State of the Planet Do you expect to use modeling in your life/career? A. Yes B. No C. Don’t know

What is a Model? From Andy Ruina, TAM, Cornell System Model Model’s manipulation rules System Represent’n behavior System behavior System’s workings Translate between system and model

Limits to Growth Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Humans on the Planet Population Resources Industrial output Pollution, etc

Limits to Growth Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Humans on the Planet Population Resources Industrial output Pollution, etc Numbers Equations representing interactions Graphs of how the numbers change over time

Disease Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Spread of infectious disease through the population

Disease Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Spread of infectious disease through the population Equations to represent - transmission rates - contact rates, - vaccination efficiency…

Disease Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Spread of infectious disease through the population Equations to represent - transmission rates - contact rates, - vaccination efficiency… Answer questions like: How much of the population do we have to vaccinate to prevent an epidemic?

Who Can Model? You don’t have to be a mathematician to use quantitative models! Just make friends with a mathematician & learn enough to communicate with them… Take: Multivariable Calculus & Linear Algebra & Modeling, Dynamical Systems or Differential Eq’s

Great Modeling Course at Cornell BIOEE/MATH 362 Dynamic Models in Biology Steve Ellner John Guckenheimer

What Can a Novelist Do? Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model The Sunderban Islands Poverty and hunger Conservation Mangroves Cyclones

What Can a Novelist Do? Fiction can help people to inhabit a place in their imaginations. To see the ways in which the lives of the animals, the lives of the trees, and the lives of the human beings link together. -Amitav Ghosh on “The Hungry Tide” Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model The Sunderban Islands Poverty and hunger Conservation Mangrove forests Cyclones Novel “The Hungry Tide” by Amitav Ghosh

Limits to Growth Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Humans on the Planet Population Resources Industrial output Pollution, etc Numbers Equations representing interactions Graphs of how the numbers change over time

Limits to Growth Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Humans on the Planet Population Resources Industrial output Pollution, etc Numbers Equations representing interactions Graphs of how the numbers change over time Huge, interdisciplinary project!

Limits to Growth Model Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Humans on the Planet Population Resources Industrial output Pollution, etc Numbers Equations representing interactions Graphs of how the numbers change over time Huge, interdisciplinary project! Model scenarios are input here

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies 2.Double non-renewable resources 3.(2) + Pollution control technology 4.(3) + land yield technology 5.(4) + land erosion technology 6.(5) + resource efficient technology

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies 2.Double non-renewable resources 3.(2) + pollution control technology 4.(3) + land yield technology 5.(4) + land erosion technology 6.(5) + resource efficient technology 7.(2) + population control 8.(7) + industrial output control

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies 2.Double non-renewable resources 3.(2) + pollution control technology 4.(3) + land yield technology 5.(4) + land erosion technology 6.(5) + resource efficient technology 7.(2) + population control 8.(7) + industrial output control 9.Everything: (6)+(8)

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies 2.Double non-renewable resources 3.(2) + pollution control technology 4.(3) + land yield technology 5.(4) + land erosion technology 6.(5) + resource efficient technology 7.(2) + population control 8.(7) + industrial output control 9.Everything: (6)+(8) 10. (9) adopted 20 years earlier.

Model Scenarios: Pathways into Unknown 1.Continuation of 20th century policies

Pathway 2 into the Unknown: What will happen under Scenario 2? Double non-renewable resources A. Sustainable population B. Exhausted resources C. High pollution D. Food scarcity E. Industry crash

Pathway 6 into the Unknown: What will happen under Scenario 6? Double non-renewable resources, with pollution control, land yield technology, land erosion technology, and resource efficient technology A. Sustainable population B. Exhausted resources C. High pollution D. Food scarcity E. Industry crash

Pathway 8 into the Unknown: What will happen under Scenario 8? Double non-renewable resources with population control and industrial output control A. Sustainable population B. Exhausted resources C. High pollution D. Food scarcity E. Industry crash

Pathway 9 into the Unknown: What will happen under Scenario 9? Everything: Double the non-renewable resources, pollution control, land yield, land erosion, and resource efficient technology, population and industrial output control A. Sustainable population B. Exhausted resources C. High pollution D. Food scarcity E. Industry crash

Model Scenarios: A Novelist’s View “It is when we think of the world that … indifference might bring into being, that we recognize the urgency of remembering the stories we have not yet written.” -Amitav Ghosh

