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Towards a better understanding of changes in European temperature extremes

A multi-model analysis from CMIP5/CFMIP2

Julien Cattiaux, Hervé Douville, Aurélien Ribes and Fabrice Chauvin.

CNRM/Météo-France, Toulouse, France.

January 25, 2012

J. Cattiaux et al. (CNRM) CNRM

(2)

Motivations

Temperature extremes?

Extremely warm/cold days: Tmax/Tmin above/below the 90th/10th centile of a reference pdf (e.g., observations or historicalruns).

Highest impacts, responses not necessarily scaled on the mean.

Questions

Uncertainties in GCMs: Large-scale circulation? Soil processes?

Cloud feedbacks?

How to separate dynamical vs. non-dynamical contributions?

Multi-model data (9 GCMs so far)

CMIP5: historical(1979–2008) &rcp85(2070–2099): 8 GCMs.

CFMIP2: amip&amipFuture: 4 GCMs.

J. Cattiaux et al. (CNRM) CNRM

(3)

Motivations

Temperature extremes?

Extremely warm/cold days: Tmax/Tmin above/below the 90th/10th centile of a reference pdf (e.g., observations or historicalruns).

Highest impacts, responses not necessarily scaled on the mean.

Questions

Uncertainties in GCMs: Large-scale circulation? Soil processes?

Cloud feedbacks?

How to separate dynamical vs. non-dynamical contributions?

Multi-model data (9 GCMs so far)

CMIP5: historical(1979–2008) &rcp85(2070–2099): 8 GCMs.

CFMIP2: amip&amipFuture: 4 GCMs.

J. Cattiaux et al. (CNRM) CNRM

(4)

Motivations

Temperature extremes?

Extremely warm/cold days: Tmax/Tmin above/below the 90th/10th centile of a reference pdf (e.g., observations or historicalruns).

Highest impacts, responses not necessarily scaled on the mean.

Questions

Uncertainties in GCMs: Large-scale circulation? Soil processes?

Cloud feedbacks?

How to separate dynamical vs. non-dynamical contributions?

Multi-model data (9 GCMs so far)

CMIP5: historical(1979–2008) &rcp85(2070–2099): 8 GCMs.

CFMIP2: amip&amipFuture: 4 GCMs.

J. Cattiaux et al. (CNRM) CNRM

(5)

Future changes in wintertime cold days

Probability of exceedingQ10historical inrcp85(PQ10)

J. Cattiaux et al. (CNRM) CNRM

(6)

Future changes in wintertime cold days

Probability of exceeding Q10amip in amipFuture(PQ10)

J. Cattiaux et al. (CNRM) CNRM

(7)

European temperatures & North-Atlantic dynamics

Weather regimes

Clustering of daily Z500anomalies. (e.g., Michelangeli et al., 1995)

Temperatures well discriminated among the 4 classical regimes.

PQ10=P

kP(Ωk)·P(T <T10|Ωk).

Z500(NCEP2)

PQ10 (E-OBS)

J. Cattiaux et al. (CNRM) CNRM

(8)

Future changes in mean Z500

Z500, DJFM,rcp85−historical

J. Cattiaux et al. (CNRM) CNRM

(9)

Future changes in mean Z500

Z500, DJFM,amipFuture−amip

J. Cattiaux et al. (CNRM) CNRM

(10)

Evaluating dynamical contributions

Contribution of changes in regimesfrequencies:

X =X

k

fkxk F−PX = XFXP=X

k

fkFxkFX

k

fkPxkP

= X

k

∆fk·xkP

| {z }

BC

+X

k

fkP·∆xk

| {z }

WC

+X

k

∆fk·∆xk

| {z }

RES

Contribution of changes in regimesstructures:

∀k xk= Φ(dk) ∆xk= ΦF(dkF)−ΦP(dkP) = [ΦF(dkF)−ΦP(dkF)]+[ΦP(dkF)ΦP(dkP)]

Final breakdown

F−PX =X

k

∆fk·ΦP(dkP)

| {z }

BC

+X

k

fkP·ΦP(∆dk)

| {z }

WCd

+X

k

fkP·∆Φ(dkF)

| {z }

WCΦ

+RES

Cattiaux et al.,SI Clim. Dyn., submitted.

J. Cattiaux et al. (CNRM) CNRM

(11)

Evaluating dynamical contributions

Contribution of changes in regimesfrequencies:

X =X

k

fkxk F−PX = XFXP=X

k

fkFxkFX

k

fkPxkP

= X

k

∆fk·xkP

| {z }

BC

+X

k

fkP·∆xk

| {z }

WC

+X

k

∆fk·∆xk

| {z }

RES

Contribution of changes in regimesstructures:

∀k xk= Φ(dk) ∆xk= ΦF(dkF)−ΦP(dkP) = [ΦF(dkF)−ΦP(dkF)]+[ΦP(dkF)ΦP(dkP)]

Final breakdown

F−PX =X

k

∆fk·ΦP(dkP)

| {z }

BC

+X

k

fkP·ΦP(∆dk)

| {z }

WCd

+X

k

fkP·∆Φ(dkF)

| {z }

WCΦ

+RES

Cattiaux et al.,SI Clim. Dyn., submitted.

J. Cattiaux et al. (CNRM) CNRM

(12)

Evaluating dynamical contributions

Contribution of changes in regimesfrequencies:

X =X

k

fkxk F−PX = XFXP=X

k

fkFxkFX

k

fkPxkP

= X

k

∆fk·xkP

| {z }

BC

+X

k

fkP·∆xk

| {z }

WC

+X

k

∆fk·∆xk

| {z }

RES

Contribution of changes in regimesstructures:

∀k xk= Φ(dk) ∆xk= ΦF(dkF)−ΦP(dkP) = [ΦF(dkF)−ΦP(dkF)]+[ΦP(dkF)ΦP(dkP)]

Final breakdown

F−PX =X

k

∆fk·ΦP(dkP)

| {z }

BC

+X

k

fkP·ΦP(∆dk)

| {z }

WCd

+X

k

fkP·∆Φ(dkF)

| {z }

WCΦ

+RES

Cattiaux et al.,SI Clim. Dyn., submitted.

J. Cattiaux et al. (CNRM) CNRM

(13)

Evaluating the term Φ

P

(d

kF

)

I.e. the mean value of X that would produce present-day physics from future circulations.

One way to do it: consider

ΦP(dkF)ΦP(dfkP) ,

where dfkP are the flow-analogs ofdkF sampled among the present-day circulations dkP.

See, e.g., Lorenz (1969) for flow-analogs.

−2 −1 0 1 2

−2

−1 0 1 2

EOF1

EOF2

●●

pre

Cattiaux et al.,SI Clim. Dyn., submitted.

J. Cattiaux et al. (CNRM) CNRM

(14)

Evaluating the term Φ

P

(d

kF

)

I.e. the mean value of X that would produce present-day physics from future circulations.

One way to do it: consider

ΦP(dkF)ΦP(dfkP) ,

where dfkP are the flow-analogs ofdkF sampled among the present-day circulations dkP.

See, e.g., Lorenz (1969) for flow-analogs.

−2 −1 0 1 2

−2

−1 0 1 2

EOF1

EOF2

●●

● ●

● ●

● ●

● ●

●●

● ●

pre fut

Cattiaux et al.,SI Clim. Dyn., submitted.

J. Cattiaux et al. (CNRM) CNRM

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