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Interpretation of station data with an adjoint Model

Interpretation of station data with an adjoint Model. Maarten Krol (IMAU) Peter Bergamaschi (ISPRA) Jan Fokke Meierink, Henk Eskes (KNMI) Sander Houweling (SRON/IMAU). What is TM5?. Global model with zoom option Two-way nesting Mass-conserving / Positive

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Interpretation of station data with an adjoint Model

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  1. Interpretation of station data with an adjoint Model Maarten Krol (IMAU) Peter Bergamaschi (ISPRA) Jan Fokke Meierink, Henk Eskes (KNMI) Sander Houweling (SRON/IMAU)

  2. What is TM5? • Global model with zoom option • Two-way nesting • Mass-conserving / Positive • Atmospheric chemistry Applications • Off-line ECMWF • Flexible geometry

  3. What is TM5? 6x4 3x2 1x1

  4. Why an Adjoint TM5? • Concentrations on a station depend on emissions • Interesting quantity: dM(x,t)/dE(I,J,t’) • How does a ‘station’ concentration at t changes as a function of emissions in gridbox (I,J) at time t’? • Inverse problem: from measurements M (x,t) --> E(I,J,t’)

  5. Adjoint TM5 • dM(x, t)/dE(I,J) (constant emissions) can be calculated with the adjoint in one simulation • M0(x, t) = f(E0(I,J)) • M(x, t) = M0+dM(t)/dE(I,J)*(E(I,J)-E0(I,J)) • Only if the system is linear!

  6. Adjoint TM5 (4DVAR)

  7. Finokalia MINOS 2001 measurements Dirty Clean

  8. Finokalia • Integrations from M(t) back to july, 15. • Forcing at station rm(I,J,1) = rm(I,J,1) + f(t,t+dt) (during averaging period) • Adjoint chemistry • Adjoint emissions give analytically: dM(t)/dE(I,J)

  9. Clean

  10. Dirty

  11. Clean

  12. Dirty

  13. Clean

  14. Dirty

  15. Clean

  16. Dirty

  17. Prior MCF emission distribution

  18. Procedure • Minimise • With

  19. Negatives Emissions over sea Posterior MCF emissions: BETTER CONSTRAIN THE PROBLEM

  20. Conclusions • Emissions seem to come from regions around the black sea! • Results sensitive to prior information • Not surprising: 8 observations <==> 1300 unknowns • Emissions required: 10-30 gG/year • How to avoid negatives?

  21. Next Steps (to be done) • Prior Information • non-negative • full covariance matrix • Full 4Dvar, starting with obtained solution as starting guess emissions • Influence station sampling, BL scheme, …. • All observations separately (Movie)

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