1. Cheas 2006 Meeting Marek Uliasz: Estimation of regional fluxes of CO 2 … Cheas 2006 Meeting Marek Uliasz: Estimation of regional fluxes of CO 2 …

2. = LI-820 sampling from 75m above ground on communication towers. = 40m Sylvania flux tower with high-quality standard gases. = 447m WLEF tower. LI-820, CMDL in situ and flask measurements. Problems of regional scale CO 2 flux estimations by inversions: - limited domain - domain coverage by tower data

3. ASSUMPTION: SiB-RAMS is capable to realistically reproduce diurnal cycle and spatial distribution of CO 2 (assimilation and respiration) fluxes. Therefore, observation data are used to correct those fluxes for errors in atmospheric transport. ASSUMPTION: SiB-RAMS is capable to realistically reproduce diurnal cycle and spatial distribution of CO 2 (assimilation and respiration) fluxes. Therefore, observation data are used to correct those fluxes for errors in atmospheric transport.

4. CO 2 flux respiration & assimilation fluxes simulated by SiB-RAMS respiration & assimilation fluxes simulated by SiB-RAMS time independent corrections to be estimated from concentration data for each inversion cycle time independent corrections to be estimated from concentration data for each inversion cycle

5. CO 2 flux respiration & assimilation fluxes simulated by SiB-RAMS respiration & assimilation fluxes simulated by SiB-RAMS time independent corrections to be estimated from concentration data for each inversion cycle time independent corrections to be estimated from concentration data for each inversion cycle

6. SiB-RAMS LPDM meteo fields CO 2 fields and fluxes influence functions influence functions inversion techniques inversion techniques Bayesian MLEF CO 2 observations corrected CO 2 fluxes typically run with several nested grids covering a continental scale run on any subdomain extracted from SiB-RAMS corrected within each inversion cycle MODELING FRAMEWORK

7. surface fluxes initial concentration inflow fluxes concentration sample Representation of atmospheric concentration sample with the aid of influence function, C *, derived from a backward in time run of the LPDM.

8. [10 -10 x sm -3 ]

16. sunrise

17. [10 -10 x sm -3 ]

21. influence functions for 396m WLEF tower integrated over unit flux for 7x10 day inversion cycles

22. C – observed concentration k – index over observations (sampling times and towers) i – index over source grid cell (both respiration & assimilation fluxes) C * R.A – influence function integrated with respiration & assimilation fluxes C IN – background concentration combining effect of the flow across lateral boundaries and initial concentration at the cycle start “beta’s” – corrections to be estimated Implementation for a given inversion cycle

23. SiB-RAMS simulation: 75 days starting on April 25 th, 2004 on two nested grids (10 km grid spacing on the finer grid) INVERSION EXPERIMENTS

24. SiB-RAMS simulation: 75 days starting on April 25 th, 2004 on two nested grids (10 km grid spacing on the finer grid) INVERSION EXPERIMENTS LPDM and influence function domain: 600x600km centered at WLEF tower

25. SiB-RAMS simulation: 75 days starting on April 25 th, 2004 on two nested grids (10 km grid spacing on the finer grid) INVERSION EXPERIMENTS LPDM and influence function domain: 600x600km centered at WLEF tower Concentration pseudo-data were generated for WLEF and the ring of towers from SiB-RAMS assimilation and respiration fluxes using correction values of 1

26. SiB-RAMS simulation: 75 days starting on April 25 th, 2004 on two nested grids (10 km grid spacing on the finer grid) INVERSION EXPERIMENTS LPDM and influence function domain: 600x600km centered at WLEF tower Concentration pseudo-data were generated for WLEF and the ring of towers from SiB-RAMS assimilation and respiration fluxes using correction values of 1 Model-data mismatch error was assumed to be higher for lower towers: 1 ppm for towers>100m, 1.5 ppm for towers > 50m, and 3 ppm for towers < 50m and very high values for short towers during nighttime

27. SiB-RAMS simulation: 75 days starting on April 25 th, 2004 on two nested grids (10 km grid spacing on the finer grid) INVERSION EXPERIMENTS LPDM and influence function domain: 600x600km centered at WLEF tower Concentration pseudo-data were generated for WLEF and the ring of towers from SiB-RAMS assimilation and respiration fluxes using correction values of 1 Model-data mismatch error was assumed to be higher for lower towers: 1 ppm for towers>100m, 1.5 ppm for towers > 50m, and 3 ppm for towers < 50m and very high values for short towers during nighttime 7 x 10 day inversion cycles were performed using Bayesian inversion technique with concentration pseudo data (initial corrections = 0.75 and their standard deviations = 0.1)

28. source area: 20x20 km NW of WLEF 10 day (cycle) average

29. 24 hour average source area: 20x20 km NW of WLEF

30. hourly average source area: 20x20 km NW of WLEF

31. NEE uncertainty reduction [umol/m 2 /s]cycle #1

32. NEE uncertainty reduction [umol/m 2 /s]cycle #2

33. NEE uncertainty reduction [umol/m 2 /s]cycle #3

34. NEE uncertainty reduction [umol/m 2 /s]cycle #4

35. NEE uncertainty reduction [umol/m 2 /s]cycle #5

36. NEE uncertainty reduction [umol/m 2 /s]cycle #6

37. NEE uncertainty reduction [umol/m 2 /s]cycle #7

38. NEE UNCERTAINTY: INITIAL, WLEF, RING aggregation of source areas

39. NEE UNCERTAINTY: INITIAL, WLEF, RING aggregation of source areas

40. NEE UNCERTAINTY: INITIAL, WLEF, RING aggregation of source areas

41. C – observed concentration k – index over observations (sampling times and towers) i – index over source grid cell (both respiration & assimilation fluxes) C * R.A – influence function integrated with respiration & assimilation fluxes C IN – background concentration combining effect of the flow across lateral boundaries and initial concentration at the cycle start “beta’s” – corrections to be estimated Implementation for a given inversion cycle

42. C – observed concentration k – index over observations (sampling times and towers) i – index over source grid cell (both respiration & assimilation fluxes) l - index over time intervals C * R.A – influence function integrated with respiration & assimilation fluxes C IN – background concentration combining effect of the flow across lateral boundaries and initial concentration at the cycle start “beta’s” – corrections to be estimated Implementation for a given inversion cycle

43.  Pseudo-data experiments  The ring of towers (Bayesian, MLEF)  US continental scale (MLEF)  Real data experiments  The ring of towers (Bayesian)  Pseudo-data experiments  The ring of towers (Bayesian, MLEF)  US continental scale (MLEF)  Real data experiments  The ring of towers (Bayesian) Inversion experiments: new SiB-RAMS simulations

44.  Influence functions to be integrated with user provided CO2 fluxes RUC-LPDM: