def run_simmod(run_start_year,
run_end_year,
dt,
rcp,
c_sens=c_sens,
add_start=0,
add_end=0,
c_add=0,
ch4_add=0,
n2o_add=0):
warnings.simplefilter(action='ignore', category=FutureWarning)
pd.set_option('mode.chained_assignment', None)
"""
Run the various parts of SimMod and export images and CSV files.
"""
run_years = (run_end_year - run_start_year + 1)
emission_vals = emissions(run_start_year, run_end_year, dt, rcp, add_start,
add_end, c_add, ch4_add, n2o_add)
conc = pulse_decay_runner(run_years, dt, emission_vals)
# if carbon_model == 'BEAM':
# beam._initial_carbon = np.array([596., 713., 35625.])
# beam.intervals = SUBSTEPS
# beam.time_step = dt
# beam.emissions = emission_vals['co2_pg'] / C_TO_CO2
# beam_results = pd.melt(beam.run()[0:1])
# conc['co2_ppm'] = beam_results['value'] * PGC_TO_MOL * 1e6 / MOLES_IN_ATMOSPHERE
# if carbon_model == 'box diffusion':
# box_diffusion_results = box_diffusion_model(
# emission_vals,
# dt,
# DZ,
# MIXING
# )
# conc['co2_ppm'] = box_diffusion_results['co2ppm']
if normalize_2000_conc == True:
conc['co2_ppm'] = (conc['co2_ppm'] -
conc.loc[conc['year'] == 2000, 'co2_ppm'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_co2_ppm'].min())
conc['ch4_ppb'] = (conc['ch4_ppb'] -
conc.loc[conc['year'] == 2000, 'ch4_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_ch4_ppb'].min())
conc['n2o_ppb'] = (conc['n2o_ppb'] -
conc.loc[conc['year'] == 2000, 'n2o_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_n2o_ppb'].min())
forcing = calc_radiative_forcing(conc)
warming = continuous_diffusion_model(forcing, run_years, dt, c_sens)
return warming
#results = run_simmod(run_start_year, run_end_year, dt, rcp, c_sens)
#results.to_csv('results/simmod_run_'+rcp+' '+carbon_model+'.csv')
def run_simmod(run_start_year,
run_end_year,
dt,
rcp,
c_sens=c_sens,
add_start=0,
add_end=0,
c_add=0,
ch4_add=0,
n2o_add=0):
"""
Run the various parts of SimMod and export images and CSV files.
"""
run_years = (run_end_year - run_start_year + 1)
emission_vals = emissions(run_start_year, run_end_year, dt, rcp, add_start,
add_end, c_add, ch4_add, n2o_add)
conc = pulse_decay_runner(run_years, dt, emission_vals)
if carbon_model == 'BEAM':
beam._initial_carbon = np.array([596., 713., 35625.])
beam.intervals = SUBSTEPS
beam.time_step = dt
beam.emissions = emission_vals['co2_pg'] / C_TO_CO2
beam_results = pd.melt(beam.run()[0:1])
conc['co2_ppm'] = beam_results[
'value'] * PGC_TO_MOL * 1e6 / MOLES_IN_ATMOSPHERE
if carbon_model == 'box diffusion':
box_diffusion_results = box_diffusion_model(emission_vals, dt, DZ,
MIXING)
conc['co2_ppm'] = box_diffusion_results['co2ppm']
if normalize_2000_conc == True:
conc['co2_ppm'] = (conc['co2_ppm'] -
conc.loc[conc['year'] == 2000, 'co2_ppm'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_co2_ppm'].min())
conc['ch4_ppb'] = (conc['ch4_ppb'] -
conc.loc[conc['year'] == 2000, 'ch4_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_ch4_ppb'].min())
conc['n2o_ppb'] = (conc['n2o_ppb'] -
conc.loc[conc['year'] == 2000, 'n2o_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_n2o_ppb'].min())
forcing = calc_radiative_forcing(conc)
warming = continuous_diffusion_model(forcing, run_years, dt, c_sens)
return warming
def run_simmod(*, run_start_year, run_end_year, dt, rcp, add_start, add_end,
c_add, ch4_add, n2o_add, carbon_model, cfg_beam,
normalize_2000_conc, c_sens):
"""
Run the various parts of SimMod and save the results.
