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Dynamical responses to volcanic forcings in
climate model simulationsDynVar workshop 22.04.13
Matthew Toohey
with Kirstin Krüger, Claudia Timmreck,
Hauke Schmidt
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• What would happen if a large volcanic eruption occurred tomorrow?
→ Every seasonal to decadal climate forecast made prior to the eruption would become obsolete.
Motivation
Thompson et al. (2012)Thompson et al. (2009)
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Motivation
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“Winter Warming”
Robock and Mao (1992)
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Post-volcanic dynamical anomalies
Baldwin andDunkerton. 2001
Christiansen, 2008
13 eruptions Schmidt et al., 2013
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Stratospheric mechanism
Stenchikov et al. (2002)
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• A number of studies have reported realistic simulation of post-volcanic NH dynamical anomalies (Graf et al., 1993, 1994; Mao and Robock, 1998; Kirchner et al., 1999; Shindell et al., 2001; Rozanov et al., 2002; Stenchikov et al., 2002; Collins, 2004; Shindell et al., 2003, Shindell et al. 2004)
• But multi-model studies (e.g. CMIP, CCMVal-2) have not produced a convincing picture of model behavior.
Model results
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CCMVal-2 post-eruption T anomalies
Ch. 8 in SPARC, CCMVal Report, 2010
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CMIP59 eruptionsn=18
9 eruptions13 models72 members
9 eruptions13 models72 members
4 eruptionsn=8
Driscoll et al. 2012
Sea level Pressure
50 hPaGeopotential height
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CMIP5
Charlton-Perez et al., 2013
Low-topHigh-topERA-interim
CMIP5
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Stratospheric mechanism
Stenchikov et al. (2002)
?
?
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•Why don’t CMIP5 models show strong NH winter vortices (i.e., negative polar cap z50 anomalies) after volcanic eruptions?→Either
1. Response is not real (just chance?)2. Models are flawed3. Implementation of volcanic aerosol forcing is
flawed4. Volcanic aerosol forcing is flawed
The question
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CMIP volcanic forcings
0.4
0.3
0.2
0.1
0
Sato et al. (1990)/GISS/Stenchikov Ammann (2003)/(2007)
• Pinatubo and El Chichon based on SAGE observations
• Recently updated with OSIRIS observations Oct 2001 - present
• Best estimate sulfur mass injection, distributed via parameterized stratospheric transport model
Jan 92
Jul 91Jan 92
Jan 91
Jan 92
Jul 91Jan 92
Jan 91
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• Notes: zonal mean, monthly mean, for pre-satellite era eruptions, spatial distribution of aerosols poorly constrained
CMIP Volcanic forcings
Sato et al. (1990)/GISS/Stenchikov
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• Part 1:• Use MAECHAM5-HAM, a coupled aerosol-climate
model, to simulate the evolution of stratospheric sulfate aerosol after a Pinatubo-like eruption.
• Part 2:• Use MPI-ESM, a high-top CMIP5 model, and replace
the prescribed Pinatubo volcanic forcing from historical simulations with forcing sets built from Part 1.
Experiment
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• MPI-ESM: full Earth System model, with atmosphere, ocean, carbon cycle, vegetation components. • Atmospheric component ECHAM6. • “low resolution” (LR, T63/L47), configuration used here
(no QBO).
• Volcanic aerosols are prescribed• CMIP5 historical simulations use Stenchikov et al.
(1998) forcing data set -> monthly mean, zonal mean aerosol extinction, single scattering albedo, and asymmetry factor
MPI-ESM
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• ECHAM: GCM developed at MPI-M, Hamburg• Middle atmosphere version: 39 vertical levels up to 0.01 hPa (~80 km)• T42 horizontal resolution• Climatological sea surface temperatures, no QBO, no chemistry
• HAM: Aerosol microphysical module• Modified for simulation of stratospheric volcanic aerosols• Models aerosol growth, radiative effects, eventual removal
MAECHAM5-HAM
Inject SO2 at 24 km
Aerosol growthRadiative effects
Aerosol transport via atmospheric
circulation
Transport to troposphere,
rainout!
HAM
ECHAM5SO2→ H2SO4
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Toohey et al (2011, ACP)
MAECHAM5-HAM Pinatubo simulations
• Simulations of 17 Tg eruption, June 15, 15.3°N• Excellent agreement with ERBE TOA SW flux anomalies
observed after Pinatubo eruption. Little to no dependence on eruption longitude.
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Modeled aerosol transport
months after eruption months after eruption
Toohey et al. (2011)
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HAM July eruption simulations: DJF1
Temperature Geopotential height Zonal wind
n=12
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DJF1 z50 anomalies
n=12
July eruptions April, July and October eruptions
n=36
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AOD: July eruption ensemble variability
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Weak and Strong vortex composite AOD
n=12
July eruptions
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Vortex strength ~ AOD gradient?
Polar cap gph anomaly calculated as area mean over 70-90N.AOD gradient at 60N as AOD(60-90N) – AOD(50-60N)
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Vortex strength ~ AOD gradient?
Strong Vortex AOD gradient across vortex
Aerosol heating gradient?
If we want our prescribed aerosols to force a strong vortex, the forcing had better take the form of a strong vortex.
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MPI-ESM Pinatubo forcing experiment
Stenchikov (CMIP5)
HAM weak
HAM strong
r1,r2,r3r4,r5,r6r7,r8,r9
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Aerosol extinction at 550 nmSt
ench
ikov
HA
M w
eak
HA
M s
tron
g
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MPI-ESM: tropical 50 hPa T
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MPI-ESM: DJF1 T and u anomaliesStenchikov HAM weak HAM strong
Tem
pera
ture
(K)
u w
ind
(m/s
)
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MPI-ESM: DJF1 z50 anomalies
Low-topHigh-topERA-interim
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MPI-ESM: DJF1 z50 anomalies
Low-topHigh-topERA-interim
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MPI-ESM: DJF1&2 z50 anomalies
Low-topHigh-topERA-interim
CMIP5
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Aerosol extinction at 550 nmSt
ench
ikov
HA
M w
eak
HA
M s
tron
g
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Arfeuille et al. ACPD 2013
Extinction at 550 nm
August
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• CCMI: Surface Area Densities (SADs), stratospheric heating rates, and radiative properties, based on SAGE_4λ retrievals (Tom Peter and Beiping Luo, ETHZ)
Volcanic forcing, the next generation
• Model-based aerosol reconstructions becoming available for pre-satellite era eruptions.
Tambora: Arfeuille et al. (2013) vs. Crowley (2008)
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• For a CMIP5 historical-style simulation of Pinatubo, we can control the strength of the (ensemble mean) post-eruption NH winter vortex with the aerosol forcing set• Vortex strength ~ AOD gradient across vortex edge
→ Likely that dynamical response to volcanic eruptions can be „improved“ by using different forcing data sets.
→ Future work will show whether new volcanic forcing sets lead to better dynamical responses in climate models.
Conclusions
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Volcanic vs. Anthropogenic forcing