Analysis of model drift in a climate forecast system used

for decadal predictions

Emilia Sanchez-Gomez, Christophe Cassou, Elodie Fernandez, Laurent Terray

CERFACS – SUC 1875 (Toulouse) France

Special thanks to the CNRM colleagues

1. Initialisation methodology to minimise the model drift

1. Analysis of the drift dynamics in decadal hindcasts

3. Conclusions

Outline

Initialisation methodology

Aims:

1. Minimising the initial shock and the model drift (initial conditions close

to model mean state)

2. Obtaining initial conditions for sea ice and atmosphere components,

compatible with initialisation date.

Solution :

Nudging of the ocean component in the coupled model towards a ocean

reanalysis (NEMOVAR).

ARPEGE-Climat T127 (1.4°), 31 levels

SURFEX Interface

GELATO v5

NEMO 1° 42 levels

OASIS River Routing

TRIP

The NEMOVAR-COMBINE

ECMWF Ocean Reanalysis

Balsameda et al. 2010

CNRM-CM5 coupled model

Nudging only of the ocean component =

3D Newtonian damping +

Sea surface restoring

Aims:

1. Minimising the initial shock and the model drift (initial conditions close

to model mean state)

2. Obtaining initial conditions for sea ice and atmosphere components,

compatible with initialisation date.

Initialisation methodology

NO-EQ IC No 3D nudging within the 1°S–1°N band

• Several tests have been performed on the nudging parameters to avoid

spurious effects on the ocean and to control the nudging strength (spatial

domain, sea surface restoring).

Initial conditions issued from nudging experiments

3D Newtonian damping + sea surface restoring

NO-TROP IC No 3D nudging Within the 15°S–15°N band

Initial conditions issued from nudging experiments

NO-EQ IC No 3D nudging within the 1°S–1°N band

3D Newtonian damping + sea surface restoring

• Several tests have been performed on the nudging parameters to avoid

spurious effects on the ocean and to control the nudging strength (spatial

domain, sea surface restoring).

Mean 1960-2005

1. Initial conditions to minimise model drift Initial conditions issued from nudging experiments

Ocean Heat Content (300m) NOEQ - NOTROP

Uinitialized NEMOVAR NOEQ NOTROP

ΔH

Indian Ocean Pacific Ocean Atlantic Ocean

SST averaged over 60°N - 35°S NOEQ vs NOTROP

SST observations

Forecast annual means for leadtime 1- 5 (years)

- Only 9 initial dates

- Only atmosphere is perturbed to obtain the members (10 members)

1. Initial conditions to minimise model drift Decadal experiments using different ICs

SST averaged over 60°N - 35°S NOEQ vs NOTROP

SST observations

Forecast annual means for leadtime 1- 5 (years)

- Strong warming at forecast range 1

- Progressive cooling towards the equilibrium state

1. Initial conditions to minimise model drift Decadal experiments using different ICs

SST observations 0.08 °C

0.01 °C

NOEQ decadal forecasts exhibits a stronger warming at the first lead

years NOTROP decadal forecasts completed for CMIP5.

SST averaged over 60°N - 35°S

1. Initial conditions to minimise model drift Decadal experiments using different ICs

NOEQ vs NOTROP

Focus on internal variability modes of the CNRM-CM5 model

2. Understanding the model drift Analysis of the model drift : Methodology

1. Natural modes of variability determined by EOF analysis on PiCTL

(PreIndistrial – Control) experiment :

- ENSO

- Tropical Atlantic

- AMO, PDO

2. Decadal forecasts EOF projection PDF analysis

Seasonal means considered: JFM , AMJ , JAS, OND

(only JFM is shown here)

Leadtim

e (

years

) 2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Uninitialized

Leadtim

e (

years

) 2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

NOEQ

Uninitialized

Leadtim

e (

years

) 2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Y1: no drift

Y2: An El Niño event is excited for most of members

Y3: An La Niña event occurs for most of members

- Fast drift (equilibrium at 4 years lead time)

- Oscillatory behaviour

NOEQ

Uninitialized

Leadtim

e (

years

) 2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Y1: no drift

Y2: An El Niño event is excited for most of members

Y3: An La Niña event occurs for most of members

- Fast drift (equilibrium at 4 years lead time)

- Oscillatory behaviour

- More moderate initial shock for NOTROP initialized

forecasts

NOTROP

NOEQ

Uninitialized

Leadtim

e (

years

) 2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Mean bias CNRM-CM5 Non Initialized – NEMOVAR

Ocean heat content [0-300m]

The strong heat release can be explained by model

biases

NOTROP

NOEQ

Uninitialized

2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Color=precip / contour=Z500

(significance hatching 95%)

Atmospheric response :

NOEQ – NOTROP differences

2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Color=precip / contour=Z500

(significance hatching, 95%)

Atmospheric response :

NOEQ – NOTROP differences

NAO WESPAC

NOTROP

NOEQ

Uninitialized

2. Understanding the model drift Analysis of the model drift : Equatorial Pacific (ENSO)

Color=precip / contour=Z500

(significance hatching 95%)

Atmospheric response :

NOEQ – NOTROP differences

- Y1: Initial shock at the first

winter (positive NAO)

- Y2: negative NAO, positive

WESPAC.

