Calendar Event Details
Event Date: Wednesday, September 4, 2013
Location: Bldg 33, NOTE DIFFERENT ROOM G133
Time: 3:30 PM
Quantifying the observability of flux uncertainty in atmospheric CO2 records using NASA's GEOS-5 model
Although carbon dioxide is increasing in the atmosphere due to anthropogenic emissions, the rate of increase is strongly affected by the relative magnitude of land and ocean carbon fluxes. Uncertainty in our understanding of these fluxes and how they are evolving in a changing climate persists despite the fact that many components of the carbon cycle are constrained by a variety of remote sensing measurements. Observations of land surface parameters constrain estimates of carbon flux from terrestrial biosphere models while estimates of oceanic carbon fluxes are informed by satellite observations of ocean color and ocean properties. Atmospheric CO2 concentrations, which are governed by the balance of terrestrial, oceanic, and anthropogenic fluxes, are observed from space by an expanding suite of instruments in addition to being monitored by an extensive global network of surface stations. Additionally, atmospheric transport patterns simulated by NASA’s GEOS-5 data analysis system are strongly influenced by observations of atmospheric state variables. NASA’s Carbon Monitoring System Flux Pilot Project was created to quantify the constraints placed on carbon flux estimates by the current observing system and to assess what additional observational needs are required for future monitoring and attribution efforts. As part of this effort, GEOS-5 modeling studies using different combinations of observationally constrained land and ocean fluxes were used to better understand how flux uncertainty propagates in the atmosphere. Results from this ensemble of simulations are sampled at locations consistent with different types of CO2 observing systems to quantify how surface flux uncertainty may be observed in the atmosphere, and where current observing systems fail to observe significant flux differences. These modeling results are also used to better understand how potential future observing systems could contribute to reducing uncertainty in the global carbon budget.