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Signals of Circulation Trends at High Latitudes Paul J. Kushner Dept. of Physics, University of Toronto Laurent Terray CERFACS,Toulouse

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Signals of Circulation Trends at High Latitudes

Paul J. KushnerDept. of Physics, University of Toronto

Laurent TerrayCERFACS, Toulouse

Outline

Introduction

Perspectives from . . .

• CCSM Large Ensemble

• NAM Dynamics

Conclusion

Introduction

High latitude circulation subject to climate noise and observational uncertainty, making D&A of human influence difficult.

Circa 2003: Detectable human influence on SLP detectable but model trends too weak.

Presently: Only lower latitude SLP trends attributable to human influence (Gillett and Stott).

D&A of 20c SLP Trends (Gillett et al. 2003) AO Index 1950-2010

High Latitude Circulation Signals: Hard to Detect

21st Century DJF Response, CCSM3 “Large” Ensemble

SLP

Precip

Ts

Signal # Realizations to Detect Signal

Deser et al. 2011

Today’s Questions

Which changes in high latitude circulation from surface to stratosphere can be attributed, or will be attributable, to human influence?

Are there dynamical insights that constrain the problem?

Seek insights from:

• Large ensemble

• Dynamical ideas on stationary wave/NAM interactions

Primary focus on Northern Hemisphere, with comments on Southern Hemisphere

Perspective from the CCSM3 Large Ensemble

CCSM3 Large Ensemble Results

In this plot, response is calculated as epochal differences.

Thermal response in free troposphere quite robust, in stratosphere not so robust.

Surface and stratospheric circulation responses are not.

60N-90N Response (2005-2065)

Temperature Geopotential

Mean

Standard Deviation

Extremes

Comparing Surface and Free Troposphere

In this plot, response is calculated as 2005-2065 trends.

Mid tropospheric signal thermally dominated and therefore more robust than surface response.

• Time to detection (Deser et al.) will be shorter.

DJF Response, NCAR CCSM3 “Large” Ensemble

SLP

Z500

Signal # Realizations to Detect Signal

Pinpointing Controls on DetectabilitySH includes strong warming from ozone recovery.

• SH response is much more robust than NH response.

CAM3/SST/RAD:

• AMIP with ensemble mean SST driving.

• Mean and spread similar even without air-sea coupling.

Zonal Mean Geopotential Response, DJF

CCSM3

CAM3/SST/RAD

Signal# Realizations to

Detect Signal

Pinpointing Controls on Detectability

Ozone forcing controls SH signal.

GHG warming controls NH signal.

CAM3/SST/RAD

CAM3/SST/NORAD CAM3/NOSST/RAD

Perspective from NAM Dynamics

A Dynamical Point

The NAM-related barotropic response is unpredictable.

NAM barotropic response

~ surface pressure response

~ surface zonal wind response

~ wave-driving response (in stratosphere and troposphere)

What controls wave driving response?

NAM Composited on F(z)

Baldwin & Dunkerton 2001,Polvani & Waugh 2004

[Z] Response

Wave-1 Z* Climatology (shaded) & Response (contours)

Indian Warming

Wave-2 Z* Climatology (shaded) & Response (contours)

Fletcher and Kushner impose warming separately in Tropical Indian Ocean and Tropical Pacific Ocean.

•Linear interference effect controls response.•Is this kind of mechanism at work in the large ensemble?

A Clue from the Tropical SST ProblemPacific Warming

Flet

cher

& K

ushn

er 2

010

[Z] Response

Wave-1 Z* Climatology (shaded) & Response (contours)

Indian WarmingPositive NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Fletcher and Kushner impose warming separately in Tropical Indian Ocean and Tropical Pacific Ocean.

•Linear interference effect controls response.•Is this kind of mechanism at work in the large ensemble?

A Clue from the Tropical SST ProblemPacific Warming

Flet

cher

& K

ushn

er 2

010

[Z] Response

Wave-1 Z* Climatology (shaded) & Response (contours)

Indian WarmingPositive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Fletcher and Kushner impose warming separately in Tropical Indian Ocean and Tropical Pacific Ocean.

•Linear interference effect controls response.•Is this kind of mechanism at work in the large ensemble?

A Clue from the Tropical SST ProblemPacific Warming

Flet

cher

& K

ushn

er 2

010

[Z] Response

Wave-1 Z* Climatology (shaded) & Response (contours)

Indian WarmingPositive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Fletcher and Kushner impose warming separately in Tropical Indian Ocean and Tropical Pacific Ocean.

•Linear interference effect controls response.•Is this kind of mechanism at work in the large ensemble?

Destructive interference

A Clue from the Tropical SST ProblemPacific Warming

Flet

cher

& K

ushn

er 2

010

[Z] Response

Wave-1 Z* Climatology (shaded) & Response (contours)

Indian WarmingPositive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Fletcher and Kushner impose warming separately in Tropical Indian Ocean and Tropical Pacific Ocean.

•Linear interference effect controls response.•Is this kind of mechanism at work in the large ensemble?

