Transcript 1 - Intro

Dynamics of
Climate Variability
& Climate Change
EESC W4400x
Fall 2006
Instructors: Lisa Goddard, Mark Cane
Teaching Assistant: Philip Orton
Objectives: Knowledge
• Understand fundamental physical
processes underlying climate variability
and climate change
• Understand how models and predictions
work
• Understand important influencing factors
(in models & predictions) and important
assumptions/uncertainties
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Objectives: Skills
• Climate science literacy:
Read with understanding (i.e. be able to
summarize and interpret) articles on the topics
covered in this course in journals such as Science
and Nature.
• Forecast interpretation:
Identify influencing factors and uncertainties
for climate predictions on time scales, from
seasonal-to-interannual forecasts to climate
change projections.
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OUTLINE
• “Climate”
• Models
• Systems and Feedbacks
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Climate System
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What is Climate?
• Climate is the mean state of the environment, defined over a finite time
interval, at a given location and time.
- This state can be characterized by the mean values of a range of
weather variables, such as wind, temperature, precipitation, humidity,
cloudiness, pressure, visibility, and air quality.
• The definition of climate also includes the typical range of variability in
values of environmental variables (for example – the standard deviation
of temperature).
• A complete description of the climate system and the understanding of
its characteristics and change require the study of the physical
properties of the high atmosphere, deep ocean, and the land surface,
and sometimes the measurement of their chemical properties.
• The study of climate is a quantitative science, involving the
understanding of the transfer of energy from the sun to the earth, from
earth to space, and between atmosphere, ocean, and land, all under
fundamental physical laws such as conservation of mass, heat, and
momentum.
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Mean Temperature Field
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Regional
Temperature
Variability
Remove mean
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Example:
Time Scales of
Variability
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Modeling the Climate
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Models
• Conceptual
Illustrate principal relationships or balances
• Empirical/statistical
Describe relationship between observed parameters
(e.g. sea surface temperature and rainfall)
• Numerical/dynamical
Based on set of mathematical equations describing
physical processes, that allow the system to evolve in
time
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How do we model climate?
[physically]
• Physical/dynamical equations
- 3-D equations of motion (conservation of momentum)
-
Continuity equation (conservation of mass)
Thermodynamic equation (conservation of energy)
Equation of state for air
Balance equation for water vapor
• Parameterizations
Small-scale processes that are treated statistically and their
effects related to average conditions over much longer periods of
time and larger space scales
e.g. clouds, radiative transfer, turbulence
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Hierarchy of Climate Models
(Physically-based)
• 3-D coupled ocean-atmosphere GCMs (CGCMs)
• 3-D atmosphere-only GCMs (AGCMs)
• 2-D(λ,φ) – “barotropic” or 2-D(φ,z) – “Energy
Balance” models
• 1-D(z) – “Radiative-Convective Models” (RCMs)
or “Single Column Models” (SCMs)
• 0-D – Global-Mean Energy Balance Models
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Weather & Climate Prediction
Initial & Projected
State of Atmosphere
Climate Change
Decadal
Uncertainty
Current
Observed
State
Initial &
Projected
State of Ocean
Initial &
Projected
Atmospheric
Composition
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Time Scale, Spatial Scale
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Systems & Feedbacks
• Example 1:
Albedo (daisies) & temperature
 “Daisyworld”
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Example 1 (cont.)
Temperature as Function of
Daisy Coverage
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Example 1 (cont.)
Daisy Coverage as Function of
Temperature
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Example 1 (cont.)
Equilibrium & Stability
Dmax
x
System of Equations:
(1)
(2)
D = Dmax – (T-To)2
(1)
T = Tmax – αD
(2)
 0 : T  To
D
 2(T  To )
T
 0 : T  To
To
x
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T
   0
D
x
Tmax
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Systems & Feedbacks
• Example 2:
Albedo (snow/ice) & temperature
Snow/Ice
coverage
Surface
temperature
As temperature decreases, snow/ice coverage increases
(less snow/ice melted, and more precipitation delivered in frozen form)
As snow/ice cover increases, temperature decreases
(albedo increases, so less solar energy is absorbed by surface)
 Positive feedback (Snowball Earth, Chp. 12 – Kump et al.)
Potential negative feedback: As temperature drops, atmosphere holds
less H2O, and precipitation decreases. Also, ice may begin to sublimate.
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