1. Biospheric Models as Priors Deborah Huntzinger, U. Michigan

2. Synthesis Bayesian Inversion Inversion Carbon Budget 

3. Inversion Carbon Budget  Geostatistical Inversion Model (GIM)

4. Inversion Carbon Budget  Geostatistical Inversion Model (GIM)

5.  Data-driven approach eliminating use of explicit prior estimates  Takes advantage of spatial autocorrelation in flux distribution  Incorporates auxiliary variables related to flux processes in a manner analogous to multi-linear regression  Objective function and flux estimates: Deterministic component Stochastic component Geostatistical Inversion Model (GIM)

6. Global GIM CO 2 Flux Estimation S. Gourdji January 2000 Gourdji, Mueller, Schaefer, Michalak (JGR 2008) Mueller, Gourdji, Michalak (JGR 2008) Estimate global monthly CO 2 fluxes at 3.75°x5° for 1997 to 2001 using:  CO 2 flask data from NOAA-ESRL network  TM3 atmospheric transport model  Auxiliary environmental data

7. Mueller et al. (JGR, 2008) Global GIM CO 2 Flux Estimation

8.  1°x1° North American fluxes estimated for 2004 and 2006 using continuous & weekly flask atmospheric measurements, a Lagrangian atmospheric particle-tracking model (STILT), and high-resolution meteorology (WRF) T. Nehrkorn North American GIM CO 2 Flux Estimates Sharon Gourdji, U. Michigan

9. North American GIM CO 2 Flux Estimates Sharon Gourdji, U. Michigan

10. North American GIM CO 2 Flux Estimates Sharon Gourdji, U. Michigan

11. GIM Scalability