Dynamic Systems Sea-Level Rise Model: …mesl.ce.gatech.edu/RESEARCH/Forcing Function...

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Dynamic Systems Sea-Level Rise Model: Interpretation of the Forcing Function Jiabao Guan, Biao Chang and Mustafa M. Aral Multimedia Environmental Simulations Laboratory School of Civil and Environmental Engineering Georgia Institute of Technology

Transcript of Dynamic Systems Sea-Level Rise Model: …mesl.ce.gatech.edu/RESEARCH/Forcing Function...

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Dynamic Systems Sea-Level Rise Model: Interpretation of the Forcing Function

Jiabao Guan, Biao Chang and Mustafa M. Aral Multimedia Environmental Simulations Laboratory School of Civil and Environmental Engineering Georgia Institute of Technology

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Climate Change / Sea-level Rise DATA on: Temperature Sea-Level Rise Radiative forces (CO2 Emissions)

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Global Temperature Change:

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Global Sea-Level Rise:

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Data on CO2 Emissions:

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Sea Level Rise (m at 2090-2099 relative to 1980-1999)

Case Model-based range excluding future rapid dynamical changes in ice flow

B1 scenario 0.18 – 0.38 A1T scenario 0.20 – 0.45 B2 scenario 0.20 – 0.43 A1B scenario 0.21 – 0.48 A2 scenario 0.23 – 0.51 A1FI scenario 0.26 – 0.59

The Summary for Policy Makers (SPM) released recently provide the following table of sea level rise projections (IPCC4th Framework Report, 2007):

The IPCC Study:

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IPCC estimates:

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Semi-Empirical Models: Rahmstorf’s Study (Science, Vol. 315 pp.19, 2007) and others:

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{ }0.5 1.4m−

Semi-Empirical Models: Rahmstorf’s Study (Science, Vol. 315 pp.19, 2007) and others.

Sea-level Rise Interval Predicted above 1990 level:

IPCC Interval Predicted above 1990 level:

{ }0.09 0.88m−

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Major limitations of the previous empirical models

No feedback of SLR on temperature change

Zero-dimensional, thus does not capture spatial variations in SLR

Impact of external forcing is not considered

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A Dynamic Systems Model

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Earlier studies showed that the relationship between T & H is linear.

Our Hypothesis: (Dynamic Systems Model):

Temperature:

Sea-Level:

( )1 1, , ,T f T H U c=

( )2 2, , ,H f T H U c=

Expected Relationship:

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11 12 1

21 22 2

( ) ( ) ( )

( ) ( ) ( )

dT t a T t a H t cdt

dH t a T t a H t cdt

= + +

= + +

Initial Model Proposed:

(Simplified)

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( ) ( ) ( ),d t dT t dH tdt dt dt

τ =

X

( ) ( )d t tdt

= +X AX C

11 12

21 22

a aa a

=

A 1

2

cc

=

C

Initial Model Proposed:

(Simplified)

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Initial Model Proposed:

(Simplified)

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Dynamic Systems Model:

( )tU

( )tXddtX

( )tU

( )tX ddtX

System

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( )

( )

11 12 13 1

21 22 23 2

( ) ( ) ( )

( ) ( ) ( )

i ii

i ii

dT t a T t a H t a U t cdt

dH t a T t a H t a U t cdt

= + + +

= + + +

Proposed Model:

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more flexible; may answer more questions; may provide control analysis perspective; and, hopefully will be more useful. potential drawback may require more data.

The Proposed model is:

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( ) ( ) ( ) ( )d t t t tdt

= + + +X AX BU C w

11 12

21 22

a aa a

=

A 11 12 1

21 22 2

m

m

b b bb b b

=

B

1

2

cc

=

C

Proposed Model:

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( 1) ( ) ( ) ( )k k k k+ = + + + 1XΦX ΓU Ω w

; ;t t t= + ∆ = ∆ = ∆Φ I A Γ B Ω C

Discrete form of the Proposed Model:

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( ) ( ){ }* minimizei

i i i iF τ= − −φ

YΛφ Y Λφ

LSM Model to determine aij , bij & ci :

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Confidence Interval:

( )( )( )( )

12/2, 4

12/2, 4

ˆ ˆ ˆ ˆˆ( ) ( ) 1 ( ) ( )

ˆ ˆ ˆ ˆˆ( ) ( ) 1 ( ) ( )

CI n T

CI n H

T k T k t Z k Z k

H k H k t Z k Z k

τ τα

τ τα

σ

σ

= ± +

= ±

+

Λ Λ

Λ Λ

(Wadsworth, 1998)

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Application:

2-year moving average outcome is used for

both state variables.

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Temperature Data:

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Sea-Level Data:

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Resulting Matrix Coefficients:

System System matrix Control matrix

Constant vector

Discrete

Continuous

0.75042 -0.000530.41015 0.99568

0.002450

0.857440.25863−

-0.24958 -0.000530.41015 -0.00432

0.002450

0.857440.25863−

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-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

Tem

pera

ture

(o C)

ObservationReconstructionConfidence interval

1880 1900 1920 1940 1960 1980 2000Year

-20

-15

-10

-5

0

5

10

Sea

-leve

l ris

e (c

m)

ObservationReconstructionConfidence interval

(a)

(b)

Global CO2 Impact: Calibration

R2 = 0.80

R2 = 0.97

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-1

-0.5

0

0.5

1

1.5

2

2.5Te

mpe

ratu

re (o C

)

ObservationProjectionConfidence interval

1880 1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100Year

-20

-10

0

10

20

30

40

50

60

70

Sea

-leve

l ris

e (c

m)

ObservationProjectionConfidence intervalRahmstorf's results

(a)

(b)

Global CO2 Impact: Prediction for “2 oC” Scenario (Scenario is designed to limit global warming in 2100 2oC above the temperature in 2000 )

(Hansen et al., 2000)

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1880 1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100Year

0

200

400

600

800

1000

1200

CO

2 e

mis

sio

n (

pp

m)

SCENARIOSA1FIA1BA1TA2B1B2

IPCC Global CO2 Emission Scenarios:

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-1

0

1

2

3

4

5

6

Tem

pera

ture

(o C

)

ObservationA1FIA1BA1TA2B1B2

1880 1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100Year

-20

0

20

40

60

80

100

120

Sea

-leve

l ris

e (c

m)

ObservationA1FIA1BA1TA2B1B2

(a)

(b)

Global CO2 Impact: Comparison of results

Solid lines are Dyn. Sys. Model results. Dashed lines are IPCC results.

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For example: If we want to restrict the global temperature and sea-level rise to zero-growth, the global CO2 emission should be controlled with the relationship given by

Decision Making on Global CO2 Emissions:

2( ) 101.87 ( ) 0.22 ( ) 349.98COu t T t H t= + +

2( )COu t represents the amount of yearly CO2 emission (ppm).

where

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