A probabilistic approach to exploring global dynamics Nicky Grigg, Fabio Boschetti, Markus Brede, John Finnigan CSIRO, Australia AIMES Open Science Conference,

A probabilistic approach to exploring global dynamics

Nicky Grigg, Fabio Boschetti, Markus Brede, John Finnigan

CSIRO, Australia

AIMES Open Science Conference, Edinburgh

11 May 2010

CSIRO. A probabilistic approach to exploring global dynamics

What, how and why?

• What:• Interactions: population, carbon emissions, economy

• How:• Low dimensional dynamic model

• Rates estimated from probability distributions fitted to UN datasets

• Ensembles of model runs to capture uncertainty and variability

• Why:• Trial probabilistic approach

• Qualitative insights, informed by quantitative dynamics

Model overview


Cumulative emissions

Population GDP

birthrate

deathrate

energy use per capita

GDP per capita

intrinsic growth rate

Peak temperature change

carbon intensity of energy use

Damagerate

State variables



Population GDP

birthrate

deathrate


GDP per capita




Damagerate

Rates inferred from probability distributions



Population GDP

birthrate

deathrate


GDP per capita




Damagerate

Derived quantities



Population GDP

birthrate

deathrate


GDP per capita




Damagerate

Scenarios



Population GDP

birthrate

deathrate


GDP per capita




Damagerate

Model overview



Population GDP

birthrate

deathrate


GDP per capita




Damagerate


Birth rate vs GDP per capita

Data from http://unstats.un.org and http://data.un.org

http://unstats.un.org/

http://data.un.org/


Birth rate vs GDP per capita


Death rate vs GDP per capita



http://data.un.org/


Death rate vs GDP per capita


Energy use per capita vs GDP per capita



http://data.un.org/



Modelled historical distributions: population


* World population

Modelled historical distributions: cumulative emissions


* World cumulative emissions

Modelled historical distributions: world GDP


* World GDP

Mitigation



Climate damages

076.2

9.6211ln

ETpeak

Committed peak temperature change due to cumulative emissions:

(Raupach et al, 2010)

Climate damages


Relationship between damage rate and Tpeak:

Climate damages


Relationship between damage rate and Tpeak:

Proportion of runs with Tpeak < 2˚C


Mitigation completed sooner

Steeper onsetof damages

Proportion of runs with Tpeak < 2˚C



Steeper onsetof damages


Proportion of runs with rising GDP per capita

Gentler onsetof damages



Proportion of runs with rising GDP per capita




Proportion of runs withTpeak < 2˚C AND rising GDP per capita



Population <10 billion only




Max allowable energy use per capita








http://data.un.org/

Conclusions

• Data-driven probabilistic approach:• Uses more of the information inherent in datasets

• Allows propagation of variability and uncertainty

• Forward model to 2100 generates distributions of trajectories consistent with system evolving under realistic rates

• Probability distributions are more informative than single trajectories.

• Qualitative dynamics:• Surfaces in mitigation-damage space: steep boundary between

‘poverty trap’ and ‘good life’.

• Population-energy patterns within mitigation-damage scenario.

• Applicability more broadly• Framework suitable for studying other systems in which

environmental limits interact with population and economy.


Contact UsPhone: 1300 363 400 or +61 3 9545 2176

Email: [email protected] Web: www.csiro.au

Thank you

CSIRO Land and WaterDr Nicky Grigg

Phone: +61 2 6246 5569Email: [email protected]

Model assumptions

• Population (P):• birth and death rates.

• Cumulative carbon dioxide emissions since1751 (E)• population size

• energy use per capita

• carbon intensity of energy supply.

• GDP (A):• Endogenous and population-related growth rates

• Climate feedback on GDP:• Global peak temperature change is a function of cumulative carbon

dioxide emissions.

• Temperature changes damage the economy.



Model equations: population

PkPkdt

dPdeathbirth

Population (P)

births/year deaths/year

kbirth is the birth rate per capita (births/person/year)kdeath is the death rate per capita (births/person/year)

Birth and death rates change over time and are a function of GDP per capita


Model equations: cumulative emissions

Pckdt

dEenergy

Cumulative emissions since 1751 (E)

c is the carbon intensity of energy (gC/MJ)kenergy is the rate of energy use per capita (MJ/person/year)P is the population

Energy use per capita varies over time and is a function of GDP per capita.Carbon intensity per MJ changes over time as an exogenously prescribed mitigation trajectory


Model equations: GDP

AkAkAkt

AAP damage2A2Ad

d

Climate-related damage rate

GDP (A)

Population-related GDP growth rate

Intrinsic GDP growth rate

t

P

Pk AP d

d2

= 0 : no population impact on GDP growth

= 1 : population impact on GDP growth rate

A probabilistic approach to exploring global dynamics Nicky Grigg, Fabio Boschetti, Markus Brede, John Finnigan CSIRO, Australia AIMES Open Science Conference,

Documents

global dynamics energy

global dynamics mitigation

global dynamics proportion

world gdp slide

global dynamics relationship

world gdp csiro

population csiro

mitigation csiro