Variable reference

Each entry lists a model variable's description, units, dimensions and availability.

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Required parameters

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All variables

GDP_gross

Regional gross GDP from the Cobb-Douglas production function, before deducting damages, adaptation costs, mitigation costs, and financial transfers.

Units: usd*trillion/yr
Dimensions: t, regions

GDP_loss

Regional GDP loss relative to the baseline, calculated as baseline GDP minus net GDP, divided by baseline GDP. Includes direct costs and indirect effects on economic growth.

Units: fraction_of_baseline_GDP
Dimensions: t, regions

GDP_net

Regional net GDP available for investment and consumption after mitigation costs, financial transfers, and any included damage and adaptation costs.

Units: usd*trillion/yr
Dimensions: t, regions

LBD_factor

Multiplier on marginal abatement costs from learning by doing, based on cumulative emissions avoided relative to the SSP baseline through the preceding timestep. Starts at one; lower values mean cheaper mitigation.

Units: not declared
Dimensions: t

LOT_factor

Multiplier on marginal abatement costs from exogenous technological progress, independent of mitigation undertaken. Starts at one; a positive learning rate reduces it at each model timestep.

Units: not declared
Dimensions: t

NPV

Sum of discounted global welfare (Net Present Value of global welfare), discounted with the pure rate of time preference.

Units: not declared
Dimensions: t

NPV

Description not provided.

Units: not declared
Dimensions: t

adaptation_costs

Total adaptation costs from all sectors, as a fraction of GDP.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

adaptation_costs_abs

Total adaptation costs from all sectors, in currency units.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

attributed_emission_reductions

Emission reductions attributed to a region after trading, equal to its physical emission reductions plus its emission-reduction trading balance.

Units: GtCO2/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['emissiontrade module'] = 'emissiontrade'
model = MIMOSA(params)

avoided_damage_costs

Avoided damages, calculated as the difference between the damage costs in a no-policy baseline run and the damage costs in this run.

Units: fraction_of_GDP
Dimensions: t, regions
Requires a no-policy baseline.

baseline_emissions

Regional baseline CO2 emissions (emissions before applying mitigation). Taken from the selected SSP or calculated from baseline carbon intensity and model GDP.

Units: GtCO2/yr
Dimensions: t, regions

capital_stock

Regional stock of productive capital. Increases through investment and decreases through depreciation; used in the Cobb-Douglas production function.

Units: usd*trillion/yr
Dimensions: t, regions

carbon_price

Regional carbon price required to achieve the mitigation level on the marginal abatement cost curve, accounting for regional and SSP calibration and technological learning. Set to zero at the initial timestep.

Units: usd*trillion/GtCO2/yr
Dimensions: t, regions

consumption

Regional physical consumption, equal to net GDP minus investment.

Units: usd*trillion/yr
Dimensions: t, regions

damage_costs

Total damages from all sectors (excluding non-market impacts like mortality), as a fraction of GDP.

Units: fraction_of_GDP
Dimensions: t, regions

damage_costs

Total regional COACCH damage costs as a fraction of gross GDP, relative to the model start. Sum of the temperature-dependent and separate sea-level-rise damage terms.

Units: fraction_of_GDP
Dimensions: t, regions

damage_costs_abs

Total damages from all sectors (excluding non-market impacts like mortality), in currency units.

Units: usd*trillion/yr
Dimensions: t, regions

damage_costs_abs

Total regional COACCH damage costs in currency units, calculated as the damage fraction times gross GDP.

Units: usd*trillion/yr
Dimensions: t, regions

domestic_mitigation_costs_abs

Cost of emission reductions physically carried out in a region, calculated as the area under its marginal abatement cost curve times baseline emissions.

Units: usd*trillion/yr
Dimensions: t, regions

effort_sharing_common_level

Common mitigation-cost share of gross GDP targeted across regions. Each region's attributed mitigation-cost share is constrained to remain approximately equal to this value.

Units: fraction_of_GDP
Dimensions: t

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'equal_mitigation_costs'
model = MIMOSA(params)

or

params = load_params()
params['model structure']['effortsharing module'] = 'equal_total_costs'
model = MIMOSA(params)

effort_sharing_common_level

Common total-cost share of gross GDP targeted across regions through 2100, including mitigation, damages, adaptation and financial transfers. Regional totals are constrained to remain approximately equal to this value.

Units: fraction_of_GDP
Dimensions: t

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'equal_mitigation_costs'
model = MIMOSA(params)

or

params = load_params()
params['model structure']['effortsharing module'] = 'equal_total_costs'
model = MIMOSA(params)

effortsharing_AP_allowances

Regional emission allowances prescribed by the ability-to-pay rule, equal to baseline emissions minus the globally corrected regional reduction. These are the targets for the region's emission allowances after trading.

