CarbonTracker-Lagrange (CT-L) is a new regional inverse modeling framework currently under development and designed for estimating North American greenhouse gas emissions and uptake fluxes. CT-L uses surface sensitivity footprints from Lagrangian Particle Dispersion Models driven by high-resolution meteorological simulations. Surface fluxes are optimized for consistency with a variety of in situ and remote sensing observations of CO₂ using Bayesian and geostatistical inverse modeling techniques. A beta footprint product is available for download now, and more products are coming soon.

Download CT-Lagrange Footprints

Inversion Software
Documentation and Download

Atmospheric Transport Model:

CT-L uses a high-resolution WRF-STILT atmospheric transport model customized for Lagrangian simulations (Nehrkorn et al., Meteorol. Atmos. Phys., 107, 2010). Species independent 10-day surface footprints are computed and stored for each measurement along with back-trajectories.

WRF domains used for CT-L footprint generation. Meteorological fields are currently available for 2004-2010.

Sensitivity to surface emissions and uptake fluxes for summer 2010 representing the combined footprints for continuous in situ and discrete (flask) CO₂ measurements that are linked to the WMO CO₂ calibration scale.

Optimization Framework:

CT-L uses an efficient inverse modeling framework described by Yadav and Michalak [Geoscientific Model Development, 6, 583-590, 2013] implemented at NOAA in python and modified to include boundary value optimization similar to the method of Lauvaux et al. [Atmospheric Chemistry and Physics, 12(1), 337-354, 2012]. The fast sparse-matrix algorithms enable ensembles of calculations to test sensitivity to data-weighting scenarios, mathematical construct(form of state vector; Bayesian versus geostatistical optimization), and prior information.

Acknowledgements:

Support for CT-L has been provided by the NOAA Climate Program Office’s Atmospheric Chemistry, Carbon Cycle, & Climate (AC4) Program and the NASA Carbon Monitoring System.

CT-L Modeling team:

• NOAA & CIRES: A. Andrews, K. Thoning, M. Trudeau, R. Draxler, A. Stein, L. Hu, L. Bruhwiler, J. Miller, H. Chen, C. Alden, K. Masarie, A. Karion
• AER, Inc.: J. Eluszkiewicz, T. Nehrkorn, M. Mountain
• Carnegie Institution for Science/Stanford: A. Michalak, V. Yadav, Mae Qui
• Colorado State University: C. O’Dell
• Harvard University: S. Wofsy, B. Xiang, S. Miller, J. Benmergui

CT-L Data Providers:

• NOAA Earth System Research Laboratory’s Global Monitoring Division
• Penn State University (K. Davis, S. Richardson, N. Miles)
• NCAR (B. Stephens)
• Oregon State University (B. Law, A. Schmidt)
• Lawrence Berkeley National Lab (M. Torn, S. Biraud, M. Fischer)
• Earth Networks (C. Sloop)
• Environment Canada (D. Worthy)
• Harvard University (S. Wofsy, J. W. Munger)
• U of Minnesota (T. Griffis)
• CalTech (D. Wunch, P. Wennberg; S. Newman) & JPL (G. Toon)
• GOSAT-ACOS team

Links:

• U.S. Potent GHG Tracker
• Hu et al, "Enhanced North American carbon uptake associated with El Niño"
• North American terrestrial CO2 fluxes between 2007 and 2015 derived from CarbonTracker- Lagrange
• Yadav and Michalak: http://www.geosci-model-dev.net/6/583/2013/gmd-6-583-2013.html
• Lauvaux et al.: http://www.atmos-chem-phys.net/12/337/2012/acp-12-337-2012.html
• Nehrkorn et al.: http://link.springer.com/article/10.1007%2Fs00703-010-0068-x