calendar":
"gregorian",
"modeling_realm":
"land",
"Conventions":
"CF-1.5",
"crunch_source_files":
"Files: ['/cmip5/experiment/Lmon/gpp/model/realisation/gpp_Lmon_model_experiment_realisation_185001-185003.nc']; sftlf: ['/cmip5/experiment/fx/sftlf/model/r0i0p0/sftlf_fx_model_experiment_r0i0p0.nc']; areacella: ['/cmip5/experiment/fx/areacella/model/r0i0p0/areacella_fx_model_experiment_r0i0p0.nc']",
}
exp = _add_land_area_metadata(exp, realm="land")
return exp
def get_hfds_expected_results():
sftof_fracs = 100 - SURFACE_FRACS
ocean_weights = sftof_fracs * AREA_WEIGHTS
world_values = np.sum(np.sum(RAW_DATA * ocean_weights, axis=2),
axis=1) / np.sum(ocean_weights)
world_ocean_values = world_values
nh_area_weights = np.copy(AREA_WEIGHTS)
nh_area_weights[2, :] = 0
# we do these by hand: yes they're very slow but that's the point
world_nh_ocean_values = np.array([
(30 * 100 + 40 * 70 + 50 * 100 + 60 * 90) * 1.2 +
(110 * 20 + 190 * 100 + 260 * 50) * 2,
(0 * 100 + 15 * 70 + 45 * 100 + 90 * 90) * 1.2 +
(300 * 20 + 450 * 100 + 270 * 50) * 2,
(60 * 100 + 120 * 70 + 60 * 100 + 60 * 90) * 1.2 +
(510 * 20 + 220 * 100 + 280 * 50) * 2,
]) / ((100 + 70 + 100 + 90) * 1.2 + (20 + 100 + 50) * 2)
world_nh_values = world_nh_ocean_values
sh_area_weights = np.copy(AREA_WEIGHTS)
sh_area_weights[:2, :] = 0
world_sh_ocean_values = np.array([
(3 * 80 + 60 * 90 + 20 * 49 + 40 * 85) * 1.1,
(10 * 80 + 70 * 90 + 90 * 49 + 130 * 85) * 1.1,
(50 * 80 + 60 * 90 + 55 * 49 + 60 * 85) * 1.1,
]) / ((80 + 90 + 49 + 85) * 1.1)
world_sh_values = world_sh_ocean_values
world_north_atlantic_values = np.array([260, 270, 280])
world_elnino_values = np.array([190, 450, 220])
data = np.vstack([
world_values,
world_ocean_values,
world_nh_values,
world_sh_values,
world_nh_ocean_values,
world_sh_ocean_values,
world_north_atlantic_values,
world_elnino_values,
]).T
exp = ScmDataFrame(
data=data,
index=SCMDF_TIME,
columns={
"model":
"unspecified",
"scenario":
"experiment",
"region": [
"World",
"World|Ocean",
"World|Northern Hemisphere",
"World|Southern Hemisphere",
"World|Northern Hemisphere|Ocean",
"World|Southern Hemisphere|Ocean",
"World|North Atlantic Ocean",
"World|El Nino N3.4",
],
"variable":
"hfds",
"unit":
"W m^-2",
"climate_model":
"model",
"activity_id":
"cmip5",
"member_id":
"realisation",
"variable_standard_name":
"surface_downward_heat_flux_in_sea_water",
"mip_era":
"CMIP5",
},
)
exp.metadata = {
"calendar":
"gregorian",
"modeling_realm":
"ocean",
"Conventions":
"CF-1.5",
"crunch_source_files":
"Files: ['/cmip5/experiment/Omon/hfds/model/realisation/hfds_Omon_model_experiment_realisation_185001-185003.nc']; sftof: ['/cmip5/experiment/fx/sftof/model/r0i0p0/sftof_fx_model_experiment_r0i0p0.nc']; areacello: ['/cmip5/experiment/fx/areacello/model/r0i0p0/areacello_fx_model_experiment_r0i0p0.nc']",
}
exp = _add_land_area_metadata(exp, realm="ocean")
return exp
def get_rsdt_expected_results():
world_values = np.sum(np.sum(RAW_DATA * AREA_WEIGHTS, axis=2),
axis=1) / np.sum(AREA_WEIGHTS)
land_weights = SURFACE_FRACS * AREA_WEIGHTS
world_land_values = np.sum(np.sum(RAW_DATA * land_weights, axis=2),
axis=1) / np.sum(land_weights)
ocean_weights = (100 - SURFACE_FRACS) * AREA_WEIGHTS
world_ocean_values = np.sum(np.sum(RAW_DATA * ocean_weights, axis=2),
