Brian Gaudet

(Penn State, Assistant Research Professor)

Untangling CO2 fluxes and transport: using the data from ACT-America evaluate global CO2 models

What Meteo Colloquium Homepage GR
When Mar 28, 2018
from 03:30 pm to 04:30 pm
Where John Cahir Auditorium 112 Walker Building
Contact Name Steven Greybush
Contact email
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Brian Gaudet

While atmospheric greenhouse gas (GHG) concentrations continue to increase, it becomes critical to improve our understanding of their surface sources and sinks, and how these surface fluxes might be expected to change over time.  While constraints on CO2 fluxes can be derived on the global scale (through remote-site concentration measurements and global inversion models) and the local scale (through eddy-covariance flux tower measurement), observational constraints on the intermediate scales are more difficult to obtain.  The variability of CO2 concentrations over North America on regional spatial scales and seasonal-to-subseasonal temporal scales can be large, and derives from the interplay between strong diurnal and seasonal cycles of biogenic CO2 uptake, and complicated patterns of atmospheric transport due to synoptic weather systems and variations of vertical mixing processes.  Thus errors in both surface fluxes and atmosphere transport can lead to regional-scale errors in global inversion CO2 concentrations, which can be difficult to isolate from each other.

Atmospheric Carbon and Transport – America (ACT-America) is a multi-year NASA Earth Venture Suborbital project designed to increase our understanding of GHG concentrations and fluxes over North America through aircraft, satellite, and tower-based observational platforms.  This is being accomplished through a series of aircraft field campaigns that cover three focus regions (Mid-Atlantic, Gulf Coast, and Midwest), and all four seasons (summer, winter, fall, and spring), including both frontal and fair-weather conditions, from the boundary layer to the upper troposphere.  We will show examples of how B200 and C130 aircraft in situ data can be used to evaluate the skill and systematic biases of global inversion models such as CarbonTracker, and discuss implications for the flux or transport errors that could be responsible for the observed differences.