estimation of daily co 2 fluxes over europe by inversion of atmospheric continuous data n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data PowerPoint Presentation
Download Presentation
Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data

Loading in 2 Seconds...

play fullscreen
1 / 25

Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data - PowerPoint PPT Presentation


  • 78 Views
  • Uploaded on

Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data. 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.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data' - sol


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
estimation of daily co 2 fluxes over europe by inversion of atmospheric continuous data

Estimation of daily CO2 fluxes over Europe by inversion of atmospheric continuous data

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

slide2

How to assimilate daily measurements ?

Schauinsland

CO2 (ppm)

high spatial resol. Model

daily time step inversion

slide3

Inversion setup

  • Period :1 year = 2001
  • Observations :10 European stations, daily averaged data
  • Transport model :LMDZ, zoom over Europe
  • Fluxes :- Europe & North east Atlantic : each pixel / daily
  • - Elsewhere : subcontinental regions / monthly
  • Prior :Fluxes : optimised monthly fluxes
  • Errors : 1 GtC/year over Europe
  • 0.5 GtC/year over north east Atlantic
  • tiny on other regions
  • Correlations :spatial and temporal variable correlationsbetween European pixels
slide4

Continuous European measurement sites

Continuous sites

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

slide5

Inversion setup

  • Period :1 year = 2001
  • Observations :10 European stations,daily averaged data
  • Transport model :LMDZ, zoom over Europe
  • Fluxes :- Europe & North east Atlantic : each pixel / daily
  • - Elsewhere : subcontinental regions / monthly
  • Prior :Fluxes : optimised monthly fluxes
  • Errors : 1 GtC/year over Europe
  • 0.5 GtC/year over north east Atlantic
  • tiny on other regions
  • Correlations :spatial and temporal variable correlationsbetween European pixels
slide6

Transport model

  • 192 x 146 and 19 vertical levels-0.5 x 0.5 degrees in the zoom
  • - 4 x 4 degrees at the lowest resolution
  • Nudged on ECMWF winds
slide7

Inversion setup

  • Period :1 year = 2001
  • Observations :10 European stations,daily averaged data
  • Transport model :LMDZ, zoom over Europe
  • 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
  • Correlations :spatial and temporal correlations between European / N.Atlantic pixels
slide8

Spatial and temporal correlations

Based on correlation lengths:

Distance(i,j) : distance in space or time between 2 fluxes i, j

  • L spatial : 500 - 800 km
  • L temporal : 5 – 15 days
slide9

Technical aspects :

  • Use “retro-plume approach” (~ adjoint) to get daily response functions for all pixels
  • Two steps inversion : - 1st : standard monthly Fluxes + Globalview data- 2nd : daily fluxes using the 1st step estimated fluxes..
  • Synthesis inversion to get posterior errors :

Huge memory size problems !

Sequential approach with overlap :

11 * 2 months inversions

Still 7000*60 unknowns

covariance matrix of ~ 400,000 x 400,000 !!

slide10

FIRST RESULTS

( Still preliminary)

slide11

Two different inversions

First inversion

  • 10 sites : Cabauw tower at 120m and 200m
  • Data : full daily mean
  • Data-error : stdev of hourly measurements
  • Time correlation length : 5 days
  • Spatial correlation lengths : 500/800 Km for land/ocean

Updated inversion

  • 9 sites : Cabauw tower at 200 m + data-error x 3 in winter
  • Data : daytime-only mean
  • Time correlation : 15 days
slide12

Fit to the stations : Westerland

Observations + error bars

Posterior

Prior

16/01

22/03

27/05

3/08

22/10

15/12

(Days)

slide13

Fit to the stations : Monte Cimone

Observations + error bars

Posterior

Prior

16/01

22/03

27/05

3/08

22/10

15/12

(Days)

slide14

Aerocarb project : Forward simulation with REMOD model

Diurnal cycle

At

Monte-Cimone

“Proper”

vertical level

(appropriated

in winter)

Need to use different levels depending on the season

slide15

Fit to the stations : Schauinsland

Observations + error bars

Posterior

Prior

16/01

22/03

3/08

22/10

15/12

27/05

(Days)

slide16

Fit to the stations : Cabauw (200 m)

Observations + error bars

Posterior

Prior

16/01

22/03

3/08

22/10

15/12

27/05

(Days)

slide17

Flux correction : posterior - prior

First inversion

Updated inversion

May

November

-160

-250

20

200

110

-70

(gC / m2 / month)

slide18

Total flux over Europe

First inversion

Updated inversion

fluxes (gC/day)

02/10

16/01

30/06

08/04

15/12

(Days)

slide19

Error Reduction

30

First inversion

25

20

15

10

5

0

LAND

OCEAN

Error Reduction (%)

Updated inversion

16/01

3/08

22/10

27/05

15/12

22/03

(Days)

slide21

Impact of spatial correlation length

Correlation = 300 km

Correlation = 2000 km

Posterior

-

Prior

(GtC/m²/month)

-25

0

50

100

Error Reduction

(%)

0

6

12

18

24

30

slide22

Conclusions …

  • First daily inversion over a full year with real continuous data and flux error correlations !
  • Spatial / Temporal patterns of fluxes critically depend on flux error correlations & error observations !
  • Flux corrections are still a bit high…

… and Perspectives

  • Comparaison with flux tower data / Bio. model
  • Define spatial correlations from biogeochemical model
  • Use improved prior fossil emissions
  • Use new LMDz version with 38 vertical levels
  • Integrated carbon assimilation system
slide24

30

LAND

OCEAN

25

20

15

10

5

0

16/01

22/10

15/12

27/05

3/08

22/03

(Days)

Total fluxes and error reduction

European NEP

North east Atlantic flux

Posterior flux

Prior flux

16/01

22/03

3/08

22/10

15/12

16/01

22/03

3/08

22/10

15/12

27/05

27/05

(Days)

(Days)

Error reduction (%)

slide25

Prior Fluxes

-20

160

80

0

gC/m²/month