Understanding climate model biases in Southern Hemisphere

mid-latitude variability

Isla Simpson1

Ted Shepherd2, Peter Hitchcock3, John Scinocca4

(1) LDEO, Columbia University, USA (2) Dept of Meteorology, University of Reading, UK (3) DAMTP, University of Cambridge, UK (4) CCCma, Environment Canada, Canada

The Southern Annular Mode

Dominant mode of variability in SH extra-tropical circulation

Climatology First EOF

ERA-Interim re-analysis

The SAM timescale

Calculate the autocorrelation function

Calculate the e-folding timescale.

=7 days

The SAM timescale bias – CMIP3 Climate models exhibit much too persistent SAM anomalies in the summer season.

Gerber et al (2008)

Obs

IPCC models

The SAM timescale bias – CCMVal2 Climate models exhibit much too persistent SAM anomalies in the summer season.

Obs

CCMVal modelsGerber et al (2010)

Climate Models exhibit a SAM that is much too

persistent in the summer season.

Gerber et al (2010)

The SAM timescale bias – CCMVal2

Climate Models exhibit a SAM that is much too

persistent in the summer season.

The SAM timescale bias – CMIP5

Many climate forcings produce a mid-latitude circulation response that projects onto the SAM.

Ozone depletion

Son et al (2010), JGR

Why is this potentially of concern for simulating forced responses?

May indicate that we’re getting an important process wrong in the simulation of the SH extra-tropical circulation.

Why is this potentially of concern for simulating forced responses?

Eddy Feedbacks(Lorenz and Hartmann 2001, 2003), Robinson 2000)

Dissipative processes e.g. surface friction

Intraseasonal Forcing e.g. forcing from the stratosphere(Keeley et al 2009)

Can we isolate the role for “internal” tropospheric dynamics on the SAM timescale bias from the influence of stratospheric variability as an intraseasonal forcing on the SAM?

A stratospheric influence on SAM timescales?

Thought to be stratospheric variability that gives rise to this maximum…variability in the timing of the vortex breakdown (Baldwin et al 2003)

The SH vortex breaks down too late in GCMs, maybe this is resulting in enhanced stratospheric variability in the summer and contributing to the SAM timescale bias?

The Canadian Middle Atmosphere Model

Comprehensive stratosphere resolving GCM

T63L71, lid=0.0006hPa

Without interactive chemistry

Prescribed SSTs

No QBO

Constant GHG’s (1990’s concentrations)

Model Experiments

100 year free running control simulation (FREE)

100 year nudged simulation (NUDGED)

In NUDGED, the zonal mean vorticity, divergence and temperature in the stratosphere are nudged toward the zonal mean, seasonally varying climatology of FREE.

We eliminate zonal mean stratospheric variability but keep the climatology the same.

The Nudging Process

In spectral space

N

oXXpK

t

X

)(

)(

Only acting on the zonal mean

K

The Nudging Process

In spectral space

N

oXXpK

t

X

)(

)(

Only acting on the zonal mean

timeclimatology

FREE and NUDGED have the same climatologies, but FREE has stratospheric variability, NUDGED

does not.Vortex Breakdown DatesFREE NUDGED

ERA-Interim

FREE

FREE

NUDGED

Contribution from stratospheric variability

Stratospheric variability enhances the SAM timescales in the SH spring.

NUDGED

ERA-Interim

There does seem to be a problem in the “internal” dynamics of the tropospheric circulation.

Is this caused by climatological circulation biases?

Relationship between climatological jet bias and SAM timescales

Kidston and Gerber (2010)

If we improve the jet position, do we improve the timescale of SAM variability?

Obtain the mean tendency that is required to bring the model toward the ERA climatology (Kharin and Scinocca, 2012, GRL) applying that constant seasonally varying tendency to the model.

Model Climatology

Observed Climatology

Different from nudging in that variability can still occur, just around a new climatological state.

