© Crown copyright Met Office Atmospheric Blocking and Mean Biases in Climate Models Adam Scaife,...

© Crown copyright Met Office

Atmospheric Blocking and Mean Biases in Climate

Models

Adam Scaife,

Tim Hinton, Tim Woollings, Jeff Knight,

Srah Keeley, Gill Martin and Malcolm Roberts

Reading University

December 2010


Atmospheric Blocking

Pelly and Hoskins (2003): Blocking index B is the difference between the average potential temperature in the N box and the average potential temperature in the S box.

B > 0 implies blocking

Tibaldi and Molteni (1990): similar index based on GPH at 500hPa

A signature of atmospheric wave breaking


Blocking Maintenance

• Maintenance of blocks by potential vorticity flux from small scale eddies (Shutts 1983, 1986, 1987)

• SELF – Synoptic Eddy and Low Frequency flow interaction (Lau 1988)

• General rule for transient eddy feedback on low frequency variability (Kug et al 2009)

• These suggest upscale feedback and a behaviour in this case that is opposite to that in L.F. Richardson’s famous rhyme:

Big whirls have little whirls that feed on their velocity,

and little whirls have lesser whirls and so on to viscosity

Motivates some key questions:

• Does this imply that blocking frequency in climate models is very sensitive to resolution?

• Does this mean that regional climate change signals could be very wrong? (e.g. Palmer et al 2008)


Blocking Errors

“recent studies have found that GCMs tend to simulate the location of NH blocking more accurately than frequency or duration” (IPCC, AR4, WG1 Chapter 8)

Climate model blocking frequencies (D’Andrea et al. 1997)

Almost all models underestimate blocking in almost all regions

Concentrate on frequency


Mean or variability errors?

If this procedure corrects errors in blocking frequency and the variability term is realistic then the error lies in the mean

M = model O = obs

Overbar = climate meanPrime = time varying part

Swap model mean for observed mean:


Atmospheric Blocking

Lack of blocking in both Atlantic and Pacific

Same error in Summer and Winter

Peak deficit > 0.15 day-1

Mean values ~0.25 day-1

Winter

Summer


Other Models

“recent studies have found that GCMs tend to simulate the location of NH blocking more accurately than frequency or duration” (IPCC, AR4, WG1 Chapter 8)


Blocking Errors and Resolution

Sensitivity to Horizontal Resolution in JMA/MRI AGCM(Matsueda et al 2009)

Sensitivity to Vertical Resolution in HadAM3(Scaife and Knight 2009)


Mean versus variability

Underestimated blocking

Balanced by overestimated ‘anti-blocking’ or ‘mobile’ days!

=> width (variability) is relatively well modelled

=> error is in mean climate and not in variability

So can our model simulate the blocking process after all?


Bias corrected errors in our model

Error removed in both Atlantic and Pacific

Error removed in Summer and Winter

Winter

Summer

Winter bias corrected

Summer bias corrected


Bias corrected errors in IPCC models

Greatly reduced

Smaller amount remaining


Mean State ErrorsSensitivity to Horizontal Resolution in JMA/MRI AGCM(Matsueda et al 2009)

Pacific mean errors are larger in high resolution model

Atlantic mean errors are smaller in high resolution Model

Has the right sense to explain the blocking result


New HadGEM3 model:

See Scaife et al 2010: Atmospheric Blocking and Mean Biases in Climate Models, J.Clim., in press

New model has small atmospheric mean biases.

This leads to a good representation of Atlantic blocking.

Old Model

New Model

New Model

Old Model – bias removed

Observed Blocking


Here’s the cause:

North Atlantic Gulf Stream Cold bias is creating the mean climate error in the atmosphere

N96L85O(1) N216L85O(0.25)


An example blocking event:


Summary

• Atmospheric blocking is still underestimated in current climate models

• Most of the deficit is directly attributable to a westerly bias in mean climate

• This westerly bias is removed in latest HadGEM3 models

• It stems from the ubiquitous cold bias in the N Atlantic

• This also explains why it occurs in so many models

• Latest HadGEM3 models also show good Atlantic blocking frequency

• Is this all circular: low resol’n -> no blocking -> mean bias?

• No :- N96 A runs show blocking, ocean only runs show no Atlantic bias

• Blocking duration also increases accordingly

• Wave-breaking is alive and well in the model


Revisiting high resolution blocking results:

Swap high and low resolution mean states

TL95 looks like TL959!

Mio Matsueda

© Crown copyright Met Office Atmospheric Blocking and Mean Biases in Climate Models Adam Scaife,...

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