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Changes in the Carbon Cycle Observed in Greenhouse Gas Total Columns-TCCON
Project Funding: 2017 - 2020
NRA: 2016 NASA: Carbon Cycle Science
Funded by NASA
Abstract:NASA's Carbon Cycle Science Investigation Program has historically supported the development and operations of the Total Carbon Column Observing Network (TCCON). Here, we propose to continue the coordination, maintenance, improvement and analysis of long-term measurements from the TCCON. There are currently more than 20 operational TCCON sites. All PIs of the operational TCCON sites are participants in this proposal. TCCON is both scientifically and societally important. Data from the network are being used extensively to improve the description of carbon dynamics and to help evaluate products developed from space-based sensors from the US, ESA, and JAXA. The proposed work directly addresses the critical need identified in 3.7.2, cross-cutting research activities, to provide a critical and continual evaluation of space-based data for atmospheric CO2 and CH4. TCCON provides the primary validation data for multiple existing and future US and foreign missions. TCCON is a critical source of validation data for GOSAT; for OCO-2 (launch July 2014); OCO-3 (launch 2018); and for the future ASCENDS mission. TCCON has been used in the evaluation of SCIAMACHY and MOPITT data, and is planned for use in GOSAT-2 and TropOMI aboard S-5P. We propose to use TCCON and other data sets to investigate the underlying fluxes of carbon to and from the atmosphere. Through key collaborations with members of the carbon cycle community, we will investigate variability in the flux of CO2 and CH4 using observations made from TCCON and associated data sets made by remote sensing from space.
Publications:
Hedelius, J. K., Liu, J., Oda, T., Maksyutov, S., Roehl, C. M., Iraci, L. T., Podolske, J. R., Hillyard, P. W., Liang, J., Gurney, K. R., Wunch, D., Wennberg, P. O. 2018. Southern California megacity CO<sub>2</sub>, CH<sub>4</sub>, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model. Atmospheric Chemistry and Physics. 18(22), 16271-16291. DOI: 10.5194/acp-18-16271-2018