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# NBVAL_IGNORE_OUTPUT
from os.path import join
import datetime
import dateutil
from copy import deepcopy
import numpy as np
import pandas as pd
from pymagicc import MAGICC6, rcp26, zero_emissions
from pymagicc.io import MAGICCData
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%matplotlib inline
from matplotlib import pyplot as plt
plt.style.use("ggplot")
plt.rcParams["figure.figsize"] = (12, 6)
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with MAGICC6() as magicc:
res = magicc.run(rcp26)
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# NBVAL_IGNORE_OUTPUT
res.head()
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plt.figure()
res.filter(variable="Emis*CO2*", region="World").line_plot(hue="variable")
plt.figure()
res.filter(variable="Atmos*Conc*CO2", region="World").line_plot(hue="variable");
The switches which control the time at which MAGICC switches from concentrations driven to emissions driven are all in the form GAS_SWITCHFROMXXX2EMIS_YEAR e.g. CO2_SWITCHFROMCONC2EMIS_YEAR and BCOC_SWITCHFROMRF2EMIS_YEAR.
Changing the value of these switches will alter how MAGICC runs.
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# NBVAL_IGNORE_OUTPUT
df = deepcopy(rcp26)
df["scenario"] = "RCP26_altered_co2_switch"
with MAGICC6() as magicc:
res = res.append(magicc.run(df, co2_switchfromconc2emis_year=1850))
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plt.figure()
res.filter(variable="Emis*CO2*", region="World").line_plot(hue="variable")
plt.figure()
res.filter(variable="Atmos*Conc*CO2", region="World").line_plot(hue="variable");
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# NBVAL_IGNORE_OUTPUT
res.timeseries()
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As we can see, the emissions remain unchanged but the concentrations are altered as MAGICC is now running emissions driven from 1850 rather than 2005 (the default).
To get a fully emissions driven run, you need to change all of the relevant GAS_SWITCHXXX2EMIS_YEAR flags.
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df = zero_emissions.timeseries()
time = zero_emissions["time"]
df.loc[
(
df.index.get_level_values("variable")
== "Emissions|CO2|MAGICC Fossil and Industrial"
),
:,
] = np.linspace(0, 30, len(time))
scen = MAGICCData(df)
scen.filter(variable="Em*CO2*Fossil*").line_plot(
x="time", label="CO2 Fossil", hue=None
)
scen.filter(variable="Em*CO2*Fossil*", keep=False).line_plot(
x="time", label="Everything else", hue=None
);
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# NBVAL_IGNORE_OUTPUT
with MAGICC6() as magicc:
co2_only_res = magicc.run(
scen,
endyear=scen["time"].max().year,
rf_total_constantafteryr=5000,
rf_total_runmodus="CO2",
co2_switchfromconc2emis_year=min(scen["time"]).year,
)
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for v in [
"Emis*CO2*",
"Atmos*Conc*CO2",
"Radiative Forcing",
"Surface Temperature",
]:
plt.figure()
co2_only_res.filter(variable=v, region="World").line_plot(hue="variable")
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time = zero_emissions["time"]
forcing_external = 2.0 * np.arange(0, len(time)) / len(time)
forcing_ext = MAGICCData(
forcing_external,
index=time,
columns={
"scenario": ["idealised"],
"model": ["unspecified"],
"climate_model": ["unspecified"],
"variable": ["Radiative Forcing|Extra"],
"unit": ["W / m^2"],
"todo": ["SET"],
"region": ["World"],
},
)
forcing_ext.metadata = {
"header": "External radiative forcing with linear increase"
}
forcing_ext.line_plot(x="time");
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with MAGICC6() as magicc:
forcing_ext_filename = "CUSTOM_EXTRA_RF.IN"
forcing_ext.write(
join(magicc.run_dir, forcing_ext_filename), magicc.version
)
ext_forc_only_res = magicc.run(
rf_extra_read=1,
file_extra_rf=forcing_ext_filename,
rf_total_runmodus="QEXTRA",
endyear=max(time).year,
rf_initialization_method="ZEROSTARTSHIFT", # this is default but to be sure
rf_total_constantafteryr=5000,
)
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ext_forc_only_res.filter(
variable=["Radiative Forcing", "Surface Temperature"], region="World"
).line_plot(hue="variable")
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print(MAGICC6.set_zero_config.__doc__)
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# NBVAL_IGNORE_OUTPUT
with MAGICC6() as magicc:
magicc.set_zero_config()
res_zero = magicc.run()
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res_zero.filter(
variable=["Surface Temperature", "Radiative Forcing"], region="World"
).line_plot(x="time");
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df = zero_emissions.timeseries()
time = zero_emissions["time"]
emms_fossil_co2 = (
np.linspace(0, 3, len(time))
- (1 + (np.arange(len(time)) - 500) / 500) ** 2
)
df.loc[
(
df.index.get_level_values("variable")
