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CFMIP2: Options for SST-forced and slab experiments

Mark Ringer, Brian Soden

Hadley Centre,UK & RSMA/MPO, US

CFMIP/ENSEMBLES Workshop: Paris, 11-13th April 2007

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Introduction – consider options for SST-forced and slab model experiments

Some issues to consider prior to this afternoon’s break-out group session on experimental design.

CMIP 1% per year composite ΔSST pattern Climatological or AMIP control? Constructing the composite ΔSST pattern

Other idealized SST perturbation experiments and approaches

Slab model experiments

These are just some ideas to get the discussion going…

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CMIP 1% per year increase in CO2: ΔTs at time of doubling (e.g. Wyant et al. 2006)

Arguably more realistic and relevant to climate change over the 21st century.

However, the perturbation is relatively small (<ΔTs> ~ 1.4K) and there is little spatial structure in the tropics – resembles a uniform ΔTs in the zonal mean.

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Choosing the control experiment – seasonal climatology or varying (AMIP) SSTs?

Climatology (e.g. 10 years) – reaches an equilibrium, which should hopefully reduce the noise in the response.

AMIP – control is potentially more useful for evaluation studies, but the response will be “conditioned” by ENSO and other variability during the period.

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Constructing the composite ΔTs pattern

One alternative to simple averaging might be to “average the patterns”

i.e. ΔTs/<ΔTs>

and then scale by ensemble mean <ΔTs>.

This would reduce biases due to very high or low sensitivity models, for example.

ΔTs ΔTs /<ΔTs>

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In addition, we could also consider…

A simple globally uniform SST perturbation (e.g. the ensemble mean ΔTs) to determine the impact of the SST pattern versus the overall warming – a seasonally varying version of the Cess et al. (1989) method

A zonally uniform SST perturbation to isolate the impact of changes to the meridional gradient in SST (analogous to the aquaplanet experiments in APE)

Reducing the SSTs – this might also provide insights into feedbacks. E.g. Wyant et al. show that +2K/-2K responses are not necessarily symmetric in a given model

Including a composite sea-ice response as well as the SST perturbation – but how?

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Other approaches – e.g. Barsugli et al. (2006)[Climate Dynamics, 27(5), Oct. 2006]

Specified 2K warming/cooling at different locations in the tropics in order to investigate sensitivity to the pattern of ΔSST. Allowed them to separate the “local” and “global” sensitivities to the warming. Example shown is for TOA net radiation – local sensitivity is +ive everywhere but global sensitivity can be either +ive or -ive.

Other techniques include introducing (or suppressing) warming at specific locations believed to be important. E.g. Schneider et al. [JAS, 54, May 1997] held SSTs in the Pacific cold tongue at control values while allowing temperatures elsewhere to vary in response to doubling CO2.

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Slab models – equilibrium 2×CO2 experiments, as in CFMIP1

Although not identical, the control states are relatively similar.

Allows us to consider equilibrium climate sensitivity – if that is still thought to be important!

Also provides continuity with previous studies.

• Will slab models be included in IPCC AR5?

• If not, what will they be “replaced” by (if anything)?

• Should CFMIP2 do them in any case?

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Slab models – continued

Produce larger response – magnitude and spatial pattern – than the 1% per year simulations.

Could produce a composite pattern from these for the SST-forced experiments?

In essence this would mean CFMIP2 looking like CFMIP1 but with patterned SST experiments replacing the Cess et al. (1989) runs plus sensitivity experiments and any other idealized experiments we decide to do…

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Summary of points discussed

Composite pattern derived from…

1%/year runs at time of CO2 doubling

Slab 2×CO2 equilibrium runs

Construction of composite pattern

Simple averaging Average of “patterns” scaled by mean <ΔSST>

Control simulation Seasonally varying climatology

AMIP SSTs, i.e. include interannual variability

Composite sea-ice pattern

Include? Don’t include?

Other idealized experiments

“Classic”, e.g. uniform ΔSST, reduced SST, etc

More sophisticated, e.g. Barsugli et al. method

Slab model experiments

Exclude if not part of IPCC AR5

Perform anyway as part of CFMIP2