DARGAN M. W. FRIERSONUNIVERSITY OF WASHINGTON, DEPARTMENT OF

ATMOSPHERIC SCIENCES

COLLABORATORS: SARAH KANG, ISAAC HELD, MING ZHAO, JIALIN LIN, IN-SIK KANG, DAEHYUN KIM, MYONG-IN LEE, ADAM SOBEL, ERIC MALONEY,

GILLES BELLON

Experiments with a Hierarchy of GCMs: ITCZ Response to High Latitude Forcing, and Tropical

Variability

Modeling Philosophy

Models aren’t reality… They can only tell us so much about the real

atmosphere

A major advantage of using models is ability to play around with parameters Turning feedbacks on/off Modifying/simplifying boundary conditions Changing physical parameterizations

Comprehensive and Simplified GCMs

With comprehensive models, not always straight-forward to perform such experiments Can affect many aspects of model (e.g., convection scheme

affects clouds, etc) Can cause fidelity of simulated climate to decrease Requires careful experimental design

Simplified GCMs are useful for aiding the above Here we’ll discuss:

Moist GCM with highly simplified physics (Frierson 2005) No cloud- or water vapor-radiative feedbacks Simplified Betts-Miller convection scheme

Aquaplanet full GCM simulations Realistic geography full GCM simulations

Outline

ITCZ response to extratropical forcing With Sarah Kang & Isaac Held

Convectively coupled Kelvin waves With Jialin Lin, In-Sik Kang, Daehyun Kim & Myong-In

Lee

MJO With Adam Sobel, Eric Maloney & Gilles Bellon

ITCZ Location

Pioneering work by Chiang, Biasutti and Battisti (2004) and Chiang and Bitz (2005): Showed strong sensitivity of ITCZ to high latitude sea

ice and land ice in LGM simulation using CCSM

Moistening

Drying

Southward displacement of ITCZ occurs in LGM climate

Paleoclimate data is consistent with such a shift

From Chiang and Bitz (2005)

Extratropical Influences on ITCZ

Sarah Kang’s thesis work (2009): Effect of high latitude forcing on ITCZ

location/structure/intensity Simplified moist GCM and aquaplanet full GCM

(AM2) runs w/ idealized forcing:

NH cooling

SH warming

From Kang, Held, Fri., & Zhao (2008, J Clim) and Kang, Fri. & Held (in press, JAS)

Forcing

Think glaciers + sea ice in NH, plus warming in SH (to keep global mean temperature the same)

ITCZ Changes

In both models, ITCZ precipitation shifts towards warmed hemisphere

Tropical precip in full GCM

• Response is sensitive to parameters which affect cloud feedbacks

• Response is significantly larger in full GCM as compared with simplifiedGCM

From Kang, Held, Fri., & Zhao (2008, J Clim) and Kang, Fri. & Held (in press, JAS)

Mechanism for ITCZ Response

We argue energy flux is of key importance

8

Anomalous energy flux into cooled region

Change in MSE flux in simplified GCM

Less flux into warmed region

Mechanism for ITCZ Response

ITCZ latitude ~ “Energy flux equator”

8 Define “energy flux equator” as zero crossing of energy flux

Shifted into SH in perturbed case

In tropics, mean circulation does most of the flux => v=0 there =>ITCZ is nearby

Change in MSE flux in simplified GCM

ITCZ location (-) is approximatelysame as energy flux equator (--)for full GCM

Mechanism for Energy Flux Change

Eddies modify fluxes in midlatitudes Quasi-diffusively: they can be well-approximated with

a moist energy balance model

Anomalous Hadley circulation modifies fluxes in tropics

See Kang, Held, Fri., & Zhao (2008, J Clim) & Kang, Fri. & Held (in press, JAS) for more

Role of Cloud-Radiative Forcing

Differences in cloud-radiative forcing (CRF) affect ITCZ as follows: CRF = extra forcing at certain latitude bands Forcing is again propagated away byeddies quasi-diffusively Changes in energy flux equator then result in changes in ITCZ location Result in massive differences in ITCZ shift for same

forcing!

