identifying the volcano signal with pcm

THE EFFECT OF CLIMATE

SENSITIVITY ON THE RESPONSE TO VOLCANIC FORCING

Tom Wigley, National Center for Atmospheric Research,

Boulder, CO

(together with Caspar Ammann, NCAR, Ben Santer, PCMDI, LLNL, and Sarah Raper, CRU, UEA)

wigley@ucar.edu

Presented at Eighth Annual CCSM Workshop,

24 June 2003.

SUMMARY AND GOALS

• To identify the volcanic response signal in the signal+noise of a set of AOGCM runs (PCM)

• To see how well this signal can be reproduced with a simple upwelling-diffusion energy-balance climate model

• To use the UD EBM to determine the characteristics of volcanic response and how these vary with the climate sensitivity

PCM experiments with volcanic forcing• Volcanoes only• Solar + Volcanoes• Solar, Volcanoes and Ozone• ‘ALL’ = S, V, O + Greenhouse gases + direct sulfate Aerosols

IDENTIFYING THE VOLCANO SIGNAL WITH PCM

Variability summary (monthly data over 1890–1999)

Number Experiment Mean S.D.

(degC)

S.D. of Ensem. Ave.

1 Control 0.171 0.085

2 V 0.191 0.121

3 SV 0.195 0.131

4 OSV 0.199 0.134

5 ALL 0.271 0.232

6 Observed 0.248

Variability of ensem-ave volcano cases(monthly data over 1890 –1999)

Number Combination S.D. (degC)

1 V 0.121

2 SV-V 0.139

3 OSV-OS 0.144

4 ALL-GAOS 0.154

5 (1+2+3+4)/4.0 0.101

Control 0.0851

V – Vsignal 0.0905

5 – Vsignal 0.0604

Ensemble averaging:

n=1 to 4

VOLCANIC SIGNAL: SINGLE REALIZATION (V-677)

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0 120 240 360 480 600 720 840 960 1080 1200 1320MONTH (JAN. 1890=1)

TE

MP

ER

AT

UR

E C

HA

NG

E

(de

gC

)

VOLCANIC SIGNAL: 4-MEMBER ENSEMBLE MEAN

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0 120 240 360 480 600 720 840 960 1080 1200 1320MONTH (JAN. 1890=1)

TE

MP

ER

AT

UR

E C

HA

NG

E

(de

gC

)Eruption dates for Santa Maria, Agung, El Chichon and Pinatubo marked.

Note how difficult it is to estimate the maximum cooling signals with only one realization.

Ensemble averaging: n=4 to 16

VOLCANIC SIGNAL: 4-MEMBER ENSEMBLE MEAN

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-0.6

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0

0.2

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0.6

0 120 240 360 480 600 720 840 960 1080 1200 1320MONTH (JAN. 1890=1)

TE

MP

ER

AT

UR

E C

HA

NG

E

(de

gC

)

Eruption dates for Santa Maria, Agung, El Chichon and Pinatubo marked

VOLCANIC SIGNAL: 16-MEMBER ENSEMBLE MEAN

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0

0.2

0.4

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0 120 240 360 480 600 720 840 960 1080 1200 1320MONTH (JAN. 1890=1)

TE

MP

ER

AT

UR

E C

HA

NG

E

(de

gC

)

IDENTIFYING THE VOLCANO SIGNAL WITH AN UPWELLING-DIFFUSION ENERGY-BALANCE

MODEL (MAGICC)

IDENTIFYING THE SIGNAL WITH MAGICC: METHOD

• Use MAGICC model parameters from IPCC Ch. 9 based on fit to 1% compound CO2 CMIP simulation(note that this is decadal timescale forcing, while the volcanic forcing is on a monthly timescale)

• Drive MAGICC with forcing used in the PCM experiments (from Caspar Ammann)

VOLCANIC ERUPTION SIGNAL16-member ensemble-mean from PCM [signal plus noise] compared

with simulation using the simple UD EBM ‘MAGICC’ [pure signal].

