aquaplanet simulations of the mjo: wind-evaporation feedback and horizontal moisture advection
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Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal moisture advection. Eric D. Maloney, Walter Hannah Department of Atmospheric Science Colorado State University Adam Sobel Columbia University. - PowerPoint PPT PresentationTRANSCRIPT
Aquaplanet simulations of the MJO: Wind-evaporation feedback and horizontal
moisture advection
Eric D. Maloney, Walter HannahDepartment of Atmospheric Science
Colorado State University
Adam SobelColumbia University
Funded by: NSF Climate and Large-Scale Dynamics Program, NOAA Climate Program Office, CMMAP
The Madden-Julian Oscillation (MJO)
• Salient features:– Convectively coupled
disturbance that propagates eastward across the Tropics
– 5-10 m s-1 propagation speed in the Indian and west Pacific, where MJO convective variability is strongly coupled to the large-scale flow.
– Simple baroclinic wind structure, with 850 hPa and 200 hPa wind perturbations 180o out of phase
– Characteristic timescales of 30-90 days.
Madden and Julian 1972
Theory: Moisture Modes and Wind-Induced Surface Heat Exchange (WISHE)
Moisture modes:• A moisture mode is a balanced disturbance in which the large-scale dynamics are regulated by the weak temperature gradient approximation (e.g. Sobel et al. 2001; Majda and Klein 2003; Raymond and Fuchs
2007, 2009; Sugiyama 2009)• Properties are strongly regulated by local interactions between convection and tropospheric moisture• Essential dynamics of the mode involve processes that control the tropical moisture field, including latent heat flux and horizontal advectionWISHE:• Early models of WISHE: Mean easterly flow and enhancement of surface fluxes to the east of convection supported disturbance amplitude and eastward propagation (Neelin et al. 1987, Emanuel 1987)• Increasing evidence exists that some form of WISHE may be importance for MJO maintenance and possibly propagation, although it must operate in a state of basic state westerlies, unlike the early linear
models (e.g. Sobel et al. 2009)
SST Boundary Condition for Our Primary Simulation
4
• Resembles the observed mean December-April SST, but with the meridional SST gradient poleward of 10o reduced to ¼ of observed.
• Modified version of NCAR CAM3• T42 horizontal resolution (2.8o x 2.8o), and 26 vertical levels• Perpetual March 21 insolation and ozone• 16-year simulation
Unfiltered Precipitation and Winds vs. Longitude
Even in unfiltered data, many salient features of the MJO apparent, including 5 m s-1 eastward propagation, and a period of 40-60 days.
5 m/s
Wavenumber-Frequency Spectra (Precip)
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30 days90 days30 days90 days
A strong spectral peak exists in the model at same zonal wavenumber and frequency as observations.
Model Observations
Mean Wind and Precipitation Variance
7
Variance units: mm2 day-2
Intraseasonal variance peaks in regions of mean westerly flow at low-levels. Variance is stronger than observed.
8
Composite Precipitation and U850 (Unfiltered)
9
Precipitation is an increasing and strongly non-linear function of saturation fraction of the troposphere (e.g. compare to Bretherton et al. 2004)
Composite PW Anomalies
10
PW Units: mm
Column precipitable water anomalies are sizeable, and in phase with precipitation anomalies, as would be expected given the strong relationship between saturation fraction and precipitation.
Precipitation contour interval 4 mm day-1.
dPW/dt in quadrature with precipitation signal. Precipitation contour 4 mm day-1.
• Horizontal advection is the leading term and is (nearly) in quadrature with PW and precipitation in the intraseasonal MSE budget
• Latent heat flux slightly lags precipitation, and has a positive covariance with precipitation
• 80-90% of MSE tendency due to latent heat component• Vertical advection causes anomalous MSE export during enhanced
precipitation, although is overcompensated by LH and LW anomalies
hv
t
h
Precip
LH+SHvh
LW
12
SWLWSHLHhvvht
h
Intraseasonal Vertically-Integrated MSE Budget
e.g. Neelin and Held (1987)
Composite Vertically-Integrated Moisture Budget
PEqvvqt
q
• Horizontal advection is (nearly) in quadrature with precipitation (and PW) and in phase with the humidity tendency.
• Surface evaporation slightly lags the precipitation anomalies, with a strong positive covariance
• = 50-day mean, = deviation from 50-day mean
• Eastward zonal advection of moisture anomalies is supported by
Composite Zonal Advection (Phase 5)
u u q
x
a
a
x
qu
x
qu
x
qu
x
qu
x
qu
x
qu
x
qu
Total
15
PrecipU850
• At time of peak moistening in the model, total zonal winds are on the order of 5 m s-1.
• That is helping to regulate eastward propagation in the model might be testable by changing the SST boundary condition in the model in order to reduce the basic state westerly flow in the model.
• Meridional advection appears to act more as a damping mechanism on moisture anomalies, mainly through
u u q
x
v q
y
Sensitivity Tests
1) Set surface fluxes at climatological mean to test influence of WISHE
2) Use SST distribution with reduced zonal gradient to test influence of reduced zonal advection through reduction in
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u u
Control Versus No-WISHE ComparisonControl No-WISHE
• WISHE appears to destabilize the MJO in the model. 30-90 day, zonal wavenumber 1-3 variance decreases dramatically without WISHE active
• Small spatial scale precipitation variability that moves slowly east is still apparent in the model
Effect of Reduced Basic State Westerlies
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30 days90 days
Control
Reduced Zonal Gradient
• The space time-spectrum of precipitation still indicates a concentrated spectral peak, but now it occurs near 100 day period rather than 40-50 days.
