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Idealized GCM studies, AGU Fall Meeting 2007
Idealized GCM Studies of Snowball Earth and of Titan
Raymond T. Pierrehumbert
The University of Chicago
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Idealized GCM studies, AGU Fall Meeting 2007
Idealized GCM vs. Intermediate Complexity Models
• ICM: Parameterized dynamics (e.g. synoptic eddy heat flux)
• IGCM
– Full representation of dynamics
– Perhaps reduced resolution
– Simplified physics
– ...and/or idealized forcing, bdd. conditions, etc.
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Idealized GCM studies, AGU Fall Meeting 2007
Limitations of Intermediate Complexity Models
• Winds, momentum fluxes (anything dynamical)
• Hadley cell, water vapor feedback (c.f. CLIMBER)
• Synoptic heat and moisture fluxes (c.f. static stability effects)
• Precipitation and hydrological cycle
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Idealized GCM studies, AGU Fall Meeting 2007
”Intermediate Complexity” a misnomer
• Often more complex than GCM, because of ad hoc parameterizations
• Too complex to allow good understanding of behavior
• But, even when behavior is understood, too far from basic physics toallow conclusions about general principles to be drawn
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Idealized GCM studies, AGU Fall Meeting 2007
Two paths to IGCM
• Strip down a full GCM, simplify physics, experimental design
• Purpose-built idealized GCM
The former is mostly a matter of philosophy about how to use a GCM. Thelatter engages question of flexible modelling software design.
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Idealized GCM studies, AGU Fall Meeting 2007
Two Examples
• Snowball Earth Climate
• The General Circulation of Titan
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Idealized GCM studies, AGU Fall Meeting 2007
Neoproterozoic Snowball Earth simulations
• Initiation (Poulsen et al. GRL 2001 and follow-ons)
• Deglaciation threshold (Pierrehumbert Nature 2004, JGR 2005)
• Surface wind during partial deglaciation
• Postglacial hothouse and recovery
Conducted with FOAM GCM
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Idealized GCM studies, AGU Fall Meeting 2007
Surface wind during Snowball Deglaciation
• Motivation: Giant wave ripples in sediment indicate strong prevailingsurface wind
• Conjectured to be due to temperature gradient between ice marginand hot ocean
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Idealized GCM studies, AGU Fall Meeting 2007
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Idealized GCM studies, AGU Fall Meeting 2007
Surface wind during Snowball Deglaciation
Cold Ice
Hot Ocean
Surface Wind??
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Idealized GCM studies, AGU Fall Meeting 2007
But the basic GFD works like this
EqPole
Cold Hot
Surface dragbalances u’v’
Baroclinically Unstable JetimpliesEddiesimplies
Angular Momentum Transport
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Idealized GCM studies, AGU Fall Meeting 2007
Simulations at .2 bar CO2
90
-90-180 0 180
Longitude
Lat
itud
e
Individual Jan. Mon. Mean Surf. U
-180 0 180Longitude
Individual Jul. Mon. Mean Surf. U m/s
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Idealized GCM studies, AGU Fall Meeting 2007
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Idealized GCM studies, AGU Fall Meeting 2007
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Idealized GCM studies, AGU Fall Meeting 2007
Postglacial Hothouse
• High CO2 needed to deglaciate
• After deglaciation, left with low albedo, high CO2 Hothouse
• Precip determines weathering rate and recovery time
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Idealized GCM studies, AGU Fall Meeting 2007
Precip vs. CO2
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0
50
100
150
10 100 1000
B.L Sat. Specific Hum.BL Specific Hum
Precip
Spec
ific
Hum
idity
Precip (mm
/mo)
CO2 (xPAL)
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Idealized GCM studies, AGU Fall Meeting 2007
The Surface Budget
0
50
100
150
200
10 100 1000
S_{abs}L
F_{sens}IR
Flux
(W
/m2 )
CO2 (xPAL)
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Idealized GCM studies, AGU Fall Meeting 2007
Winds at 100x CO2
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Idealized GCM studies, AGU Fall Meeting 2007
Winds at 200x CO2
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Idealized GCM studies, AGU Fall Meeting 2007
Winds at 400x CO2 – Superrotation!
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Idealized GCM studies, AGU Fall Meeting 2007
Summary: Precip and surface conditions on Hot Worlds
• Clausius-Clapeyron means that small ∆T yields big L
• When L approaches surface absorbed solar, temperature inversionsform which choke off evaporation (cf Pierrehumbert Nature 2002)
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Idealized GCM studies, AGU Fall Meeting 2007
Titan, at 95K is a ”Hot World” !
• Surface solar radiation under 2W/m2
• Methane so volatile that in saturation, 30 % of surface layer atmo-sphere is Methane
• That’s like Earth water vapor at 345K
• Leads to > 400W/m2 of Methane latent heat flux if surface is 1K
warmer than atmosphere
• Strong surface inversions are a dominant feature of Titan climate
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Idealized GCM studies, AGU Fall Meeting 2007
Moist Methane Climate Dynamcics of Titan
• Axisymmetric GCM
• Grey-gas radiative transfer
• Simplified Betts-Miller methane moist convection
• Simplified Monin-Obukhov stable boundary layer scheme
• Thesis work of Jonathan Mitchell (also collaborations with DarganFrierson and Rodrigo Caballero)
• See Mitchell et al. PNAS 2006.
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Idealized GCM studies, AGU Fall Meeting 2007
About the software issues
• Based on interpreted Python script
• Numerically intensive routines written in compiled Fortran or c , andbuilt into new Python commands using SWIGor PyFort .
• Model construction using Caballero’s ClimT object-oriented toolkit
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Idealized GCM studies, AGU Fall Meeting 2007
Convection patterns: dry case
121
(a) Dry seasonality (b) Dry convection
(c) Moist seasonality (d) Moist convection
(e) Intermediate seasonality (f) Intermediate convection
Figure 4.7: Left column: Contour plots of precipitation (filled contours) for our threesimulations, with the pattern of solar forcing at the surface overlaid (black lines) forreference. Right column: Contour plots of the logarithm of the averages of convectiveperturbations for the 10 terrestrial years bracketing southern summer solstice; filledcontours are the convective heating rate in K/day on the same color scale (10−6: coolcolors to 10−1.5: warm colors) and dashed contours are the convective drying ratein g/kg/day. “Stepping” patterns at the edges of contours are representative of theresolution of our simulations.
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Idealized GCM studies, AGU Fall Meeting 2007
Convection patterns: moist case
121
(a) Dry seasonality (b) Dry convection
(c) Moist seasonality (d) Moist convection
(e) Intermediate seasonality (f) Intermediate convection
Figure 4.7: Left column: Contour plots of precipitation (filled contours) for our threesimulations, with the pattern of solar forcing at the surface overlaid (black lines) forreference. Right column: Contour plots of the logarithm of the averages of convectiveperturbations for the 10 terrestrial years bracketing southern summer solstice; filledcontours are the convective heating rate in K/day on the same color scale (10−6: coolcolors to 10−1.5: warm colors) and dashed contours are the convective drying ratein g/kg/day. “Stepping” patterns at the edges of contours are representative of theresolution of our simulations.
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