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Inversion of continuous data over Europe : a pseudo-data analysis.

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. How to assimilate daily measurements ?.

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Inversion of continuous data over Europe : a pseudo-data analysis.

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  1. 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

  2. How to assimilate daily measurements ? Schauinsland CO2 (ppm) high spatial resol. model daily time step inversion

  3. Inversion setup : Data PAL WES MHD CBW SCH HUN SAC PRS PUY CMN • Period :1 year = 2001 • Observations :daily modelled concentrations. EuropeanNEP fluxes from ORCHIDEE. 10 European stations AEROCARB data base : http://www.aerocarb.cnrs-gif.fr/database.html

  4. Transport model : LMDZ, zoom over Europe • 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

  5. Inversion setup : prior information • 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

  6. Spatial and temporal correlations « distance » correlations : extent of synoptic events L land/ocean : 1000/1500 km L 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

  7. Illustration of correlations Distance Climate x distance (November) Biomes x distance

  8. Technical aspects : • Use “retro-plume approach” (~ adjoint) to get • daily response functions for all pixels • 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 !!

  9. PSEUDO DATA : Perfect transport

  10. Annual error reduction maps : Distance correlations Climate correlations percentage 0 10 20 30

  11. Pixel resolution Prior (with TURC) ORCHIDEE (Truth) posterior correlation prior/poste : 0.69 / 0.79 4 gC/m²/day 0 SAC -6 2001 2001.25 2001.5 2001.75 2002 correlation prior/poste : 0.69 / 0.53 8 PRS 4 gC/m²/day 0 -4 2001 2001.25 2001.5 2001.75 2002

  12. Regional resolution Prior (with TURC) ORCHIDEE (Truth) posterior correlation prior/poste : 0.89 / 0.94 2 gC/m²/day 0 Western Europe -3 2001 2001.25 2001.5 2001.75 2002 correlation prior/poste : 0.55 / 0.77 1 0 gC/m²/day Mediterranean Europe -2 2001 2001.25 2001.75 2002 2001.5

  13. Residual : flux – seasonal flux NSD prior Correlation: prior vs. true (NSD true = 1) NSD posterior Correlation: posterior vs. true 1.8 0.8 0.6 1.4 0.4 0.2 1.0 residual correlation Normalised standard dev. 15 days 1 day 8 days 2.8 0.5 2.4 0.3 2.0 0.1 1.6 8 days 15 days 1 day Time smooth length

  14. PSEUDO DATA : Non-perfect transport

  15. Western Europe ORCHIDEE (Truth) Prior (with TURC) posterior 2 Flux (gC/m²/day) 0 -2 -4 2002 2001 2001.25 2001.5 2001.75 3.5 0.6 NSD prior Correlation prior 2.5 0.4 NSD posterior Correlation posterior residual correlation Normalised standard dev. 0.2 1.5 8 days 15 days 1 day Time smooth length

  16. 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

  17. Western Europe ORCHIDEE (Truth) Prior (with TURC) posterior 15 10 Flux (gC/m²/day) 5 0 -5 2002 2001 2001.25 2001.5 2001.75 8 0.2 6 0.1 4 NSD posterior Correlation posterior residual correlation Normalised standard dev. 0 NSD prior Correlation prior 2 -0.1 0 8 days 15 days 1 day Time smooth length

  18. Fit to observations 440 posterior prior Obs. CBW 400 360 CO2 (ppm) 2002 2001 2001.25 2001.5 2001.75 380 370 CMN 360 2002 2001 2001.25 2001.5 2001.75

  19. 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

  20. Flux correction : posterior - prior First inversion Updated inversion May November -160 -250 20 200 110 -70 (gC / m2 / month)

  21. Continuous European measurement sites Continuous sites AEROCARB data base : http://www.aerocarb.cnrs-gif.fr/database.html

  22. 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 !!

  23. Retro-plume approach : Station Zotino (Russia) October 2001 Latitude Latitude Longitude Longitude Day 1 Day 4

  24. Taylor diagram 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 Total Europe / Western Europe 3 2.5 Residual correlation 2 Normalised standard deviation 1.5 1 0.5 TRUTH 0 0 0.5 1 1.5 2 2.5 3 Normalised standard deviation

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