axis=1) / np.sum(ocean_weights)
nh_area_weights = np.copy(AREA_WEIGHTS)
nh_area_weights[2, :] = 0
world_nh_values = np.sum(np.sum(RAW_DATA * nh_area_weights, axis=2),
axis=1) / np.sum(nh_area_weights)
sh_area_weights = np.copy(AREA_WEIGHTS)
sh_area_weights[:2, :] = 0
world_sh_values = np.sum(np.sum(RAW_DATA * sh_area_weights, axis=2),
axis=1) / np.sum(sh_area_weights)
# we do these by hand: yes they're very slow but that's the point
world_nh_land_values = np.array([
(40 * 30 + 60 * 10) * 1.2 + (110 * 80 + 120 * 100 + 260 * 50) * 2,
(15 * 30 + 90 * 10) * 1.2 + (300 * 80 + 350 * 100 + 270 * 50) * 2,
(120 * 30 + 60 * 10) * 1.2 + (510 * 80 + 432 * 100 + 280 * 50) * 2,
]) / ((30 + 10) * 1.2 + (80 + 100 + 50) * 2)
world_sh_land_values = np.array([
(3 * 20 + 60 * 10 + 20 * 51 + 40 * 15) * 1.1,
(10 * 20 + 70 * 10 + 90 * 51 + 130 * 15) * 1.1,
(50 * 20 + 60 * 10 + 55 * 51 + 60 * 15) * 1.1,
]) / ((20 + 10 + 51 + 15) * 1.1)
world_nh_ocean_values = np.array([
(30 * 100 + 40 * 70 + 50 * 100 + 60 * 90) * 1.2 +
(110 * 20 + 190 * 100 + 260 * 50) * 2,
(0 * 100 + 15 * 70 + 45 * 100 + 90 * 90) * 1.2 +
(300 * 20 + 450 * 100 + 270 * 50) * 2,
(60 * 100 + 120 * 70 + 60 * 100 + 60 * 90) * 1.2 +
(510 * 20 + 220 * 100 + 280 * 50) * 2,
]) / ((100 + 70 + 100 + 90) * 1.2 + (20 + 100 + 50) * 2)
world_sh_ocean_values = np.array([
(3 * 80 + 60 * 90 + 20 * 49 + 40 * 85) * 1.1,
(10 * 80 + 70 * 90 + 90 * 49 + 130 * 85) * 1.1,
(50 * 80 + 60 * 90 + 55 * 49 + 60 * 85) * 1.1,
]) / ((80 + 90 + 49 + 85) * 1.1)
world_north_atlantic_values = np.array([260, 270, 280])
world_elnino_values = np.array([190, 450, 220])
data = np.vstack([
world_values,
world_land_values,
world_ocean_values,
world_nh_values,
world_sh_values,
world_nh_land_values,
world_sh_land_values,
world_nh_ocean_values,
world_sh_ocean_values,
world_north_atlantic_values,
world_elnino_values,
]).T
exp = ScmDataFrame(
data=data,
index=SCMDF_TIME,
columns={
"model":
"unspecified",
"scenario":
"experiment",
"region": [
"World",
"World|Land",
"World|Ocean",
"World|Northern Hemisphere",
"World|Southern Hemisphere",
"World|Northern Hemisphere|Land",
"World|Southern Hemisphere|Land",
"World|Northern Hemisphere|Ocean",
"World|Southern Hemisphere|Ocean",
"World|North Atlantic Ocean",
"World|El Nino N3.4",
],
"variable":
"rsdt",
"unit":
"W m^-2",
"climate_model":
"model",
"activity_id":
"cmip5",
"member_id":
"realisation",
"variable_standard_name":
"toa_incoming_shortwave_flux",
"mip_era":
"CMIP5",
},
)
exp.metadata = {
"calendar":
"gregorian",
"land_fraction":
np.sum(AREA_WEIGHTS * SURFACE_FRACS) / (100 * np.sum(AREA_WEIGHTS)),
"land_fraction_northern_hemisphere":
np.sum(nh_area_weights * SURFACE_FRACS) /
(100 * np.sum(nh_area_weights)),
"land_fraction_southern_hemisphere":
np.sum(sh_area_weights * SURFACE_FRACS) /
(100 * np.sum(sh_area_weights)),
"modeling_realm":
"atmos",
"Conventions":
"CF-1.5",
"crunch_source_files":
"Files: ['/cmip5/experiment/Amon/rsdt/model/realisation/rsdt_Amon_model_experiment_realisation_185001-185003.nc']; areacella: ['/cmip5/experiment/fx/areacella/model/r0i0p0/areacella_fx_model_experiment_r0i0p0.nc']; sftlf: ['/cmip5/experiment/fx/sftlf/model/r0i0p0/sftlf_fx_model_experiment_r0i0p0.nc']",
}
exp = _add_land_area_metadata(exp, realm="atmos")
return exp