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A. David McGuire USGS / University of Alaska Fairbanks

A comparison of recent model- and inventory- based estimates of the continental-scale carbon balance of North America. A. David McGuire USGS / University of Alaska Fairbanks North American Carbon Program 3 rd All-Investigators Meeting New Orleans – 3 February 2011.

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A. David McGuire USGS / University of Alaska Fairbanks

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  1. A comparison of recent model- and inventory- based estimates of the continental-scale carbon balance of North America A. David McGuire USGS / University of Alaska Fairbanks North American Carbon Program 3rd All-Investigators Meeting New Orleans – 3 February 2011

  2. “Fast-Track” Analysis:Model– vs. Inventory– based Data ComparisonsA component of the North American Carbon Program’s Regional / Continental Interim Synthesis Activities • Organizing • Dave McGuire • Mac Post • Dan Hayes • Inventory-based data • Graham Stinson, Werner Kurz (Canada Forest Inventory) • Brian McConkey (Canada Cropland Inventory) • Linda Heath (U.S. Forest Inventory) • Tris West (U.S. Cropland Inventory) • Ben deJong (Mexico) • Model-data processing • Yaxing Wei • NACP Regional/Continental Interim Synthesis Participants • Data analysis • Dan Hayes • Dave Turner

  3. Introduction • Current understanding of state of the North American Carbon Cycle (e.g., SOCCR; King et al., 2007): • Magnitude of sink, trends, driving forces, uncertainty

  4. Introduction • Methodologies for assessing continental-scale carbon balance: • Inventory-based methods (forest stock changes, crop productivity, harvest and soil stocks, land use change) • Forward modeling: terrestrial biosphere process-based models • “top-down” observations with an Inverse approach via atmospheric transport modeling * Data and model results contributed to the NACP Regional / Continental Interim Synthesis activity

  5. Inventory Reporting Zones no data Canada(n=15) U.S.(n=49) Mexico(n=32)

  6. Inventory-data Analysis Conceptual diagram of the continental-scale carbon budget (including NEE) from the inventory-based approaches.

  7. Inventory-based NEE estimates FOREST LANDS CROPLAND “OTHER” LANDS TOTAL

  8. Inventory-based estimates Fate of Harvested (Forest & Crop) Carbon FOREST HARVEST CROP HARVEST TOTAL HARVEST

  9. Model (Forward and Inverse) Data & Methods n = 17 n = 7

  10. Model-data Processing * Distributing model output data variables across sector (Forestland, Cropland, and “Other”) within each reporting zone

  11. Model-data Processing

  12. Compare NEE by country / sector

  13. Compare NEE spatial patterns Mean average annual NEE (gC m-2 yr-1) for each reporting zone.

  14. Compare Component Flux Estimates

  15. Compare Component Flux Estimates

  16. Discussion • What does it all mean? • Lack of convergence between approaches • Different Approaches: • Strengths and weaknesses of each • Is our inventory approach (e.g. harvested product transfers and emissions) realistic? How can we reconcile with modeling approaches? • Inventory data gaps and uncertainties? • Uncertainties in the inverse approach: observation network, flux priors, transport models • Variability in the forward modeling approach: driver data, model formulations, processes / mechanisms simulated • Formal model inter-comparisons?

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