== "Emissions|CO2|MAGICC Fossil and Industrial"
),
:,
] = emms_fossil_co2
scen = MAGICCData(df)
scen.filter(variable="Em*CO2*Fossil*").line_plot(x="time", hue="variable")
scen.filter(variable="Em*CO2*Fossil*", keep=False).line_plot(
x="time", label="Everything Else"
)
forcing_external = 3.0 * np.arange(0, len(time)) / len(time)
forcing_ext = MAGICCData(
forcing_external,
index=time,
columns={
"scenario": ["idealised"],
"model": ["unspecified"],
"climate_model": ["unspecified"],
"variable": ["Radiative Forcing|Extra"],
"unit": ["W / m^2"],
"todo": ["SET"],
"region": ["World"],
},
)
forcing_ext.metadata = {
"header": "External radiative forcing with linear increase"
}
forcing_ext.line_plot(x="time", hue="variable");
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# NBVAL_IGNORE_OUTPUT
scen.timeseries()
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with MAGICC6() as magicc:
magicc.set_zero_config() # very important, try commenting this out and see what happens
forcing_ext_filename = "CUSTOM_EXTRA_RF.IN"
forcing_ext.write(
join(magicc.run_dir, forcing_ext_filename), magicc.version
)
co2_emms_ext_forc_res = magicc.run(
scen,
endyear=scen["time"].max().year,
co2_switchfromconc2emis_year=min(scen["time"]).year,
rf_extra_read=1,
file_extra_rf=forcing_ext_filename,
rf_total_runmodus="ALL", # default but just in case
rf_initialization_method="ZEROSTARTSHIFT", # this is default but to be sure
rf_total_constantafteryr=5000,
)
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plt.figure()
co2_emms_ext_forc_res.filter(variable="Emis*CO2*", region="World").line_plot(
x="time", hue="variable"
)
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Atmos*Conc*CO2", region="World"
).line_plot(x="time")
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Radiative Forcing", region="World"
).line_plot(x="time")
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Surface Temperature", region="World"
).line_plot(x="time");
If we adjust MAGICC's CO$_2$ temperature feedback start year, it is easier to see what is going on.
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with MAGICC6() as magicc:
magicc.set_zero_config()
forcing_ext_filename = "CUSTOM_EXTRA_RF.IN"
forcing_ext.write(
join(magicc.run_dir, forcing_ext_filename), magicc.version
)
for temp_feedback_year in [2000, 2100, 3000]:
scen["scenario"] = "idealised_{}_CO2_temperature_feedback".format(
temp_feedback_year
)
co2_emms_ext_forc_res.append(
magicc.run(
scen,
endyear=scen["time"].max().year,
co2_switchfromconc2emis_year=min(scen["time"]).year,
rf_extra_read=1,
file_extra_rf=forcing_ext_filename,
rf_total_runmodus="ALL",
rf_initialization_method="ZEROSTARTSHIFT",
rf_total_constantafteryr=5000,
co2_tempfeedback_yrstart=temp_feedback_year,
)
)
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co2_emms_ext_forc_res.filter(variable="Emis*CO2*", region="World").line_plot(
x="time", hue="variable"
)
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Atmos*Conc*CO2", region="World"
).line_plot(x="time")
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Radiative Forcing", region="World"
).line_plot(x="time")
plt.figure()
co2_emms_ext_forc_res.filter(
variable="Surface Temperature", region="World"
).line_plot(x="time");
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time = zero_emissions["time"]
co2_concs = 278 * np.ones_like(time)
co2_concs[105:] = 278 * 1.01 ** (np.arange(0, len(time[105:])))
co2_concs = MAGICCData(
co2_concs,
index=time,
columns={
"scenario": ["1%/yr CO2"],
"model": ["unspecified"],
"climate_model": ["unspecified"],
"variable": ["Atmospheric Concentrations|CO2"],
"unit": ["ppm"],
"todo": ["SET"],
"region": ["World"],
},
)
co2_concs = co2_concs.filter(year=range(1700, 2001))
time = co2_concs["time"]
co2_concs.metadata = {"header": "1%/yr atmospheric CO2 concentration increase"}
co2_concs.line_plot(x="time");
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with MAGICC6() as magicc:
co2_conc_filename = "1PCT_CO2_CONC.IN"
co2_concs.write(join(magicc.run_dir, co2_conc_filename), magicc.version)
co2_conc_driven_res = magicc.run(
file_co2_conc=co2_conc_filename,
co2_switchfromconc2emis_year=max(time).year,
co2_tempfeedback_switch=1,
co2_tempfeedback_yrstart=1870,
co2_fertilization_yrstart=1870,
rf_total_runmodus="CO2",
rf_total_constantafteryr=max(time).year,
endyear=max(time).year,
out_inverseemis=1,
)
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plt.figure()
co2_conc_driven_res.filter(
variable="Inverse Emis*CO2*", region="World"
).line_plot()
plt.figure()
co2_conc_driven_res.filter(
variable="Atmos*Conc*CO2", region="World"
).line_plot()
plt.figure()
co2_conc_driven_res.filter(
variable="Radiative Forcing", region="World"
).line_plot()
plt.figure()
co2_conc_driven_res.filter(
variable="Surface Temperature", region="World"
).line_plot();
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