1. Objective –Attempt to utilize flux tower records to evaluate the validity of continental flux estimates submitted to the regional interim synthesis activity. Methods (only partly completed) –Compare flux tower records to extracts from regional model runs, and to site-level model runs, with special attention to models run at both regional and site level. –Evaluate seasonal and interannual patterns, and mean bias. –Consider NEE, R and GPP. –Draw conclusions re: regional model performance. Diagnose causes of discrepancies. Joint Site-Regional Analysis Brett Raczka & Ken Davis, Penn State University May 15, 2009

2. Joint Site-Regional Analysis Brett Raczka & Ken Davis, Penn State University Conclusions to date: Regional model NEE output presents a systematic positive bias as compared to site level runs Site level model runs produce higher annual NEE variability (sigma) than regional runs, more representative of observed annual NEE Site level annual NEE produce higher correlation (R) to observed annual NEE than regional model runs CLM-CN, CLM-CASA, CASA-GFED consistently ranked highest among model skill statistics for regional runs ECOSYS, CanIBIS consistently ranked highest “ “ for site level runs

3. Future work: Add additional sites and models (cutoff date?) Take comments from community and modify analyses Enlist help from the I-synthesis community in understanding the causes of observed model behaviors Expand analyses to the seasonal cycle, and R and GPP Publish results Possibly contribute some portion of the site analyses to site-only papers. Joint Site-Regional Analysis Brett Raczka & Ken Davis, Penn State University

4. Interim Synthesis: Inter-annual NEE Point #1: Systematic difference between site and regional extract model runs (DLEM, ORCHIDEE & SIB were only models run in both modes) -Regional model runs for DLEM & ORCHIDEE present a consistent positive bias compared to site model runs for DLEM & ORCHIDEE -Source(s) of Annual NEE difference? - Different driver (met) data - Different site characteristics (soil or vegetation) - Equilibrium?, Regional model averaging Brett Raczka & Ken Davis, Penn State University Carbon Source Carbon Sink Carbon Source

5. Interim Synthesis: Inter-annual NEE Correlation Coefficient (R) Point #2: For regional model runs R has wide spread i.e. R values distributed across -1 to 1 across all sites and models (1 st figure) Point #3: For site model runs R has considerable spread as well, but there are exceptions: Mer (Peatland) UMB (DBF) Me2 (Pond. Pine) –anticorrelated Obs (Old Black Spruce) (2 nd Fig.) Brett Raczka & Ken Davis, Penn State University Regional Model Run Site Model Run

6. Interim Synthesis: Inter-annual NEE σ observations vs. σ model Point #4: For regional model runs, in general: σ obs >> σ model, eg: Let (Grass), Ca1 (ENF), Ne3 Corn/Soy (1 st Figure) Point #5: For site model runs, in general: σ obs ~ σ model (2 nd Figure) Why? - Does regional averaging reduce variability either for NEE or driver data input? -Reminiscent of large variability for atmospheric inversions compared to forward model runs over continent Brett Raczka & Ken Davis, Penn State University Regional Model Run Site Model Run

7. Interim Synthesis: Inter-annual NEE RMSD (centered pattern difference) Point #6: For regional model runs, no site-model combination that performed ‘well’ i.e. small RMSD. Inter-annual pattern not being captured (1 st figure) Point #7: For site model runs, several sites show small RMSD, eg. UMB, Mer, Obs & Ho1. (2 nd figure) Not consistent across PFT however. Brett Raczka & Ken Davis, Penn State University Regional Model Run Site Model Run

8. Interim Synthesis: Inter-annual NEE Overall Model Rankings Ranking Criteria: 1)Bias (Observed mean - model mean) 2)Total RMSD (Includes both bias and centered RMSD) 3)R (Correlation Coefficient) Two methods to rank: 1)Based on average statistic value across all sites 2)Based on average ranking value across all sites Brett Raczka & Ken Davis, Penn State University Regional Model Runs

9. Interim Synthesis: Inter-annual NEE Brett Raczka & Ken Davis, Penn State University Regional Model Runs

10. Interim Synthesis: Inter-annual NEE Brett Raczka & Ken Davis, Penn State University Site Model Runs

11. Interim Synthesis: Inter-annual NEE Brett Raczka & Ken Davis, Penn State University Site Model Runs