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DARGAN M. W. FRIERSON UNIVERSITY OF WASHINGTON, DEPARTMENT OF ATMOSPHERIC SCIENCES COLLABORATORS: MARSHALL STONER, DAEHYUN KIM, JIALIN LIN, IN-SIK KANG,

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Presentation on theme: "DARGAN M. W. FRIERSON UNIVERSITY OF WASHINGTON, DEPARTMENT OF ATMOSPHERIC SCIENCES COLLABORATORS: MARSHALL STONER, DAEHYUN KIM, JIALIN LIN, IN-SIK KANG,"— Presentation transcript:

1 DARGAN M. W. FRIERSON UNIVERSITY OF WASHINGTON, DEPARTMENT OF ATMOSPHERIC SCIENCES COLLABORATORS: MARSHALL STONER, DAEHYUN KIM, JIALIN LIN, IN-SIK KANG, MYONG-IN LEE, ADAM SOBEL, ERIC MALONEY, GILLES BELLON Convectively Coupled Kelvin Waves and the MJO in a Hierarchy of GCMs

2 Outline What sets speed/structure of convectively coupled equatorial waves?  In a simplified GCM  Modeling work with SNU group What is required to generate a MJO-like structure?  AM2 model work w/ Sobel, Maloney & Bellon  Master’s thesis of Marshall Stoner

3 Convectively Coupled Equatorial Waves What sets speed?  Moist 1 st baroclinic mode? (gross moist stability: Neelin, Emanuel, etc)  Dry 2 nd baroclinic mode? (Mapes, Majda, etc) Observations show clear 2 nd baroclinic structure (Kiladis et al 2009)

4 CCKWs in a Simplified GCM Convectively coupled Kelvin waves (CCKWs)dominate tropical variability in a simplified GCM Unfiltered Hovmoller diagram of precipitation at the equator In this model, gross moist stability controls the speed of these waves Model of Frierson, Held & Zurita-Gotor (2006) Plot from Frierson (2007)

5 Convectively coupled Kelvin waves GMS reduction leads to slower convectively coupled waves: GMS = 6.9 KGMS = 3.9 KGMS = 3.0 K See Frierson (2007) for more detail Ratio of grid-scale to convective (simplified Betts-Miller) precipitation sets the GMS

6 Simplified Moist GCM CCKWs These CCKWs 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

7 Equatorial Waves in a Full GCM Experiments with SNU atmospheric GCM  Run over observed SSTs, realistic geography  Simplified Arakawa-Schubert (SAS) and Kuo convection schemes  Varying strength of convective trigger:  Tokioka entrainment limiter for SAS Higher Tokioka parameter => least entraining plumes are eliminated  Moisture threshold for Kuo From always triggering convection to 95% RH required See Lin, Lee, Kim, Kang and Fri. (2008, J Clim) & Fri. et al (submitted) for more

8 Moist Static Energy Vertical profile of MSE in the North West Pacific ITCZ for SAS simulations:  Higher entrainment => harder to warm upper troposphere  Stronger trigger => more unstable  GMS also reduced Tokioka values:

9 Equatorial Waves in a Full GCM Phase speeds in SAS simulations: In Kuo simulations: See Lin, Lee, Kim, Kang and Fri. (2008, J Clim) & Fri. et al (submitted) for more Wavespeed decreases with stronger moisture trigger Simulated equivalent depths scale with gross moist stability

10 CCKW Vertical Structures In full GCM, many cases show 2 nd baroclinic mode structures (unlike in simplified GCM) Shallow -> deep -> stratiform See Lin et al (2008) and Frierson et al (submitted) for more detail Warm over cold temperature anomalies Gradual moistening of boundary layer/midtroposphere

11 CCKW Vertical Structures Depends on convection scheme though! Least inhibited SAS case => No tilt in omega (but OK temperature) Most inhibited Kuo case => No tilt in omega, q (but OK temperature) Kuo simulations never show tilted omega or humidity. Only most inhibited case shows realistic temperature perturbations

12 Phase Speed Determination? Estimated equivalent depths versus GMS:  1 st baroclinic mode seems to explain phase speed  Presence/absence of 2 nd baroclinic mode doesn’t appear to have effect Circled cases have clear 2 nd baroclinic structure

13 Phase Speed Determination? 2 nd baroclinic mode and cloud-radiative forcing effects on GMS Stratiform phase => higher GMS Shallow phase => lower GMS CRF changes have small effect everywhere Mode structure effect on GMS averages to zero, and are small near center of the wave

14 Open Questions Reasons for second baroclinic mode structure  And why seen in some fields more easily than others? Applicability to other models?  Need for thorough comparisons of composites Relation to changes in mean precipitation?

15 MJO in 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 (Nature Geoscience 2008; J. Adv. Modeling Earth Systems in press) Obs (NCEP)Modified GFDL model Unmodified GFDL model

16 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 (Nature Geoscience 2008; J. Adv. Modeling Earth Systems in press)

17 Evap-Wind Feedback in Modeled MJO MJO greatly weakened when evaporation-wind feedback (EWF) is turned off! With EWFWithout EWF See SMBF (Nature Geoscience 2008; J. Adv. Modeling Earth Systems 2009)

18 MJO in Aquaplanet AM2 What is required to have a MJO-like structure in a model?  Land-sea contrast?  Zonal asymmetry/Walker cell?  Evaporation-wind feedback? Experiments with Neale & Hoskins aquaplanet AMIP boundary conditions  “QOBS” & “Flat”  GFDL AM2 model with Tokioka modification M.S. thesis work of Marshall Stoner (2010)

19 Zonally Symmetric Results Log(variance) spectra: QOBS (left) and “Flat” (right) Enhanced power in eastward intraseasonal band Connected to moist Kelvin wave? More clear dominance of east over west Less connected to Kelvin wave? M.S. thesis work of Marshall Stoner (2010)

20 Intraseasonal Composites Composites of structure:  When WISHE is suppressed, QOBS ISV (left) remains, while Flat ISV (right) disappears Connected to midlatitude wave trains, smaller scale More similar to observed MJO? QOBSFlat M.S. thesis work of Marshall Stoner (2010)

21 Mean States Mean states (solid = QOBS, dashed = flat): Flat has weaker easterlies, and a double ITCZ Standard WISHE likely drives the waves M.S. thesis work of Marshall Stoner (2010)

22 How about Flat + a Walker cell? Surface winds Now mean westerlies over much of the tropics Will WISHE still be important? (standard theory assumes mean easterlies) M.S. thesis work of Marshall Stoner (2010)

23 Walker Cell Case MJO-like variability still exists (although weaker)  Again it disappears if WISHE is suppressed Surface winds Log(variance) Variance avoids surface westerly region? M.S. thesis work of Marshall Stoner (2010)

24 WISHEful Thinking Evaporation composites for Flat (zonally symmetric) and Flat + Walker Flat Flat + Walker cell Both essentially have evaporation leading the wave

25 Open Questions What sets scale, speed of the MJO-like phenomenon?  Related to Kelvin wave at all, or a moisture mode?  Advection of dry air by WWBs & Rossby cyclones appears to be important in setting speed as well as WISHE Comparisons with other models (including CRMs)  Similar mechanisms acting? (mechanism denial experiments in a range of models)  Compare composites as well as spectra Understanding of how/when different mechanisms can power waves can help our interpretation of observations

26 Conclusions Convectively coupled waves in simple and full GCM are affected by “gross moist stability”  Full GCM shows second baroclinic mode characteristics MJO-like structures can exist in aquaplanet model  Zonally symmetric or with Walker cell  More realistic ISV is powered by WISHE in mostly traditional manner


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