Presentation is loading. Please wait.

Presentation is loading. Please wait.

Resolving CO 2 Flux Estimates from Atmospheric Inversions and Inventories in the Mid-Continent Region Stephen M. Ogle 1, Andrew Schuh 1, Dan Cooley 1,

Similar presentations


Presentation on theme: "Resolving CO 2 Flux Estimates from Atmospheric Inversions and Inventories in the Mid-Continent Region Stephen M. Ogle 1, Andrew Schuh 1, Dan Cooley 1,"— Presentation transcript:

1 Resolving CO 2 Flux Estimates from Atmospheric Inversions and Inventories in the Mid-Continent Region Stephen M. Ogle 1, Andrew Schuh 1, Dan Cooley 1, Scott Denning 1, Kenneth Davis 2, Tristram West 3, and F. Jay Breidt 1 Other contributors: A. Andrews, K. Gurney, L. Heath, K. Paustian, P. Tans, A. Michalak, C. Potter, C. Tonitto, A. Jacobsen Data Support: Bob Cook (MAST-DC) 1 Colorado State University, 2 Pennsylvania State University, 3 Oak Ridge National Laboratories

2 C CO 2 C Main Goal of MCI Synthesis Compare and reconcile CO 2 fluxes from inventories and atmospheric inversions, to the extent possible, and evaluate underlying mechanisms driving the fluxes Compare and reconcile CO 2 fluxes from inventories and atmospheric inversions, to the extent possible, and evaluate underlying mechanisms driving the fluxes Atmospheric Inversions Inventories

3 MCI Interim Synthesis Initial comparisons of inversions and inventory with pre-MCI Campaign data from Initial comparisons of inversions and inventory with pre-MCI Campaign data from Benchmark for campaign Benchmark for campaign Analyze the underlying sources of difference between inversion and inventories Analyze the underlying sources of difference between inversion and inventories Expectations for Comparisons Expectations for Comparisons

4 Regional Totals for CO 2 Flux

5 JENA Inversion JENA Inversion JENA Inversion Large scale global inversion (4 degree x 5 degree pixels) Large scale global inversion (4 degree x 5 degree pixels) Uses hourly and flask (weekly) data Uses hourly and flask (weekly) data Prior constraints via `statistical flux model' setting spatial/temporal correlations and weighting Prior constraints via `statistical flux model' setting spatial/temporal correlations and weighting Inversion results courtesy of : Christian Rödenbeck (MPI BCG)

6 CarbonTracker Inversion Carbon Tracker Carbon Tracker Nested global inversion (22 global regions subset by 19 Olson ecosystem types) Nested global inversion (22 global regions subset by 19 Olson ecosystem types) Uses hourly and flask (weekly) data Uses hourly and flask (weekly) data Ensemble Kalman Filter is used to ‘scale’ a prior estimate of CASA NEE over these inversion regions on weekly timestep Ensemble Kalman Filter is used to ‘scale’ a prior estimate of CASA NEE over these inversion regions on weekly timestep Inversion results courtesy of : Andy Jacobsen (NOAA)

7 Correlation? - Inventory vs. Inversion JENA Inversion CarbonTracker Inversion

8 Differences between Inversion and Inventory JENA Inversion CarbonTracker Inversion Red implies a larger sink in the inventory data and blue implies a larger sink in the inversion.

9 Differences vs. Soil Carbon Change JENA Inversion CarbonTracker Inversion

10 Difference vs. Harvest Carbon JENA Inversion CarbonTracker Inversion

11 Pre-Campaign Observations

12 MCI Campaign Observations

13 Expectation for Synthesis Expectation: More observations will allow inversions to capture the apparent sink associated with the harvest C signal in MCI Expectation: More observations will allow inversions to capture the apparent sink associated with the harvest C signal in MCI Higher resolution REGIONAL inversions! Higher resolution REGIONAL inversions! Alternative: The inventory does not accurately represent the CO 2 fluxes in the region and the apparent sink Alternative: The inventory does not accurately represent the CO 2 fluxes in the region and the apparent sink Further evaluate lateral transport out of region Further evaluate lateral transport out of region Improve ability of inventories to capture weather related impacts on CO 2 fluxes Improve ability of inventories to capture weather related impacts on CO 2 fluxes

14 Ongoing Research Reconcile inversions and inventories, providing estimates and uncertainties Reconcile inversions and inventories, providing estimates and uncertainties Further testing with the inversions using inventory data as priors Further testing with the inversions using inventory data as priors Re-evaluate underlying mechanisms driving CO 2 flux in region Re-evaluate underlying mechanisms driving CO 2 flux in region


Download ppt "Resolving CO 2 Flux Estimates from Atmospheric Inversions and Inventories in the Mid-Continent Region Stephen M. Ogle 1, Andrew Schuh 1, Dan Cooley 1,"

Similar presentations


Ads by Google