Ott, Lesley: NASA GSFC GMAO (Project Lead)
Chatterjee, Abhishek: NASA JPL (Co-Investigator)
Gregg, Watson: NASA GSFC (Co-Investigator)
Kawa, Stephan (Randy): NASA GSFC (Co-Investigator)
Oda, Tomohiro (Tom): USRA (Co-Investigator)
Pawson, Steven: NASA GSFC GMAO (Co-Investigator)
Poulter, Benjamin (Ben): NASA GSFC (Co-Investigator)
Rousseaux, Cecile: NASA GSFC (Co-Investigator)
Weir, Brad: NASA GSFC GMAO / GESTAR USRA (Co-Investigator)
Collatz, George (Jim): NASA GSFC - retired (Collaborator)
Denning, Scott: Colorado State University (Collaborator)
Hurtt, George: University of Maryland (Collaborator)
Randerson, James (Jim): University Of California, Irvine (Collaborator)
Román, Miguel: NASA GSFC / USRA (Collaborator)
Balashov, Nikolay: NASA GSFC / ESSIC UMD (Post-Doc)
Project Funding:
2017 - 2020
NRA: 2016 NASA: Carbon Monitoring System
Funded by NASA
Abstract:
This proposal is to extend NASA GSFC's contributions to the Carbon Monitoring System (CMS). Since its 2010 inception, these efforts by GSFC-based modeling teams have continuously provided the only complete and physically consistent set of global flux and atmospheric concentration data products to CMS. The proposed work will draw on the unique capabilities of NASA's Goddard Earth Observing System (GEOS) models and data assimilation system and consists of three main components: (i) production and refinement of observationally constrained 'bottom-up' atmosphere-ocean and atmosphere- land biosphere fluxes, and fossil fuel emissions from 2003 to 2019; (ii) production of global carbon reanalyses at unprecedented spatial resolution that incorporate multiple satellite (GOSAT, OCO-2) and in situ datasets; (iii) evaluation of 'bottom-up' flux estimates through comparison with 'top-down' inversion flux estimates. A central component of these efforts has been the use of meteorological forcing provided by NASA's Modern Era Retrospective-analysis for Research and Applications 2 (MERRA-
2) to produce a consistent picture of the interactions between weather, climate, and the carbon cycle. By extending land and ocean model-based flux estimates over a 17-year period that includes notable climatic variability, we will evaluate the ability of these models to reproduce the interannual variability of atmospheric carbon observations. These flux estimates will also incorporate a number of improvements implemented during earlier phases of CMS and refine methods of uncertainty quantification. We will use a combination of diagnostic and prognostic land biosphere models to enhance understanding of carbon flux processes. Ocean flux estimates will be further constrained through assimilation of multiple satellite ocean color observations. We will also exploit information on meteorological uncertainty produced by GMAO's new ensemble-based data assimilation system to refine transport uncertainty estimates that were provided for the first time in Phase 3 of CMS. These ocean and land fluxes, fossil fuel emissions and their associated uncertainties will be used together in the GEOS-5 carbon data assimilation system (CDAS) to produce a carbon reanalysis at 12.5-km resolution, providing the most complete, data-driven picture of atmospheric greenhouse gases to date. An important component of this effort will be to reduce the latency of flux datasets, providing information on the global carbon in support of scientific and stakeholder end- users.
Publications:
Fu, Z., Stoy, P. C., Poulter, B., Gerken, T., Zhang, Z., Wakbulcho, G., Niu, S. 2019. Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange. Global Change Biology. 25(10), 3381-3394. DOI: 10.1111/gcb.14731
Gregg, W. W., Rousseaux, C. S., Franz, B. A. 2017. Global trends in ocean phytoplankton: a new assessment using revised ocean colour data. Remote Sensing Letters. 8(12), 1102-1111. DOI: 10.1080/2150704X.2017.1354263
Oda, T., Bun, R., Kinakh, V., Topylko, P., Halushchak, M., Marland, G., Lauvaux, T., Jonas, M., Maksyutov, S., Nahorski, Z., Lesiv, M., Danylo, O., Horabik-Pyzel, J. 2019. Errors and uncertainties in a gridded carbon dioxide emissions inventory. Mitigation and Adaptation Strategies for Global Change. 24(6), 1007-1050. DOI: 10.1007/s11027-019-09877-2
Oda, T., Maksyutov, S., Andres, R. J. 2018. The Open-source Data Inventory for Anthropogenic CO<sub>2</sub>, version 2016 (ODIAC2016): a global monthly fossil fuel CO<sub>2</sub> gridded emissions data product for tracer transport simulations and surface flux inversions. Earth System Science Data. 10(1), 87-107. DOI: 10.5194/essd-10-87-2018
Wang, J. S., Oda, T., Kawa, S. R., Strode, S. A., Baker, D. F., Ott, L. E., Pawson, S. 2020. The impacts of fossil fuel emission uncertainties and accounting for 3-D chemical CO2 production on inverse natural carbon flux estimates from satellite and in situ data. Environmental Research Letters. 15(8), 085002. DOI: 10.1088/1748-9326/ab9795
Weir, B., Crisp, D., O'Dell, C. W., Basu, S., Chatterjee, A., Kolassa, J., Oda, T., Pawson, S., Poulter, B., Zhang, Z., Ciais, P., Davis, S. J., Liu, Z., Ott, L. E. 2021. Regional impacts of COVID-19 on carbon dioxide detected worldwide from space. Science Advances. 7(45). DOI: 10.1126/sciadv.abf9415
Weir, B., Ott, L. E., Collatz, G. J., Kawa, S. R., Poulter, B., Chatterjee, A., Oda, T., Pawson, S. 2021. Bias-correcting carbon fluxes derived from land-surface satellite data for retrospective and near-real-time assimilation systems. Atmospheric Chemistry and Physics. 21(12), 9609-9628. DOI: 10.5194/acp-21-9609-2021
More details may be found in the following project profile(s):
