Inversion of continuous data over Europe : a pseudo-data analysis. C. Carouge and P. Peylin ; P....

Inversion of continuous data over Europe : a pseudo-data

analysis.

C. Carouge and

P. Peylin ; P. Bousquet ; P. Ciais ; P. Rayner Laboratoire des Sciences du Climat et de l’Environnement

Acknowledgement : all experimentalists from Aerocarb project

high spatial resol. modeldaily time step inversion

How to assimilate daily measurements ?

SchauinslandC

O2

(ppm

)

• Period : 1 year = 2001

• Observations : daily modelled concentrations. European NEP fluxes from ORCHIDEE. 10 European stations

Inversion setup : Data

MHD

SAC

PUYPRSSCH

CBWWES

PAL

HUN

CMN

AEROCARB data base : http://www.aerocarb.cnrs-gif.fr/database.html

Transport model : LMDZ, zoom over Europe

• Nudged on ECMWF winds• 192 x 146 and 19 vertical levels - 0.5 x 0.5 degrees in the zoom - 4 x 4 degrees at the lowest resolution

• Fluxes : - Europe & North east Atlantic : each pixel / daily

- Elsewhere : subcontinental regions / monthly

• Prior : Fluxes : Europe : 0 fluxes OR TURC NEP fluxes

Elsewhere : 0 fluxes

Errors : 1 GtC/year over Europe

0.5 GtC/year over north east Atlantic

• Correlations : spatial and temporal correlations between European / N.Atlantic pixels

Inversion setup : prior information

Spatial and temporal correlations

L

jicedisjiCor

),( tan exp),(

« distance » correlations : extent of synoptic events

L land/ocean : 1000/1500 kmL temporal : 10 days

« climate » correlations : structure of synoptic events

Monthly correlations between daily NEP fluxes from ORCHIDEE X distance correlations

« biome » correlations : structure of vegetation types

Linear relation between predominant biomes of ORCHIDEE X distance correlations

Distance

Illustration of correlations

Climate x distance(November) Biomes x distance

Technical aspects :

• Synthesis inversion to get posterior errors :

Sequential approach with overlap : 11 * 2 months inversions

Still 7000*60 unknowns covariance matrix of ~ 400,000 x 400,000 !!

• Use “retro-plume approach” (~ adjoint) to get daily response functions for all pixels

Huge memory size problems !

PSEUDO DATA :

Perfect transport

Annual error reduction maps :

Distance correlations

Climate correlations

0 10 20 30 percentage

2001 2001.52001.25 20022001.75

2001.252001 2001.752001.5 2002

PRS

SAC

correlation prior/poste : 0.69 / 0.79


Prior(with TURC) posterior

ORCHIDEE(Truth)

0

4

8

-4

-6

0

4

gC/m

²/da

ygC

/m²/

day

Pixel resolution

Mediterranean Europe

Western Europe


ORCHIDEE(Truth)

2001 2001.52001.25 20022001.75

2001 2001.52001.25 20022001.75

2

0

1

-3

-2

0

gC/m

²/da

ygC

/m²/

day

Regional resolution



0.5

0.1

0.32.4

2.8

2.0

1.6

1.4

1.00.2

0.4

0.6

0.8 1.8 Norm

alised standard dev.re

sidu

al c

orre

latio

nCorrelation: prior vs. true

Correlation: posterior vs. true

NSD prior

NSD posterior

(NSD true = 1)

1 day 8 days 15 days

1 day 8 days 15 days

Time smooth length

Residual : flux – seasonal flux

PSEUDO DATA :

Non-perfect transport

Western Europe

0

2

-2

2.5

-4

0.6

1.5

0.4

0.2

3.5

No

rma

lised sta

nd

ard de

v.re

sid

ual c

orr

ela

tion

2001 2001.52001.25 20022001.75

Flu

x(g

C/m

²/d

ay)

Correlation posterior

Correlation prior NSD prior

NSD posterior


ORCHIDEE(Truth)

1 day 8 days 15 daysTime smooth length

Actual data : new setup

• Observations : daytime averaged

• Fluxes : - Europe & North east Atlantic : each pixel / daily

- Elsewhere : subcontinental regions / monthly

• Prior : Fluxes : pre-optimised monthly fluxes

Errors : 1 GtC/year over Europe

0.5 GtC/year over north east Atlantic

tiny on other regions

No

rma

lised sta

nd

ard de

v.re

sid

ual c

orr

ela

tion

2001 2001.52001.25 20022001.75

Flu

x(g

C/m

²/d

ay)

Prior(with TURC)

ORCHIDEE(Truth)

1 day 8 days 15 daysTime smooth length

Western Europeposterior

15

10

5

0

-5

0.2

0.1

0

-0.1 0

2

4

6

8

Correlation posterior

Correlation prior NSD prior

NSD posterior

Fit to observations

440

400

360

360

370

380

2001 2001.52001.25 20022001.75

2001 2001.52001.25 20022001.75

CO

2 (

ppm

)

prior Obs.posterior

CBW

CMN

Conclusions …

• 1 year of pixel inversion is technically possible

• only W. Europe can be really resolved with current network

• Transport uncertainties are critical

… and Perspectives

• data selection

•

May

November

Flux correction : posterior - prior

-250 -160 -70 20 110 200(gC / m2 / month)

First inversion Updated inversion

AEROCARB data base : http://www.aerocarb.cnrs-gif.fr/database.html

Continuous sites

Continuous European measurement sites

Technical aspects :

• Synthesis inversion to get posterior errors :

Sequential approach with overlap : 11 * 2 months inversions

Still 7000*60 unknowns covariance matrix of ~ 400,000 x 400,000 !!

• Use “retro-plume approach” (~ adjoint) to get daily response functions for all pixels

Huge memory size problems !

• Two steps inversion : - 1st : standard monthly Fluxes + Globalview data- 2nd : daily fluxes using the 1st step estimated fluxes..

Retro-plume approach :

Day 1 Day 4

Station Zotino (Russia) October 2001

Longitude Longitude

Lat

itu

de

Lat

itu

de

Taylor diagram

Residual correlation

Total Europe / Western Europe TP: TURC fluxes

1: no correlation

2: prior 0 / distance

3: prior 0 / climate x distance

4/5/6: prior Turc / distance

7: prior Turc / climate x distance

8: prior Turc / climate

30 0.5 1 1.5 2 2.5

3

0

0.5

1

1.5

2

2.5

Normalised standard deviation

No

rma

lise

d st

an

dar

d d

evi

atio

n

TRUTH

Inversion of continuous data over Europe : a pseudo-data analysis. C. Carouge and P. Peylin ; P....

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