Time

Bias Correcting Experiments

Two different experiments

Bias correcting at all levels – BC

Bias correcting in the troposphere and nudging the zonal mean toward ERA-Interim in the stratosphere - BCNUDG

• Both stratospheric and tropospheric variability but around an improved climatological state. Improved timing of the vortex breakdown and improved tropospheric jet structure.

• Removed stratospheric variability but has an improved climatological timing of the vortex breakdown. Improved the tropospheric jet structure.

Improved tropospheric jet structure?

Annual Mean Timescales

Kidston and Gerber (2010)

Annual Mean Timescales

Annual Mean Timescales

Annual Mean Timescales

The SAM timescale bias in CMAM does not seem to be caused by climatological circulation biases.

Eddy feedback biases?

Eddy feedbacks on the SAM

Eddies driving the SAM

SAM driving eddies i.e., a positive feedback

See Lorenz and Hartmann (2001), Simpson et al (2013)

Eddy forcing of the SAM regressed onto the SAM Index

Quantify the feedback strengths for each simulation and the reanalysis.

Focus on the DJF season.

Synoptic scale eddy feedback (k>3)

Planetary scale eddy feedback (k=1-3)

Summary of DJF feedback strengths

This is mostly coming from wavenumber 3

DJF regressions averaged over lags +7 to + 14 days

ERA

u

-u’v’, k=3

FREE

Regressions on the 300hPa (+7 to +14 lag average)ERA-Interim

-u’v’ (k=1-3)

Regressions on the 300hPa (+7 to +14 lag average)

ERA-Interim FREE

-u’v’ (k=1-3)

-u’v’ (k=1-3)

Comparison with CMIP-5 historical simulations

20 models: those with 6 hourly u and v available

Quantify DJF feedback strength

Eddy feedback, All k

Eddy feedback, All k

Eddy feedback, k=1-3

Eddy feedback, k=1-3

Virtually all GCMs exhibit this same bias in planetary wave feedbacks.

Models don’t capture the negative feedback by planetary scale waves that is localised to the south west of New Zealand in the summer season.

Relation to climatological circulation biases?

Our bias corrected runs tell us that climatological circulation biases are NOT the CAUSE of the eddy feedback bias.

But the climatological circulation biases and eddy feedback biases could be related e.g. they could have a common cause.

Climatologically there is wave activity propagating into the mid-latitudes to the S-W of

New ZealandERA ) '''( vu

FREE) '''( vu

There are common climatological biases in the region around New Zealand

300hPa eddy geopotential height

ERA FREE-ERA

There are common climatological biases in the region around New Zealand

300hPa eddy geopotential height

FREE-ERA CMIP5 - ERA

There are common climatological biases in the region around New Zealand

300hPa eddy geopotential height

CMIP5 - ERA

CMIP5 CONSENSUS

Climatological jet latitude bias

CMIP-5

ERA

Conclusions

Overly persistent SAM variability in the SH summer season is a common model bias.

The CMAM experiments demonstrated a bias in internal tropospheric dynamics that is not alleviated by improving the climatological circulation. The problem is associated with a bias in the feedback by planetary scale waves in the model in the summer season.

This is true of the majority of other models in the CMIP-5 archive.

Conclusions

In order to have faith in the future predictions for the SH mid-latitude circulation in the summer season, we need to understand the planetary wave feedback localised to the SW of New Zealand and why it is biased in the models.

But….

Models do reasonably well at simulating past SAM trends. CMIP-5 DJF SAM Trends

Gillett and Fyfe (2013), GRL

Are we able to simulate recent SH SAM trends correctly for the correct reason?

Is our ability to simulate SAM eddy feedbacks correctly somehow less important than we imagine for our ability to simulate forced responses?

Seasonal Variation in Timescales

Eddy feedback, k>3

Eddy feedback, k=>3

Climatologically there is wave activity propagating into the mid-latitudes to the S-W of

New ZealandERA ) '''( vu

FREE) '''( vu

Evidence for this relationship in simplified GCM strat-trop coupling experiments

Dynamical Core Experiments

Timescale of natural variability

Resp

onse

to

Forc

ing

Simpson et al (2010)