"""
run_years = (run_end_year - run_start_year + 1)
emission_vals = emissions(run_start_year, run_end_year, dt, rcp, add_start,
add_end, c_add, ch4_add, n2o_add)
conc = pulse_decay_runner(run_years, dt, emission_vals)
if carbon_model == 'BEAM':
try:
from beam_carbon.beam import BEAMCarbon
except ImportError as err:
raise RuntimeError("No BEAMCarbon model found! Please run the "
"installation procedure for the BEAMCarbon "
"model in '/beam_carbon/'.") from err
beam = BEAMCarbon()
beam._temperature_dependent = cfg_beam['temperature_dependent']
beam._initial_carbon = np.array(
[cfg_beam['INIT_MAT'], cfg_beam['INIT_MUP'], cfg_beam['INIT_MLO']])
beam.intervals = cfg_beam['SUBSTEPS']
beam.time_step = dt
beam.emissions = emission_vals['co2_pg'] / C_TO_CO2
beam_results = pd.melt(beam.run()[0:1])
conc['co2_ppm'] = beam_results[
'value'] * PGC_TO_MOL * 1e6 / MOLES_IN_ATMOSPHERE
if normalize_2000_conc == True:
conc['co2_ppm'] = (conc['co2_ppm'] -
conc.loc[conc['year'] == 2000, 'co2_ppm'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_co2_ppm'].min())
conc['ch4_ppb'] = (conc['ch4_ppb'] -
conc.loc[conc['year'] == 2000, 'ch4_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_ch4_ppb'].min())
conc['n2o_ppb'] = (conc['n2o_ppb'] -
conc.loc[conc['year'] == 2000, 'n2o_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_n2o_ppb'].min())
forcing = calc_radiative_forcing(conc)
warming = continuous_diffusion_model(forcing, run_years, dt, c_sens)
return warming
def run_simmod(*, run_start_year, run_end_year, dt, rcp, add_start, add_end,
c_add, ch4_add, n2o_add, carbon_model, cfg_beam,
normalize_2000_conc, c_sens):
"""
Run the various parts of SimMod and export images and CSV files.
"""
run_years = (run_end_year - run_start_year + 1)
emission_vals = emissions(run_start_year, run_end_year, dt, rcp, add_start,
add_end, c_add, ch4_add, n2o_add)
conc = pulse_decay_runner(run_years, dt, emission_vals)
if carbon_model == 'BEAM':
beam = BEAMCarbon()
beam._temperature_dependent = cfg_beam['temperature_dependent']
beam._initial_carbon = np.array(
[cfg_beam['INIT_MAT'], cfg_beam['INIT_MUP'], cfg_beam['INIT_MLO']])
beam.intervals = cfg_beam['SUBSTEPS']
beam.time_step = dt
beam.emissions = emission_vals['co2_pg'] / C_TO_CO2
beam_results = pd.melt(beam.run()[0:1])
conc['co2_ppm'] = beam_results[
'value'] * PGC_TO_MOL * 1e6 / MOLES_IN_ATMOSPHERE
if normalize_2000_conc == True:
conc['co2_ppm'] = (conc['co2_ppm'] -
conc.loc[conc['year'] == 2000, 'co2_ppm'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_co2_ppm'].min())
conc['ch4_ppb'] = (conc['ch4_ppb'] -
conc.loc[conc['year'] == 2000, 'ch4_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_ch4_ppb'].min())
conc['n2o_ppb'] = (conc['n2o_ppb'] -
conc.loc[conc['year'] == 2000, 'n2o_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_n2o_ppb'].min())
forcing = calc_radiative_forcing(conc)
warming = continuous_diffusion_model(forcing, run_years, dt, c_sens)
return warming
def run_simmod_orig(run_start_year,
run_end_year,
dt,
rcp,
CO2_PPM_1750,
CH4_PPB_1750,
N2O_PPB_1750,
c_sens,
add_start=0,
add_end=0,
c_add=0,
ch4_add=0,
n2o_add=0):
"""
Run the various parts of SimMod and export images and CSV files.
"""
run_years = (run_end_year - run_start_year + 1)
emission_vals = emissions(run_start_year, run_end_year, dt, rcp,
CO2_PPM_1750, CH4_PPB_1750, N2O_PPB_1750,
add_start, add_end, c_add, ch4_add, n2o_add)
conc = pulse_decay_runner(run_years, dt, emission_vals)
if normalize_2000_conc == True:
conc['co2_ppm'] = (conc['co2_ppm'] -
conc.loc[conc['year'] == 2000, 'co2_ppm'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_co2_ppm'].min())
conc['ch4_ppb'] = (conc['ch4_ppb'] -
conc.loc[conc['year'] == 2000, 'ch4_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_ch4_ppb'].min())
conc['n2o_ppb'] = (conc['n2o_ppb'] -
conc.loc[conc['year'] == 2000, 'n2o_ppb'].min() +
emission_vals.loc[emission_vals['year'] == 2000,
'rcp_n2o_ppb'].min())
forcing = calc_radiative_forcing(conc, CO2_PPM_1750, CH4_PPB_1750,
N2O_PPB_1750)
warming = continuous_diffusion_model(forcing, run_years, dt, c_sens)
return warming