Project Funding: 2015 - 2018

NRA: 2014 NASA: OCO-2 Science Team for the OCO-2 Mission   

Funded by NASA

Abstract:
We propose to perform inverse modeling of OCO-2 data to obtain monthly gridded maps of carbon sources and sinks by assimilating both XCO2 and Solar-induced fluorescence (SIF) observations into SiB4. Under previous NASA support, we have demonstrated that SiB4 can skillfully predict Gross Primary Production (GPP), ecosystem respiration (RESP), above-ground biomass, and top-of-the-atmosphere SIF. We will use SiB4 plus published data sets for anthropogenic CO2 emissions, air-sea gas exchange, and biomass burning to drive global simulations of XCO2 using the GEOS-Chem atmospheric transport model. We will sample the simulated fields at the times and places observed by the satellite instruments to obtain error vectors. We will then use a Bayesian inversion to optimize parameters in SiB4 that control the time mean and seasonal cycles of GPP and RESP using a spectral decomposition of the component fluxes. We have demonstrated the power of this innovative approach using flux tower data from a range of ecosystems around the world. We will combine SIF data from OCO-2, GOSAT, and the Global Ozone Mapping Experiment (GOME) to constrain GPP, and use the OCO-2 retrievals of XCO2 one year at a time to constrain the spectral parameters. We will evaluate uncertainty in our gridded carbon flux product using both the output from the atmospheric CO2 inversions and by direct comparison of ancillary model outputs (e.g., biomass, LAI/fPAR, and in-situ CO2) to other NASA data products. In addition to our inversion, the flux priors and uncertainties we generate will be optimized by the CMS Flux Product Team to produce an alternate set of flux estimates. Forward model and both versions (CSU and CMS) of our optimized flux and uncertainty products we obtain will be accessible to the scientific community through the CMS data system as well as a NASA Earth Science portal.

Publications:

Crowell, S., Baker, D., Schuh, A., Basu, S., Jacobson, A. R., Chevallier, F., Liu, J., Deng, F., Feng, L., McKain, K., Chatterjee, A., Miller, J. B., Stephens, B. B., Eldering, A., Crisp, D., Schimel, D., Nassar, R., O'Dell, C. W., Oda, T., Sweeney, C., Palmer, P. I., Jones, D. B. A. 2019. The 2015-2016 carbon cycle as seen from OCO-2 and the global in situ network. Atmospheric Chemistry and Physics. 19(15), 9797-9831. DOI: 10.5194/acp-19-9797-2019

Haynes, K. D., Baker, I. T., Denning, A. S., Stockli, R., Schaefer, K., Lokupitiya, E. Y., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: 1. Implementation in the Simple Biosphere Model (SiB4). Journal of Advances in Modeling Earth Systems. 11(12), 4423-4439. DOI: 10.1029/2018MS001540

Haynes, K. D., Baker, I. T., Denning, A. S., Wolf, S., Wohlfahrt, G., Kiely, G., Minaya, R. C., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling. Journal of Advances in Modeling Earth Systems. 11(12), 4440-4465. DOI: 10.1029/2018MS001541

Haynes, K., I. Baker, and S. Denning. 2020. Simple Biosphere Model version 4.2 (SiB4) technical description. Mountain Scholar, Colorado State University, Fort Collins, CO, USA. https://hdl.handle.net/10217/200691