NAO WESPAC

NOTROP

NOEQ

Uninitialized

2. Understanding the model drift Analysis of the model drift : Tropical Atlantic

North Tropical Atlantic Mode (JFM)

Power sprectrum

95%

5%

2.3yr 8-16yr

2. Understanding the model drift Analysis of the model drift : Tropical Atlantic

North Tropical Atlantic Mode (JFM)

Power sprectrum

95%

5%

2.3yr

Leadtim

e (

years

)

- Y1: the drift starts

- Linear and slow drift (cooling)

- Smaller differences between NOTROP and NOEQ

forecasts

8-16yr

NOTROP

NOEQ

Uninitialized

2. Understanding the model drift Analysis of the model drift : Tropical Atlantic

North Tropical Atlantic Mode (JFM)

Power sprectrum

95%

5%

2.3yr

Leadtim

e (

years

)

- Y1: the drift starts

- Linear and slow drift (cooling)

- Smaller differences between NOTROP and NOEQ

forecasts

8-16yr

NOTROP

NOEQ

Uninitialized

2. Understanding the model drift Analysis of the model drift : AMO and PDO

AMO PDO

NOTROP

Uninitialized

- Y1: Positives AMO and PDO

- Linear and slow drift (slow cooling)

- Likely connected to ocean gyre adjustement.

- AMO: equilibrium is not reached at leadyear 10

- PDO: equilibrium is reached at leadyear 5

2. Understanding the model drift Analysis of the model drift : AMO and PDO

AMO PDO

NOTROP

Uninitialized

- Y1: Positives AMO and PDO

- Linear and slow drift (slow cooling)

- Likely connected to ocean gyre adjustement.

- AMO: equilibrium is not reached at leadyear 10

- PDO: equilibrium is reached at leadyear 5

2. Understanding the model drift Analysis of the model drift : AMO and PDO

AMO PDO

NOTROP

Uninitialized

- Y1: Positives AMO and PDO

- Linear and slow drift (slow cooling)

- Likely connected to ocean gyre adjustement.

- AMO: equilibrium is not reached at leadyear 10

- PDO: equilibrium is reached at leadyear 5

BIAS COR.

Generating initial conditions controlling nudging strength reduces the

model initial shock, nevertheless the model drift is still present.

Strong warming at forecast range 1 + progressive cooling

The initial shock reduction seems to have no impact on the forecast

skill on SSTs (maybe other variables?).

To derive to its own climate, the model precisely uses the internal

modes of variability that we seek to predict, putting some shade and

uncertainties on traditional skill score.

According to this, the model drift can behaves differently depending

on the internal variability mode considered :

- ENSO: fast drift and oscillatory behaviour.

- North Tropical Atlantic: Slow and linear drift (slow cooling)

- AMO and PDO : slow drift and linear behaviour (for PDO

stabilisation at Y5, whereas for AMO at year 10 is not stabilised yet).

2. Understanding the model drift Conclusions

1. Initial conditions to minimise model drift THANK YOU !!

1. Initial conditions to minimise model drift Impact on the skill (correlation) of SST

Initialized NOTROP Initialized NOEQ Uninitialized

Detrended forecasts

Ocean Initialisation: Nudging experiments (3D damping)

)(1

... oTTt

T

)(1

... oSSt

S

β = f(depth, space)

Reanalysis

Current

No nudging within

the Equatorial band

(1oN-1oS) and

Near the coast

(300km)

(1/ β) =0

In the thermocline

(1/ β) =0

Deep Ocean

β = 360 days

Below thermocline

β = 10 days

Ocean Initialisation: Nudging experiments (3D damping)

)( 1 obsk

o

nsns SSTTdT

dQQQ

Heat flux:

Heat flux at

the surface

feedback term.

SSTobs= observations

dT

dQ Feedback coefficient

= -40W/m2/K

Fresh water flux:

1

13

1 )(

k

obsktso

S

SSSSeEMPEMP

Fresh water

budget at

the surface

Feedback term.

SSSobs= observations

Feedback parameter

= -167 mm/day

s

Sea Surface restoring