Constructive interference

Destructive interference

A Clue from the Tropical SST ProblemPacific Warming

Flet

cher

& K

ushn

er 2

010

Linear Interference in the Large EnsembleDefine index of vertical wave activity flux response in Northern Hemisphere lower stratosphere: TOTAL

Its linear interference component is LIN.

Correlate index with Z response across the ensemble.

Significant fraction of the response associated with interference with planetary waves.

• Need to attribute to specific surface processes (SST, snow,etc.).

TOTAL wave

activity response versus Z response

LINm=1

LIN m=2

Correlations X 10

Summary

Robust high latitude circulation response is baroclinic (thermal).

Non-robust barotropic part is related to NAM and reflects changes to wave driving.

Linear interference between forced and climatological waves controls a fraction of this.

Conclusion

Linear interference mechanism:

• NAM response sensitive to spatial coherence of wave response and stationary wave.

• Different mechanisms might be at play for different waves.

Large ensemble can be used to

• Quantify sources of spread and frame expectations for which climate signals are attributable.

• Explore dynamics underlying spread in circulation responses (see Deser et al. 2011).

• Can imagine using perfect model approach to rigorously test D&A methods. Has this been done?

Zonal Mean Geopotential Trends for Recent Period

Global circulation trend estimates also subject to observational uncertainty.

Clues from Interannual VariabilityNAM is sensitive to structure of surface forcing:

• ENSO negatively coherent with NAM.

• Tropical Indian Ocean SSTs seem to be postively coherent with NAM.

• Eurasian Snow extent in October also negatively coherent with wintertime NAM.

Why is NAM so sensitive to heating structure?

SLP anomalies during El Niño

Ineson and Scaife 2008

HadGAM1 HadSLP2

U Response

Hoerling et al. 2004

U Response to Tropical Indian Ocean Warming

Interference with Stationary Wave Field

ENSO+ (obs) Climo (obs)Z*500-wave1 (NDJ)

Ineson and Scaife 2009

Wave Response to El Niño Forcing in HadGAM1

Garfinkel and Hartmann 2009

Wave activity flux enhanced when planetary wave anomalies align with the stationary wave field.

This drives stratospheric warming(negative NAM), which couples to the troposphere.

Examples:

• ENSO

• Response to Siberian snow

• West Pacific driving of NAM

• Blocking and stratospheric sudden warmings(Garfinkel & Hartmann, Ineson & Scaife, Smith et al., Martius & Polvani, Nishii et al.).

[email protected]

Tuning the Linear Interference Effect

We move the forcing around the latitude circle.

• This gives both positive and negative NAM responses.

• The dynamics is dominated by linear interference effects.

Shifting the position of the cooling

20

[email protected]

Tuning the Linear Interference Effect

We vary the strength of the forcing:

• EM-LIN scales linearly and EM-NONLIN scales quadratically with the forcing.

• For large forcing, EM-NONLIN dominates and the NAM response switches from positive to negative.

• We are fairly close the boundary for nonlinear behaviour to kick in.

Changing  the  strength  of  the  cooling  

21

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Wave-2 Z* Climatology (shaded) & Response (contours)

Zonal MeanZ Response

TPO

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Positive NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Zonal MeanZ Response

TPO

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Positive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Zonal MeanZ Response

TPO

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Positive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Destructive interference

Zonal MeanZ Response

TPO

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Positive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

Constructive interference

Destructive interference

Zonal MeanZ Response

TPO

Why Does the NAM Response Change Sign?

TIOResponse to Tropical SST Forcing in GFDL AM2

Wave-1 Z* Climatology (shaded) & Response (contours)

Positive NAM

Negative NAM

Wave-2 Z* Climatology (shaded) & Response (contours)

• NAM response to TIO is surprisingly large.• TIO weakens and TPO strengthens wave activity flux.• TIO dominated by Wave-2, TPO by Wave-1.

Constructive interference

Destructive interference

Zonal MeanZ Response

TPO

Summary

Interference between wave anomaly and climatological wave accounts for much of sensitivity of NAM to tropical SST forcing.

Given . . .

• A large amplitude climatological wave,

• A prediction of a wave response,

• Strong constructive/destructive interference,

. . . one can predict the high latitude zonal mean response.

This a linear effect, but calculating the response to SST forcing is still inherently nonlinear.

Implications & Generalizations

The sensitivity to longitudal phase might lead to spread in simulated NAM responses to tropical forcing.

Many aspects of the responses are similar between GFDL AM2 and CCSM CAM.

We see similar effects and sensitivities in the simulated NAM response to snow variability in models and obs (Smith et al. 2010, J. Climate and submitted).

Indian Ocean Forced NAM Variability

SST anomalies composited on ENSO events 1950-2001.

Summary of GFDL Simulations

Tropospheric NAM Response v. LIN Component

Trop

osph

eric

NA

M

EM-LIN

Linear interference effect can be tuned by tuning background wave or forcing.

Fletcher & Kushner 2010 & in prep

|ΔΧ*250|

|ΔOLR*| |ΔΧ*250|

|ΔZ250*|

|ΔZPCAP|

|ΔZ250*|

ΔZPCAP

EM-LIN