• Propagation speed is 2.5 m s-1 rather than 4-5 m s-1, which is the approximate total eastward zonal wind at peak moistening as well.
• Supports the role of in eastward propagation
u u q
x
Lag-Regression Plot vs. 141oE Wind
19
Control Reduced Zonal Gradient
• Propagation speed slowed from 4-5 m s-1 to about 2.5 m s-1 in going to the simulation with reduced zonal gradient and reduced westerlies.
• Supports the role of in eastward propagation
u u q
x
Conclusions
• An MJO in an aquaplanet GCM simulation is analyzed that shows some characteristics of a moisture mode
• The model MJO is destabilized by wind-evaporation feedback, and appears to propagate eastward through advection of anomalous humidity by the sum of perturbation winds and mean westerly flow
• At the phase of peak moistening, the total zonal wind at 850 hPa is 5 m s-1, approximately the same as the propagation speed of the intraseasonal disturbances
• A zonally-symmetric aquaplanet does not support a robust MJO
Open Questions/Future Work
• Why is the MJO in a simulation with realistic meridional temperature gradients so unlocalized in frequency?
• What initiates the MJO in this model?
• Can the horizontal advection mechanism in this model be even more convincingly proven (e.g. by manipulating moisture advection?)
• Importance of cloud-radiative feedbacks?
Thanks!
Extra Slides
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Theory: Wind-Induced Surface Heat Exchange (WISHE)
• Early models of WISHE: Mean easterly flow and enhancement of surface fluxes to the east of convection supported eastward propagation (Neelin et al. 1987, Emanuel 1987)
Araligidad (2007)
• Increasing evidence exists that some form of WISHE may be importance for MJO maintenance and possibly propagation, although it must operate in a state of basic state westerlies, unlike the early linear models (e.g. Sobel et al. 2009)
Motivation for Studying the MJO: Impacts(e.g. Tropical Cyclones)
Maloney and Hartmann (2000)
Enhanced MJO Precip
Suppressed MJO Precip
Higgins and Shi (2001)
We Worked Hard to Get a Reasonable MJO in this Model
Minimum entrainment
Pre
cipi
tatio
n ef
ficie
ncy
Theory: Moisture Modes and the MSE Budget
Peters and Bretherton (2006)
• A moisture mode instability can result if large-scale divergent motions associated with convection import MSE into the column (e.g. Raymond et al. 2009, negative gross moist stability)
• Alternatively, export by divergent motions can be positive, but MSE sources such as latent heat flux and cloud-radiative feedbacks overcompensate to produce MSE increases as a result of convection.
• Such instability is manifest for WTG as strong positive moisture-convection feedbacks• The later view appears most relevant to the simulated MJO we analyze here
SST Distributions Used
Zonally Symmetric
“Realistic” SST
Quarter Meridional Gradient
Wavenumber-Frequency Spectra (U850)
29
30 days90 days30 days90 days
Model Observations
A concentrated model peak also occurs in zonal wind, although variance too strong compared to observed.
GCM Unfiltered Precipitation vs. Longitude
5 m/s40 d
60 d
50 d
30
Wavenumber-Frequency Spectra (U850)
31
Zonally Symmetric
“Realistic” SST
Quarter Gradient
Observations
Composite Precipitation and U850 (Unfiltered)
From Wheeler and Hendon (2004)
Precip
U850
(Notice reversed time axis)
33
Westerly wind maximum lags precipitation maximum by about 5 days (1 MJO phase). Note the approximate 5 m s-1 total wind at Phases 4 and 5. Composited using the method of Wheeler and Hendon (2004)
Composite Humidity Anomalies
34
Unlike popular hypothesis in the literature, no initial and gradually deepening low-level precursor humidity signal in the lower troposphere precedes MJO convection.
Lag CompositesResults
Composite Horizontal Advection (MSE)
Meridional Zonal
36
(Notice reversed time axis)
Composite U-Wind, T
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Contour=0.4 KContour=1 m s-1
Mean Wind (Vertical Profile)
38
• Precipitation and the vertical advection (convergence) terms largely are equal and opposite
• Anomalous vertical moisture advection is negative at the time of peak moistening
• Horizontal advection is (nearly) in quadrature with precipitation, consistent with its role suggested in the MSE budget
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PEqvvqt
q
qv
vq
Precip
t
q
E
Intraseasonal Precipitable Water Budget
• Meridional advection tends to be a damping influence on anomalies. The term is prominent, acting somewhat like a diffusion in the presence of strong moisture gradients
Composite Meridional Advection (Phase 5)
v q
y
y
mv
y
mv
y
mv
x
mu
x
mu
x
mu
Total
Total
41
GCM Unfiltered U850 vs. Longitude
42
Control No-WISHE
• Get the sense right away that eastward propagation is slower when the basic state westerlies are changed, supporting the role of in eastward advection.
Unfiltered Precipitation vs. Longitude,Control Versus No-WISHE
Control Reduced Zonal Gradient
u u q
x
Lag-Regression Plot vs. 141oE Wind
44
Control Reduced Zonal Gradient
• Propagation speed slowed from 4-5 m s-1 to about 2.5 m s-1 in going to the simulation with reduced zonal gradient and reduced westerlies.
• Supports the role of in eastward propagation
u u q
x
Precipitation Variance and Mean Wind
45
Mean Wind and Precip
46