Units: not declared
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'ability_to_pay'
model = MIMOSA(params)

effortsharing_AP_inv_correction_factor

Global multiplier applied to provisional ability-to-pay reductions so their sum matches the global emission reduction from baseline. Set to one at the initial time step.

Units: not declared
Dimensions: t

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'ability_to_pay'
model = MIMOSA(params)

effortsharing_AP_reductions_before_correction

Provisional regional emission reductions under the ability-to-pay rule, before global correction. The global reduction fraction is scaled by the cube root of the region's baseline GDP per capita relative to the global average, then applied to its baseline emissions.

Units: not declared
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'ability_to_pay'
model = MIMOSA(params)

emission_reduction_trading_balance

Difference between attributed and physical emission reductions due to trading. Positive values increase the reductions attributed to the region; negative values decrease them.

Units: GtCO2/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['emissiontrade module'] = 'emissiontrade'
model = MIMOSA(params)

financial_transfer

Description not provided.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['financialtransfer module'] = 'globaldamagepool'
model = MIMOSA(params)

financial_transfer_abs

Description not provided.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['financialtransfer module'] = 'globaldamagepool'
model = MIMOSA(params)

global_GDP_gross

Global gross GDP, calculated as the sum of regional gross GDP.

Units: usd*trillion/yr
Dimensions: t

global_GDP_loss

Global GDP loss relative to the baseline, calculated as global baseline GDP minus global net GDP, divided by global baseline GDP.

Units: fraction_of_baseline_GDP
Dimensions: t

global_GDP_net

Global net GDP, calculated as the sum of regional net GDP.

Units: usd*trillion/yr
Dimensions: t

global_adaptation_costs

Global total adaptation costs from all sectors, as a fraction of global GDP.

Units: fraction_of_GDP
Dimensions: t

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

global_avoided_damage_costs

Global aggregation of avoided damages

Units: fraction_of_GDP
Dimensions: t
Requires a no-policy baseline.

global_carbon_price

Population-weighted average of regional carbon prices, used to value emission trades.

Units: not declared
Dimensions: t

Available when:

params = load_params()
params['model structure']['emissiontrade module'] = 'emissiontrade'
model = MIMOSA(params)

global_cost_per_emission_reduction_unit

Average global mitigation cost per unit of CO2 emission reduction, calculated as total mitigation costs divided by total regional emission reductions. Set to zero at the initial timestep.

Units: usd*trillion/GtCO2
Dimensions: t

global_cumulative_emissions

Cumulative global net CO2 emissions since the model start, including any exogenous emissions pulse. Calculated using trapezoidal integration or timestep-weighted summation, depending on configuration.

Units: GtCO2
Dimensions: t

global_damage_costs

Global total damages from all sectors (excluding non-market impacts like mortality), as a fraction of global GDP.

Units: fraction_of_GDP
Dimensions: t

global_damage_costs

Global COACCH damage costs as a fraction of global gross GDP, calculated from the sum of regional damage costs in currency units.

Units: fraction_of_GDP
Dimensions: t

global_emission_reduction_per_cost_unit

Average global CO2 emission reduction per unit of mitigation spending, calculated as total regional emission reductions divided by total mitigation costs. Set to zero at the initial timestep.

Units: GtCO2/usd/trillion
Dimensions: t

global_emissions

Global net CO2 emissions, calculated as the sum of regional net emissions. Negative values represent net CO2 removal.

Units: GtCO2/yr
Dimensions: t

global_indirect_costs

Global GDP loss beyond direct costs, calculated as global GDP loss minus total direct costs divided by global baseline GDP.

Units: fraction_of_baseline_GDP
Dimensions: t

global_mitigation_costs

Global mitigation costs as a fraction of global gross GDP, calculated from the sum of regional mitigation costs.

Units: fraction_of_GDP
Dimensions: t

global_relative_cumulative_emissions

Cumulative global CO2 emissions divided by cumulative SSP baseline emissions since the model start. Set to one at the initial timestep.

Units: not declared
Dimensions: t

global_welfare

Undiscounted global welfare at each timestep, calculated as the sum of regional per-capita utilities weighted by population.

Units: not declared
Dimensions: t

global_welfare

Undiscounted global welfare, calculated by applying the utility function to global per-capita consumption after non-market damages and multiplying by global population.

Units: not declared
Dimensions: t

global_welfare

Undiscounted global welfare, calculated by aggregating regional welfare contributions with the configured inequality aversion and elasticity of marginal utility.

Units: not declared
Dimensions: t

indirect_costs

Regional GDP loss beyond direct costs, expressed as a fraction of baseline GDP. Includes effects of reduced capital accumulation.

