Transcript What is a model? - Cornell University

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?
System’s
System
workings
System
behavior
System
Translate between
system and model
Model
Represent’n
Model’s
manipulation
rules
From Andy Ruina, TAM, Cornell
Represent’n
behavior
Limits to Growth Model
System’s
System
workings
Humans on the Planet
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Population
Resources
Industrial output
Pollution, etc
Limits to Growth Model
System’s
System
workings
Humans on the Planet
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Numbers
Equations
representing
interactions
Population
Resources
Industrial output
Pollution, etc
Graphs of how the
numbers change
over time
Disease Model
System’s
System
workings
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Spread of infectious
disease through the
population
Disease Model
System’s
System
workings
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Spread of infectious
disease through the
population
Equations to represent
- transmission rates
- contact rates,
- vaccination efficiency…
Disease Model
System’s
System
workings
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
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?
System’s
System
workings
The Sunderban Islands
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Poverty and hunger
Conservation
Mangroves
Cyclones
What Can a Novelist Do?
System’s
System
workings
The Sunderban Islands
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Poverty and hunger
Conservation
Mangrove forests
Cyclones
Novel
“The Hungry Tide”
by Amitav Ghosh
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”
Limits to Growth Model
System’s
System
workings
Humans on the Planet
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Numbers
Equations
representing
interactions
Population
Resources
Industrial output
Pollution, etc
Graphs of how the
numbers change
over time
Limits to Growth Model
System’s
System
workings
Humans on the Planet
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Numbers
Equations
representing
interactions
Population
Resources
Industrial output
Pollution, etc
Graphs of how the
numbers change
over time
Huge, interdisciplinary project!
Limits to Growth Model
System’s
System
workings
Humans on the Planet
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
Numbers
Equations
representing
interactions
Population
Resources
Industrial output
Pollution, etc
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
2500+ 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
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”
Intergov. Panel on Climate Change
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
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
System’s
System
workings
System
behavior
Translate between
system and model
Model’s
Repres’n manipulation Repres’n
behavior
rules
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
Surface Warming
Predictions
A1B: Convergent
Balanced fuels
A2. Heterogeneous
Slow Tech.
B1. Convergent
Clean Tech.
Global Sust.
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
Do you see yourself here?
Computing
Chemistry
Physics
Whatever your talent,
Biology
Whatever your passion,
Water
Agriculture
Use them to Help the Planet
Economics
Visualization
Communication
Education
Policy
Law, Sociology, Engineering, Architecture, Creativity…
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