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Funded Research

Improving and extending CMS land surface carbon flux products including estimates of uncertainties in fluxes and biomass

Collatz, George (Jim): NASA GSFC - retired (Project Lead)
Zeng, Fanwei: NASA GSFC / SSAI (Co-Investigator)

Project Funding: 2013 - 2016

NRA: 2013 NASA: Carbon Monitoring System   

Funded by NASA

This proposal addresses the Studies to improve the characterization and quantification of errors and uncertainties in existing and/or proposed NASA CMS products, including errors and uncertainties in the algorithms, models, and associated methodologies utilized in creating them; component of CMS call for proposals. Our team was originally funded in Phase I of the CMS project to provide land surface carbon fluxes (NPP/GPP, RH/RE, Fire from CASA-GFED3) for the period 2009-2010. We produced these products, evaluated them against other models and contributed to the interpretation of modeled atmospheric CO2 distributions produced by GSFC's GEOS-5 transport model and the source/sink distributions produced by JPL's atmospheric inverse model. Our data products are available on the CMS website. For Phase II, we did not seek funding support but contributed to the Pawson and Bowman projects as collaborators providing fluxes for 2011 and further evaluation of those. Our data products are well suited for use by other CMS projects because they are highly constrained by satellite observations and have a long history of evaluation by the atmospheric CO2 modeling community. There is the need for continued updates of these key land data products and for estimates of uncertainties, which were not previously supplied. For this proposed work we plan to produce land carbon fluxes for 2012 from CASA-GFED3 by the end of this calendar year. In subsequent years of the proposal we will introduce the new updated version of the model (CASA-GFED4) with improved physiological and fire parameterizations, improved burned area estimates including representation of smaller fires, and finer spatial resolution (1/4 degree) extending the time series into the future with a latency of ~5 months. We have begun preliminary uncertainty analyses of the CASA-GFED3 fluxes by first testing the sensitivity of the modeled fluxes to characteristic model parameters. From the sensitivity analyses we are selecting a number of key parameters and using published and expert opinion estimates of uncertainties in these parameters to estimate flux uncertainties using a Monte Carlo method. We will estimate uncertainties in the individual fluxes (NPP, RH, fires, NBP, GPP, RE) at monthly time steps for the entire period of the data set. The CMS atmospheric modeling groups for their estimates of overall uncertainties in surface carbon sources and sinks critically need quantified flux uncertainties. Our simulations also produce global biomass estimates at the model's native resolution with uncertainties. We plan to evaluate these estimates against others including the CMS Biomass products.


Wang, J. S., Kawa, S. R., Collatz, G. J., Sasakawa, M., Gatti, L. V., Machida, T., Liu, Y., Manyin, M. E. 2018. A global synthesis inversion analysis of recent variability in CO<sub>2</sub> fluxes using GOSAT and in situ observations. Atmospheric Chemistry and Physics. 18(15), 11097-11124. DOI: 10.5194/acp-18-11097-2018

Liu, J., Bowman, K. W., Lee, M., Henze, D. K., Bousserez, N., Brix, H., James Collatz, G., Menemenlis, D., Ott, L., Pawson, S., Jones, D., Nassar, R. 2014. Carbon monitoring system flux estimation and attribution: impact of ACOS-GOSAT XCO2 sampling on the inference of terrestrial biospheric sources and sinks. Tellus B: Chemical and Physical Meteorology. 66(1), 22486. DOI: 10.3402/tellusb.v66.22486

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude   --   (Ning Zeng, Fang Zhao, George James Collatz, Eugenia Kalnay, Ross Salawitch, Tristram O. West, Guanter Luiz, Ghassem Asrar)   [abstract]

More details may be found in the following project profile(s):