Units: fraction_of_baseline_GDP
Dimensions: t, regions

investments

Regional investment in productive capital, calculated as the fixed savings rate times net GDP.

Units: usd*trillion/yr
Dimensions: t, regions

labourprod_adaptation_costs

Adaptation costs for labour productivity (as a fraction of GDP) (applied only to heat-related damages, not cold-related benefits)

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

labourprod_adaptation_costs_abs

Adaptation costs for labour productivity (absolute values) (applied only to heat-related damages, not cold-related benefits)

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

labourprod_adaptation_level

Adaptation level for labour productivity (applied only to heat-related damages, not cold-related benefits)

Units: fraction_of_gross_damages
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

labourprod_damage_costs

Gross damages from heat-related labour productivity loss (e.g. hot regions get hotter), without adaptation

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

labourprod_damage_costs

Residual damages for labour productivity after adaptation (heat-related component only)

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

labourprod_damage_costs_benefits

Benefits from reduced cold days for labour productivity (e.g. cold regions get less cold). No adaptation is applied to these benefits, as they are not related to heat stress.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

labourprod_damage_costs_gross

Gross damages from heat-related labour productivity loss (e.g. hot regions get hotter), without adaptation

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

labourprod_damage_costs_net

Sum of heat-related residual damages and cold-related benefits for labour productivity (net damages)

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

learning_factor

Combined technological-learning multiplier on marginal abatement costs, calculated as the product of the learning-by-doing and learning-over-time factors. Lower values mean cheaper mitigation.

Units: not declared
Dimensions: t

market_and_non_market_damage_costs

Total market and non-market damages, as a fraction of GDP.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

market_and_non_market_damage_costs_abs

Total market and non-market damages, in currency units.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

mitigation_cost_trading_balance

Net payment for emission trading, added to domestic mitigation costs. Positive values are payments and negative values are revenues; the balances sum to zero across regions.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['emissiontrade module'] = 'emissiontrade'
model = MIMOSA(params)

mitigation_costs

Mitigation costs attributed to a region, including any mitigation-cost trading balance, divided by its gross GDP.

Units: fraction_of_GDP
Dimensions: t, regions

mitigation_costs_abs

Regional mitigation costs in currency units, equal to domestic mitigation costs plus the mitigation-cost trading balance.

Units: usd*trillion/yr
Dimensions: t, regions

mitigation_level

Fraction of baseline emissions reduced through mitigation. Zero means no mitigation, one means net-zero emissions, and values above one represent net-negative emissions.

Units: fraction_of_baseline_emissions
Dimensions: t, regions

mortality_cold_related

Reduced cold-related mortality, in absolute numbers, compared to start year of the run (2025).

Units: billion*people
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

mortality_damage_costs

Mortality damage costs expressed as % of GDP

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['monetise_mortality'] = True
model = MIMOSA(params)

mortality_damage_costs_abs

Mortality damage costs in currency units. Since the extra heat-related deaths and reduced cold-related deaths are considered, this value can be positive or negative, depending on the region, time, and temperature.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['monetise_mortality'] = True
model = MIMOSA(params)

mortality_heat_related

Extra heat-related mortality, in absolute numbers. Extra is compared to start year of the run (2025).

Units: billion*people
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

mortality_net

Sum of extra heat-related mortality and reduced cold-related mortality, in absolute numbers.

Units: billion*people
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

mortality_vsl

Value of statistical life (VSL) in currency units, calculated as the relative VSL times GDP per capita

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['monetise_mortality'] = True
model = MIMOSA(params)

non_market_damage_costs_abs

Total non-market damages (monetised mortality), in currency units.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['monetise_mortality'] = True
model = MIMOSA(params)

non_slr_damage_costs

Temperature-dependent regional damages as a fraction of gross GDP, relative to the model start. Includes sea-level-rise impacts when combined damage curves are selected.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'COACCH'
model = MIMOSA(params)

regional_emission_allowances

Regional emission allowances without trading, equal to the region's physical net CO2 emissions.

Units: GtCO2/yr
Dimensions: t, regions

regional_emission_allowances

Regional emission allowances, equal to baseline emissions minus the emission reductions attributed to the region after trading.

Units: GtCO2/yr
Dimensions: t, regions

regional_emission_reductions

Regional reduction in CO2 emissions relative to the baseline, calculated as baseline emissions minus actual net emissions. Can exceed baseline emissions when net emissions are negative.

Units: GtCO2/yr
Dimensions: t, regions

regional_emissions

Regional net CO2 emissions after mitigation, calculated as baseline emissions times one minus the mitigation level. Negative values represent net CO2 removal.

