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TDI experiment with NIES model and interannually varying NCEP winds

TDI experiment with NIES model and interannually varying NCEP winds. S. Maksyutov, P.K. Patra and M. Ishizawa Jena; 13 May 2003. Objectives. Time-dependent inversion Study effect of meteorological fields on inversion Analyse climate impact on CO2 concentration anomaly

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TDI experiment with NIES model and interannually varying NCEP winds

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  1. TDI experiment with NIES model and interannually varying NCEP winds S. Maksyutov, P.K. Patra and M. Ishizawa Jena; 13 May 2003

  2. Objectives • Time-dependent inversion • Study effect of meteorological fields on inversion • Analyse climate impact on CO2 concentration anomaly • Link CO2 flux variability to ecosystem model simulations

  3. Experiments – Three transport options • ECMWF analysis for 1997 (cyclostationary) • NCEP reanalysis for 1997 (followed by 98,99) • NCEP reanalysis winds (interannually varying) Other Issues: • Fossil fuel emission trends: 1996-1999 (Marland et al., 2002) and 2000-2001 is extrapolated, spatial patterns for 90 and 95 are used

  4. Preprocessing NCEP winds • NCEP reanalysis (Period: 1988 to 2001), pressure level data at 2.5 deg resolution. Vertical winds are up to 100 mb originally. • Diagnostic vertical wind above 100 mb. Vertical motion along isentropic trajectories is assumed. w=(U*dTp/dx+V*dTp/dy)/(dTp/dp) • This simplified approach fails at the poles. Polar values are smoothed from vicinity (second row from the pole).

  5. TDI Setup • Basically the same as T3 L2 source code (Ft Collins meeting by K. Gurney et al) • Originally developed at CSIRO • Changes are made to ingest Green’s function matrices usingmultiple-year meteorology • Period of source estimation: 1988 – 2001 (after 3 years spin up time)

  6. CO2 Observation data • GLOBALVIEW (August 2002 release) • Maximum number of stations: 189 • Data period: Jan 1979 to Jan 2002 (2001 depleted) • Bare minimum modifications to R. Law’s program

  7. Transport model re-configuration for Earth Simulator • Parallelisation idea: array decomposition at tracer dimension (no reaction between tracers), rather than latitude bands etc. • Total number of pulses are: (22*12+4) per year; 14 years processed (88-01) • Single run uses 72 NEC-SX processors • each running 22 pulses (9 nodes on Earth Simulator) • simulating 6 years of monthly-pulses at once • Asynchronous meteorology (each process is allowed to run its own time); i.e., no communication between processes

  8. Other computer system issues • Virtual file system: • files are copied to each process’s virtual disk space at the job preparation stage • then disposed after run to disk or tape • process-specific input, output file extensions are added (style like .000, .001) • Job script limitations (limited to 256 explicit file declarations): • had to reduce the number of files used • we put the meteorological data for one month in one file

  9. Influence of Atmospheric transport on CO2 data inversionNumber of observations stations: 69 (55% real data in 1988-2001)

  10. Inversion results: fitting to the data

  11. Annual Mean Fluxes • reasonably good agreement • Case 1: NCEP-int closer to NCEP-97 than ECMWF-97 (constant offset: L-04, L-06, O-09) • Case 2: NCEP-97 and ECMWF-97 are different from NCEP-int (L-05, L-01) • -1998 emission – distributed evenly between tropical land areas

  12. Seasonal Cycles As it comes out of the inversion model calculation! Well produced for the well constrained regions

  13. Monthly Flux anomaly Noisy! Ln-01 & Ln-07 well correlated 1998 emission

  14. Comparison with T3L3 base case (L2 by David Baker)Number of observations stations: 76

  15. Annual Mean Fluxes Trouble with well constrained regions! Something is still missing?

  16. Average Seasonal Cycles Matches fairly well Within ~20%? (haven’t done that precisely) Reasons??

  17. Monthly Flux anomaly Too much variationStill compares quite well The 1998 emission peak gone missing

  18. Derived Flux and ENSO Index

  19. Future Outlook • High Resolution Inversion (53 regions) • Testing of different ecosystem model • Use ecosystem model output at high time resolution (daily? May be…)

  20. Conclusions • Three types of transport fields are used in interannual inversion which show good agreement • Some climate impact on CO2 emission can be studied; e.g 1998 Indonesian fire • Comparison with T3L2 tending to match • We wish to contribute to T3L3 by using a high resolution inverse model and/or with a different ecosystem model results

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