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

Slides:



Advertisements
Similar presentations
jcm.chooseclimate.org UNFCCC Article 2 Article 6, A web-based climate model for global dialogue.
Advertisements

The carbon cycle and the Anthropocene Michael Raupach 1,2 1 Centre for Atmospheric, Weather and Climate Research, CSIRO Marine and Atmospheric Research,
Protecting our Health from Climate Change: a Training Course for Public Health Professionals Chapter 7: Modeling the Health Impacts of Climate Change.
Climate Change A Statistician’s Perspective Dennis Trewin Statistical Consultant, Australia.
1 Climate change impacts and adaptation: An international perspective Chris Field Carnegie Institution: Department of Global Ecology
Center of Ocean-Land- Atmosphere studies Observed Climate Changes James Kinter Lecture15: Oct 21, 2008 CLIM 101: Weather, Climate and Global Society.
The Economics of Climate Change Nicholas Stern 15 November 2006 Presentation to the Convention Dialogue, Nairobi.
Global Hydrology Modelling and Uncertainty: Climate Change and Hydrological Extremes Katie Anne Smith.
Emissions de CO2 et objectifs climatiques
Factors Shaping Long- Term Future Global Energy Demand and Carbon Emissions 7 th International Carbon Dioxide Conference September 25-30, 2005 Jae Edmonds,
IIASA A. Grübler, 2002 IPCC SRES 4 qualitative storylines 6 IA model frameworks 40 Scenarios 6 Illustrative Scenarios representative of uncertainty range.
Predicting our Climate Future
G.S. Karlovits, J.C. Adam, Washington State University 2010 AGU Fall Meeting, San Francisco, CA.
Ways to Address Climate Change Adaptation and Mitigation.
Constraining Astronomical Populations with Truncated Data Sets Brandon C. Kelly (CfA, Hubble Fellow, 6/11/2015Brandon C. Kelly,
School of Fusion Reactor Technology Erice, July 26th - August 1st 2004 A LOW CARBON ECONOMY SERGIO LA MOTTA ENEA CLIMATE PROJECT.
Modeling Developing Country Emissions Geoffrey J. Blanford, EPRI Global Climate Change Seminar May 21, 2008 Washington, DC.
Forces Causing Future Development Demographics Income & Wealth Tastes.
Fossil Fuel Economy Current economic system is based on the extensive use of fossil fuels in production 87% 87% of world energy production – Petroleum:
Global Climate Change and its Distributional Impacts Maurizio Bussolo, Rafael de Hoyos, Denis Medvedev and Dominique van der Mensbrugghe The World Bank.
Does Shale Gas have a role in Annex 1 climate change commitments? Prof Kevin Anderson and Dr John Broderick Tyndall Manchester.
Page 1GMES - ENSEMBLES 2008 ENSEMBLES. Page 2GMES - ENSEMBLES 2008 The ENSEMBLES Project  Began 4 years ago, will end in December 2009  Supported by.
The Impact of Climate Change and Climate Policy on the Canadian Economy Jim Davies Jim MacGee Jacob Wibe.
Working with Uncertainty Population, technology, production, consumption Emissions Atmospheric concentrations Radiative forcing Socio-economic impacts.
Adapting to climate change to protect health – a Pacific view Alistair Woodward School of Population Health University of Auckland.
Climate Baseline Scenarios and GCMs performance By Mario Bidegain (Facultad de Ciencias – UR LA32/LA26) Ines Camilloni (Facultad de Ciencias – UBA LA26)
The latest science on the climate change challenge David Karoly, Univ of Melbourne TC Larry, 2006 From Bureau of Meteorology.
NORWEGIAN SCHOOL OF MANAGEMENT Climate post COP 15 in a Limits to Growth perspective Climate post COP 15 in a Limits to Growth perspective Jorgen Randers.
AP STATISTICS LESSON COMPARING TWO PROPORTIONS.
Possibilities for C / GHG mitigation in agricultural lands Pete Smith Professor of Soils & Global Change School of Biological Sciences, University of Aberdeen,