COMPARISON OF AMMANN FORCING RESULTS : PCM vs MAGICC (vble THC)

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0

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0 120 240 360 480 600 720 840 960 1080 1200 1320MONTH (JAN. 1890=1)

TE

MP

ER

AT

UR

E C

HA

NG

E (

deg

C)

VARYING THC

The excellent fit between the MAGICC and PCM results, the fact that MAGICC

gives a ‘pure’ signal, and the fact that the climate sensitivity is a user-input

parameter in MAGICC means that we can use MAGICC to obtain greater insight into

the character of the volcanic forcing response signal.

Simple energy balance equation  C dT/dt + T/S = Q(t) = A sin(t).  The solution is   T(t) = [()2/(1+()2)] exp(-t/) + [S/(1+()2)][A{sin(t) – t cos(t)}] where is a characteristic time scale for the system, = SC.  Low-frequency forcing ( << 1/), solution is simply the equilibrium response  T(t) = S A sin(t)  showing no appreciable lag between forcing and response, with the response being linearly dependent on the climate sensitivity and independent of the system’s heat capacity.  High-frequency case ( >> 1/) the solution is   T(t) = [A/(C)] sin(t – /2) showing a quarter cycle lag of response behind forcing, with the response being independent of the climate sensitivity. 

EFFECT OF CLIMATE SENSITIVITY ON THE RESPONSE TO VOLCANIC FORCING

VOLCANIC RESPONSE FOR DIFFERENT SENSITIVITIES

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-0.7

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0

0.1

0 120 240 360 480 600 720 840 960 1080 1200 1320

MONTH (JAN. 1890 = 1)

TEM

PE

RA

TUR

E C

HA

NG

E (

degC

)

1.02.0

4.0

SIMULATED PINATUBO ERUPTIONSIMULATED PINATUBO ERUPTION FOR DIFFERENT SENSITIVITIES

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0

1210 1220 1230 1240 1250 1260 1270 1280 1290 1300 1310 1320 1330 1340

MONTH (JUNE 1991 = 1218)

GLO

BA

L-M

EAN

TEM

PER

ATU

RE

CH

AN

GE

(deg

C)

PEAK FORCING

PEAK COOLING

DT2x = 1.0 degC

2.0

4.0

APPROX. EXPONENTIAL DECAY

10 YEARS AFTER ERUPTION

PEAK COOLING AS A FUNCTION OF CLIMATE SENSITIVITY

T2x

(degC)

Santa Maria

Agung El Chichon

Pinatubo

1.0 0.258[1.00]

0.265[1.00]

0.259[1.00]

0.394[1.00]

2.0 0.348[1.35]

0.357[1.35]

0.349[1.35]

0.533[1.35]

4.0 0.430[1.67]

0.439[1.66]

0.429[1.66]

0.658[1.67]

Peak cooling is closely proportional to peak forcing (3%)

DECAY TIME AS A FUNCTION OF CLIMATE SENSITIVITY

T2x

(degC)

Santa Maria

Agung El Chichon

Pinatubo

1.0 26[months]

28[months]

30[months]

30[months]

2.0 30[months]

33[months]

36[months]

36[months]

4.0 34[months]

38[months]

42[months]

41[months]

Relaxation back to the initial state is slightly slower than exponential, so the apparent e-folding time increases with

time. The above are minimum e-folding times.

CONCLUSIONS• Peak cooling is relatively insensitive to T2x [Tmax(T2x) Tmax(1) + a ln(T2x)]

• Relaxation time is 26–42 months, logarithmic in T2x

• Observed peak coolings can be used to estimate T2x, but uncertainties are large due to internal variability noise in the observations

• Long timescale response cannot be used to estimate T2x because the residual signal is too small relative to internal variability noise [contrast with Lindzen and Giannitsis, 1998)]