Simulating the extratropical response to the Madden-Julian Oscillation

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Simulating the extratropical response to the Madden-Julian Oscillation Hai Lin RPN-A, Environment Canada 46 th Congress of CMOS, Montreal May 29, 2012

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Simulating the extratropical response to the Madden-Julian Oscillation. Hai Lin RPN-A, Environment Canada 46 th Congress of CMOS, Montreal May 29, 2012. Outlines. Introduction Numerical experiments: Dependence on heating location (Lin et al. 2010) Nonlinearity - PowerPoint PPT Presentation

Transcript of Simulating the extratropical response to the Madden-Julian Oscillation

Page 1: Simulating the extratropical response to the Madden-Julian Oscillation

Simulating the extratropical response to the Madden-Julian Oscillation

Hai Lin

RPN-A, Environment Canada

46th Congress of CMOS, Montreal

May 29, 2012

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Outlines

o Introduction

o Numerical experiments: Dependence on heating location (Lin et al. 2010)

Nonlinearity

Dependence on initial condition

o Summary

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Introduction

o MJO

o Global impact (boreal winter):

NAO

Canadian temperature

Canadian precipitation

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Correlation when PC2 leads PC1 by 2 pentads: 0.66

Lin et al. (2010)

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Normalized Z500 regression to PC2

Lin et al. (2010)

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Model and experiment

• Primitive equation AGCM (Hall 2000) – similar configuration of model forcing as the Marshall-Molteni model, but not Q-G.

• T31, 10 levels

• Time-independent forcing to maintain the winter climate

• No moisture equation, no interactive convection

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Thermal forcing

Exp1 forcing Exp2 forcing

Lin et al. (2010)

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Z500 response

Exp1

Exp2

Lin et al. (2010)

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• Are the responses to opposite signs of MJO forcing mirror images? (nonlinearity)

• Which response is more predictable? less spread, less sensitive to initial condition and background flow?

• How different are those responses to the same MJO forcing?

• How does the response depend on extratropical jet initial condition?

Questions:

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• 3 sets of experiments:

1) Control

2) +MJO forcing

3) –MJO forcing

• From 360 different observed initial conditions

• 30-day nonlinear integrations

Nonlinearity

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Thermal forcing

Exp1 forcing Exp2 forcing

Lin et al. (2010)

+MJO thermal forcing

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NonlinearityZ500 response

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spread

+MJO response has less spread, less sensitive to initial condition, thus more predictable

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EOF

Downstream shift Intensify

of 360 Z500 day 6-10 responses to the same +MJO

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Dependence on initial condition U200

Jet intensifies

Jet moves southward

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Summary

• There is significant nonlinearity in response in mean response and spread

• Response to –MJO is more sensitive to initial condition (when the heating is over central Pacific), and less predictable

• Response sensitive to the strength and position of East Asian jet

• Implication to subseasonal forecasting: MJO phase and jet initial condition

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• Linear integration, winter basic state

• with a single center heating source

• Heating at different longitudes along the equator from 60E to 150W at a 10 degree interval, 16 experiments

• Z500 response at day 10

Why the response to a dipole heating is the strongest ?

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Day 10 Z500 linear response

80E

110E

150E

Similar pattern for heating 60-100E

Similar pattern for heating 120-150W