Sub-GLOBAL GUESSWORK FRAMEWORK space time GLOBAL GCI C & C - A Syntax for Survival Globalisation of Consciousness Science and the Risks.
Role of Integrated Assessment Modelling (IAM) in climate change policy analysis The Global Integrated Assessment Model (GIAM) An ABARE-CSIRO joint initiative.
Why we have to fight for our right to develop.  We are developing very rapidly  The west caused problems and now want us to fix them  We are the world’s.
Fredrik Hedenus Physical Resource Theory Fredrik Hedenus Physical Resource Theory Chalmers University of Technology. The role of.
Climate Change : The State of Knowledge Bryson Bates Leader, Pathways to Adaptation Theme 22 April 2009 Climate Adaptation National Research Flagship.
Improving carbon cycle models with radar retrievals of forest biomass data Mathew Williams, Tim Hill and Casey Ryan School of GeoSciences, University of.
Key information from FDOS Global distribution of plant communities as described by quantitative traits [and their association with phylogenetic composition??]
E.A. Mathez, 2009, Climate Change: The Science of Global Warming and Our Energy Future, Columbia University Press. Source: Solomon et al., 2007 Chapter.
Newton Paciornik BRAZIL Policy Goals and Common Metrics Implications Bonn, 04 April 2012 Workshop on common metrics to calculate the CO 2 equivalence of.
Ideas.unimelb.edu.au The Warning of the Warming World Professor David Karoly, School of Earth Sciences.
The Impact of Climatic Shocks on Alberta’s Economy: A Vector Autoregression Analysis by Wes Lu Supervisors: Vic Adamowicz and Sandeep Mohapatra Department.
Keeping warming below 2°C: link and consistency between INDC assessments and long-term goals Joeri Rogelj Side Event COP21 - Paris 1 December 2015.
Assessing INDCs and their implications: Resources, tools, and analysis Louise Jeffery, on behalf of the PRIMAP team: 1 December 2015 Johannes Gütschow,
Dr John Broderick, KT Fellow Shale gas in a low carbon future. Golden age or gilded cage?
KSLA – FACCE Seminar Slide 1 FACUTLY OF SCIENCE Department of Plant and Environmental Sciences John R Porter SCIENCE Copenhagen University DK NRI Greenwich.
NORWEGIAN SCHOOL OF MANAGEMENT The Big Island as A Role Model The Big Island as A Role Model Jorgen Randers Professor Center for Climate Strategy Norwegian.
© dreamstime CLIMATE CHANGE 2014 Mitigation of Climate Change Working Group III contribution to the IPCC Fifth Assessment Report.
ADD BUSINESS UNIT/FLAGSHIP NAME NATIONAL OUTLOOK 2015 CSIRO Australian National Outlook Economic activity, resource use, environmental performance and.
Climate Change and Impact on Corn and Grain Quality Eugene S. Takle Professor of Agricultural Meteorology, Department of Agronomy Professor of Atmospheric.
IPCC Working Group I Summary For Policymakers: The Physical Science Basis Assembled by Brenda Ekwurzel March 2, Slides for Communicating.
India’s long-term growth potential and the implications for Australia Bill Brummitt General Manager, International & G20 Division.
SLCP Benefits Toolkit:
Slide pack of all figures in the main report and the chart overview
Optimal climate policy
Models.
science-based target setting
By Peters, et al TYSON METCALF ECON 5430
Geography of greenhouse gas emissions
Climate Modeling General Circulation Models
Geography of greenhouse gas emissions
Decomposing Inequalities in CO2-Emissions
Fig. 1 Fig. 1. Observed global CO2 emissions including all terms in Eq. 1, from both the EIA (1980–2004) and global CDIAC (1751–2005) data, compared with.
CHAPTER 1 Exploring Data
Chapter 18 Growth and Sustainability in the Twenty-First Century
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Mitigation: Major Climate Change Can Be Avoided. Warren M
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Presentation transcript:

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 CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

State variables CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

Rates inferred from probability distributions CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

Derived quantities CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

Scenarios CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

Model overview CSIRO. A probabilistic approach to exploring global dynamics Cumulative emissions Population GDP birth rate death rate energy use per capita GDP per capita intrinsic growth rate Peak temperature change carbon intensity of energy use Damage rate

CSIRO. A probabilistic approach to exploring global dynamics Birth rate vs GDP per capita Data from and

CSIRO. A probabilistic approach to exploring global dynamics Birth rate vs GDP per capita

CSIRO. A probabilistic approach to exploring global dynamics Death rate vs GDP per capita Data from and

CSIRO. A probabilistic approach to exploring global dynamics Death rate vs GDP per capita

CSIRO. A probabilistic approach to exploring global dynamics Energy use per capita vs GDP per capita Data from and

CSIRO. A probabilistic approach to exploring global dynamics Energy use per capita vs GDP per capita

Modelled historical distributions: population CSIRO. A probabilistic approach to exploring global dynamics * World population

Modelled historical distributions: cumulative emissions CSIRO. A probabilistic approach to exploring global dynamics * World cumulative emissions

Modelled historical distributions: world GDP CSIRO. A probabilistic approach to exploring global dynamics * World GDP

Mitigation CSIRO. A probabilistic approach to exploring global dynamics

Climate damages Committed peak temperature change due to cumulative emissions: (Raupach et al, 2010)

Climate damages CSIRO. A probabilistic approach to exploring global dynamics Relationship between damage rate and T peak :

Climate damages CSIRO. A probabilistic approach to exploring global dynamics Relationship between damage rate and T peak :

Proportion of runs with T peak < 2˚C CSIRO. A probabilistic approach to exploring global dynamics Mitigation completed sooner Steeper onset of damages

Proportion of runs with T peak < 2˚C CSIRO. A probabilistic approach to exploring global dynamics Mitigation completed sooner Steeper onset of damages

CSIRO. A probabilistic approach to exploring global dynamics Proportion of runs with rising GDP per capita Gentler onset of damages Mitigation completed sooner

CSIRO. A probabilistic approach to exploring global dynamics Proportion of runs with rising GDP per capita Gentler onset of damages Mitigation completed sooner

CSIRO. A probabilistic approach to exploring global dynamics Proportion of runs with T peak < 2˚C AND rising GDP per capita Gentler onset of damages Mitigation completed sooner

Population <10 billion only CSIRO. A probabilistic approach to exploring global dynamics Gentler onset of damages Mitigation completed sooner

Max allowable energy use per capita CSIRO. A probabilistic approach to exploring global dynamics Gentler onset of damages Mitigation completed sooner Energy use per capita (kg oil equiv/person/yr)

CSIRO. A probabilistic approach to exploring global dynamics Energy use per capita vs GDP per capita Data from and

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. CSIRO. A probabilistic approach to exploring global dynamics

Contact Us Phone: or Web: Thank you CSIRO Land and Water Dr Nicky Grigg Phone:

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. CSIRO. A probabilistic approach to exploring global dynamics

Model equations: population Population (P) births/year deaths/year k birth is the birth rate per capita (births/person/year) k death is the death rate per capita (births/person/year) Birth and death rates change over time and are a function of GDP per capita

CSIRO. A probabilistic approach to exploring global dynamics Model equations: cumulative emissions Cumulative emissions since 1751 (E) c is the carbon intensity of energy (gC/MJ) k energy 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

CSIRO. A probabilistic approach to exploring global dynamics Model equations: GDP Climate-related damage rate GDP (A) Population- related GDP growth rate Intrinsic GDP growth rate = 0 : no population impact on GDP growth = 1 : population impact on GDP growth rate