Intergov. Panel on Climate Change scientific expert reviewers 800+ contributing authors and 450+ lead authors from 130+ countries 6 years work 4 volumes 1 Report

Intergov. Panel on Climate Change scientific expert reviewers 800+ contributing authors and 450+ lead authors from 130+ countries 6 years work 4 volumes 1 Report Fourth Assessment Report: “Climate Change 2007”

2500+ scientific expert reviewers 800+ contributing authors and 450+ lead authors from 130+ countries 6 years work 4 volumes 1 Report Fourth Assessment Report: Climate Change 2007 Third Assessment Report (TAR) was 2001 Intergov. Panel on Climate Change

IPCC Group I: The Physical Science Basis We read the summary. Full report due out soon. Group II: Impacts, Adaptation, Vulnerability Includes: Food, Water, Ecosystems, Industry, Health, Global and Regional. Group III: Mitigation of Climate Change Includes: Energy, Waste, Transport, Industry, Agriculture, Forestry, etc. IV: Synthesis Report

IPCC Summary for Policy Makers A major advance of this assessment of climate change projections … is the large number of simulations available from a broader range of models.

IPCC Summary for Policy Makers A major advance of this assessment of climate change projections … is the large number of simulations available from a broader range of models. Model experiments show that… Best-estimate projections from models indicate… Based on a range of models, it is likely that…

IPCC Summary for Policy Makers A major advance of this assessment of climate change projections … is the large number of simulations available from a broader range of models. Model experiments show that… Best-estimate projections from models indicate… Based on a range of models, it is likely that… Analysis of climate models together with constraints from observations … provides increased confidence in the understanding of the climate system response to radiative forcing.

Radiative Forcing

IPCC Summary: The Language What does “very likely” mean? A. > 95% probability of occurrence B. > 90% probability of occurrence C. > 75% probability of occurrence D. > 66% probability of occurrence E. > 50% probability of occurrence

Read the Footnotes… Virtually certain > 99% probability Extremely likely > 95% Very likely > 90% Likely > 66% More likely than not > 50% Unlikely < 33% Very unlikely < 10% Extremely unlikely < 5%

Read the Footnotes… Virtually certain > 99% probability Extremely likely > 95% Very likely > 90% Likely > 66% More likely than not > 50% Unlikely < 33% Very unlikely < 10% Extremely unlikely < 5% To learn how this is done, take a statistics class that includes “Hypothesis Testing”

How Bad is “Likely”? “Likely” > 66% chance of happening Will you move?

How Bad is “Likely”? “Likely” > 66% chance of happening Will you move?How about now?

Climate Change Models Model’s manipulation rules System Repres’n behavior System behavior System’s workings Translate between system and model Climate: Atmosphere Land Sea Ice Ocean

Climate Change Models The planet is divided into a grid e.g. by longitude and latitude

Climate Change Models The grid is thickened to represent different layers of the atmosphere

Climate Change Models On each piece of the grid, changes are calculated for a small time step

Climate Change Models The pieces are put back together and updated by their effect on each other

Climate Change Models The process is repeated to cover centuries

Model Scenarios: Pathways into Unknown A1. Convergent world. Rapid economic growth. A1FI: fossil intensive, A1T: non-fossil energy sources A1B: balance across all sources A2. Heterogeneous world. Self-reliance and preservation of local identities. Technological change is slow. B1. Convergent world, with clean and resource efficient technologies. Global solutions to sustainability. B2. Heterogeneous world. Emphasis on local solutions to sustainability. Technology is diverse and slow.

Model Scenarios: Pathways into Unknown A1B: Convergent Balanced fuels A2. Heterogeneous Slow Tech. B1. Convergent Clean Tech. Global Sust. Surface Warming Predictions

Model Scenarios: Pathways into Unknown B1. Convergent world, clean technology, global sust. solutions

How can you help? Skills needed: Math Statistics Computing Chemistry Physics Biology Water Agriculture Economics Visualization Communication Arts Education Policy, Law, Sociology, Engineering, Architecture, Creativity…

How can you help? Skills needed: Math Statistics Computing Chemistry Physics Biology Water Agriculture Economics Visualization Communication Education Policy Law, Sociology, Engineering, Architecture, Creativity… Do you see yourself here? Whatever your talent, Whatever your passion, Use them to Help the Planet

How can you help? In the meantime: Reduce our Carbon Footprint Low Carbon Diet: A 30 Day Program to Lose 5000 Pounds - David Gershon - $13.00 at Amazon