Units: GtCO2/yr
Dimensions: t, regions

riverine_adaptation_costs

Adaptation costs for riverine flooding, as a fraction of GDP.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

riverine_adaptation_costs_abs

Absolute adaptation costs for riverine flooding, in currency units. Used to calculate the adaptation level.

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

riverine_adaptation_level

Adaptation level for riverine flooding, as a fraction of gross damages. 0 means that no damages are avoided, while 1 means that all damages are avoided.

Units: fraction_of_gross_damages
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

riverine_damage_costs

Gross damages from riverine flooding, without adaptation.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

riverine_damage_costs

Residual damages from riverine flooding, after adaptation. If noadaptation is chosen, this variable represents the gross damages.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
model = MIMOSA(params)

riverine_damage_costs_gross

Gross damages from riverine flooding, without adaptation.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

slr_adaptation_costs

Adaptation costs for sea-level rise, as a fraction of GDP.

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

slr_adaptation_costs_abs

Absolute adaptation costs for sea-level rise, in currency units. Used to calculate the adaptation level

Units: usd*trillion/yr
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

slr_adaptation_level

Adaptation level for sea-level rise, as a fraction of gross damages. 0 means that no damages are avoided, while 1 means that all damages are avoided.

Units: fraction_of_gross_damages
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

slr_antarctic_ocean_temp

Antarctic subsurface-ocean temperature proxy above pre-industrial levels. Responds with a delay to global warming and drives Antarctic ice-sheet loss.

Units: degC_above_PI
Dimensions: t

slr_cumais

Global mean sea-level rise from Antarctic ice-sheet loss, relative to 1900. Includes background loss, an ocean-temperature response, and a possible faster response at high warming.

Units: m
Dimensions: t

slr_cumgis

Global mean sea-level rise from Greenland ice-sheet loss, relative to 1900. Gradually approaches a temperature-dependent equilibrium contribution.

Units: m
Dimensions: t

slr_cumgsic

Global mean sea-level rise from the loss of glaciers and ice caps outside the Greenland and Antarctic ice sheets, relative to 1900.

Units: m
Dimensions: t

slr_cumlws

Additional global mean sea-level rise from changes in land-water storage after the model start. Starts at zero and increases at a constant annual rate; historical land-water contributions are already included in the initial total sea level.

Units: m
Dimensions: t

slr_damage_costs

Gross damages from sea-level rise, without adaptation

Units: fraction_of_GDP
Dimensions: t, regions

slr_damage_costs

Residual damages from sea-level rise, after adaptation. If noadaptation is chosen, this variable represents the gross damages.

Units: fraction_of_GDP
Dimensions: t, regions

slr_damage_costs

Regional sea-level-rise damages as a fraction of gross GDP, relative to initial sea level. Includes adaptation costs when optimal-adaptation curves are selected; zero when combined damage curves are used.

Units: fraction_of_GDP
Dimensions: t, regions

slr_damage_costs_gross

Gross damages from sea-level rise, without adaptation

Units: fraction_of_GDP
Dimensions: t, regions

Available when:

params = load_params()
params['model structure']['damage module'] = 'ACCREU'
params['economics']['damages']['accreu']['adaptation'] = 'sectoral'
model = MIMOSA(params)

slr_thermal

Total global mean sea-level rise from ocean thermal expansion, relative to 1900. Sum of the fast and slow contributions.

Units: m
Dimensions: t

slr_thermal_fast

Global mean sea-level rise from the fast thermal-expansion response of the upper ocean, relative to 1900.

Units: m
Dimensions: t

slr_thermal_slow

Global mean sea-level rise from the slow thermal-expansion response of the deep ocean, relative to 1900.

Units: m
Dimensions: t

temperature

Global mean warming above pre-industrial levels. Calculated as initial warming plus the temperature response to cumulative CO2 emissions, determined by the TCRE.

Units: degC_above_PI
Dimensions: t

total_SLR

Total global mean sea-level rise relative to 1900. Sum of thermal expansion, glacier and ice-sheet loss, and future changes in land-water storage.

Units: m
Dimensions: t

total_direct_costs_abs

Total regional direct costs in currency units: the sum of mitigation costs, damage costs, and adaptation costs.

Units: usd*trillion/yr
Dimensions: t, regions

utility

Regional per-capita utility, calculated from consumption after deducting monetised non-market damages, using the elasticity of marginal utility.

Units: not declared
Dimensions: t, regions

utility

Regional consumption per person after deducting monetised non-market damages, reported as the utility variable in the cost-minimising setting.

Units: not declared
Dimensions: t, regions

utility

Regional welfare contribution, equal to population times welfare-adjusted consumption per person raised to one minus inequality aversion. Welfare-adjusted consumption deducts monetised non-market damages.

Units: not declared
Dimensions: t, regions