Similar mechanism seen in energy fluxes in IPCC model simulations of global warming Current work of my grad student Ting Hwang

Role of “Gross Moist Stability”

In idealized model, we can take the energy flux argument one step further

Can predict mass flux response (and hence precip response), with the “gross moist stability” of the tropics:

Changes in parameters of simplified Betts-Miller scheme can change (as shown in Frierson 2007a, JAS) Larger GMS when convection can easily reach high levels Smaller GMS when there’s an abrupt trigger for convection

Role of “Gross Moist Stability”

For identical forcing and identical energy flux response, the precip response can be significantly different

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See Kang et al 2008; also Frierson 2007a

Tropical Variability in Simplified GCM

Convectively coupled Kelvin waves dominate tropical variability in the idealized GCM

Unfiltered Hovmoller diagram of precipitation at the equator

Does gross moist stability control the speed of these waves (as in simple theories)?

From Frierson (2007b, JAS)

Convectively coupled Kelvin waves

GMS reduction also leads to slower convectively coupled waves:

GMS = 7 K GMS = 4.5 K GMS = 2.5 K

See Frierson (2007b) for more detail

Wavespeed can be tuned to essentially any value in this model

Idealized Moist GCM Kelvin Waves

Kelvin waves are powered by evaporation-wind feedback Likely not true in reality in Indian Ocean…

Vertical structure is purely first-baroclinic mode Unrealistic…

Longitude

Composited pressure velocity

See Frierson (2007b) for more detail

Equatorial Waves in a Full GCM

Experiments with SNU atmospheric GCM Run over observed SSTs, realistic geography Simplified Arakawa-Schubert convection scheme Varying strength of convective trigger

See Lin, Lee, Kim, Kang and Frierson (2008, J Clim) & Fri. et al (in prep) for more

• Wavespeed decreases with stronger moisture trigger• Due to smaller GMS, as in simplified GCM

Moist Static Energy

Vertical profile of MSE in the North West Pacific ITCZ:

MSE clearly reduced at higher levels (more unstable)

GMS also reduced

Vertical structures

In full GCM, the waves show realistic vertical phase tilts (unlike in simplified GCM)

Shallow -> deep -> stratiform

See Lin et al (2008) and Frierson et al (in prep) for more detail

Warm over cold temperature anomalies

Gradual moistening of boundary layer/midtroposphere

MJO in Realistic GCMs

Work with Sobel, Maloney, & Bellon using GFDL AM2 model w/ realistic geography

First crank up Tokioka “entrainment limiter” to get a better MJO simulation:

See SMBF (2008, Nature Geoscience; 2009, J. Adv. Modeling Earth Systems)

Obs (NCEP) Modified GFDL model Unmodified GFDL model

MJO in GFDL AM2 Model

Ratio of variance in eastward/westward intraseasonal bands: 2.6 for modified GFDL model Less than the observed value of 3.5, but larger than

nearly all models in Zhang et al (2006) comparison

Higher entrainment in convection scheme => more sensitivity to midtropospheric moisture

Next test role of evaporation-wind feedbacks in driving the modeled MJO Set windspeed dependence in drag law formulation to

globally averaged constant value

See SMBF (2008, Nature Geoscience; 2009, J. Adv. Modeling Earth Systems)

Evap-Wind Feedback in Modeled MJO

MJO greatly weakened when evaporation-wind feedback (EWF) is turned off!

With EWF Without EWF

See SMBF (2008, Nature Geoscience; 2009, J. Adv. Modeling Earth Systems)

Conclusions

ITCZ is affected by high latitude forcing by following processes: Energy fluxes: “energy flux equator” Cloud-radiative forcing Gross moist stability

Convectively coupled waves in simple and full GCM are affected by “gross moist stability” Full GCM shows second baroclinic mode

characteristics

Simulated MJO in full GCM extremely sensitive to evaporation-wind feedback