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Inverse modelling of methane sources and sinks using satellite observations

Inverse modelling of methane sources and sinks using satellite observations. Jan Fokke Meirink, Henk Eskes, Michiel van Weele, Albert Goede. Royal Netherlands Meteorological Institute (KNMI). Overview. EVERGREEN SCIAMACHY inverse modelling strategy first experiments.

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Inverse modelling of methane sources and sinks using satellite observations

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  1. Inverse modelling of methane sources and sinks using satellite observations Jan Fokke Meirink, Henk Eskes, Michiel van Weele, Albert Goede Royal Netherlands Meteorological Institute (KNMI)

  2. Overview • EVERGREEN • SCIAMACHY • inverse modelling strategy • first experiments

  3. EVERGREENEnVisat for Environmental Regulation of GREENhouse gases • EC 5th framework programme • Feb. 2003 – Feb. 2006 • Objective: use ENVISAT (SCIAMACHY and MIPAS) measurements for inverse modelling of GHG emissions • Partners: KNMI (NL, coordinator), Univ. Bremen (DE), Univ. Leicester (GB), Univ. Heidelberg (DE), NILU (NO), SRON (NL), MPI-BGC (DE), BIRA-IASB (BE), UPMC-SA (FR), RWE-Rheinbraun (DE), Univ. Liège (BE), EC-JRC-IES (IT) • website: http://www.knmi.nl/evergreen

  4. EVERGREEN: tasks • Retrieval and validation: CH4, CO, (CO2), O2 columns; clouds • Radiation budget modelling: use of measured trace gas distributions in radiative forcing calculations • (Inverse) modelling: CH4, CO, CO2 • emission inventory • (forward) model intercomparison (222Rn, SF6, ...) • inverse modelling

  5. SCIAMACHY on ENVISAT CO2 CO CH4

  6. SCIAMACHY measurements No useful retrievals yet: • calibration problems (mainly dark current correction) • ice layers on the detectors, channel 7 and 8 NIR retrieval quality will depend on: • albedo: over water low signal-to-noise ratio • solar zenith angle • clouds

  7. SCIAMACHY: example nadir measurements (simulated)

  8. Chemistry-transport model TM3 • horizontal resolution: 7.5x10 / 3.75x5 / 2.5x2.5 deg • vertical resolution: 19 / 31 layers up to 10 hPa • slopes scheme for advection • ECMWF meteorology • 37 tracers (22 transported) • CBM-4 scheme for NMHC chemistry • nudging at model top to climatology (O3) and UARS data (CH4) • single-tracer version with OH fields from full model

  9. Planned model setup in Evergreen • horizontal resolution: 2x3 deg • extension of model in vertical direction: use subset of ECMWF layers up to 0.1 hPa • nudging of CH4 to surface observations to have model reproduce measured NH-SH gradient • up-to-date emissions from WP 4100

  10. Inversion strategy • 4D-var method • adjoint model of TM3 CH4-only version has been developed • optimize surface fluxes and initial CH4 field • expected: in the beginning adjustments to CH4 field, later to surface fluxes • time frame: 1 week to 1 month

  11. 4D var (1)

  12. background error covariance observation operator state vector x = [c,f] observation error covariance observation 4D var (2) • cost function • model

  13. adjoint model 4D var (3) • gradient of the cost function

  14. Preconditioning • S diagonal matrix with standard deviations • LLTsymmetric matrix with correlations

  15. First experiments • First week of January 2000 • Sat.obs. taken from perturbed model run • Optimize emissions only • Background error covariance • Standard deviation: 50% of emission • Horizontal correlation function: Gaussian with length scale of 1000 km • Observation error covariance • Diagonal; standard deviation: 0.5% of column

  16. A priori emissions

  17. Perturbed run 50% enhanced emissions

  18. Effect on CH4 field after one week

  19. Pseudo satellite observations

  20. Optimized CH4 emissions

  21. Resulting CH4 field

  22. Setting obs to 2%

  23. Adding 0.5% noise to sat.data

  24. Summary • EU project EVERGREEN for emission estimates of CH4, CO, and possibly CO2, using satellite data. • SCIAMACHY has the potential of measuring CH4 and CO columns, but first some calibration problems have to be solved. • Inverse modelling of CH4 using 4D-var has been set up at KNMI and first experiments have been done.

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