HR: 11:50h
AN: A51H-07    [PDF]
TI: A Quantitative Method to Incorporate Atmospheric Transport Errors in Inverse Modeling Studies
AU: * Lin, J C
EM: jcl@io.harvard.edu
AF: Dept. of Earth and Planetary Sciences and Division of Engineering and Applied Sciences, Harvard University, 20 Oxford Street, Hoffman Lab, Cambridge, MA 02138 United States
AU: Gerbig, C
EM: chg@io.harvard.edu
AF: Dept. of Earth and Planetary Sciences and Division of Engineering and Applied Sciences, Harvard University, 20 Oxford Street, Hoffman Lab, Cambridge, MA 02138 United States
AU: Wofsy, S C
EM: scw@io.harvard.edu
AF: Dept. of Earth and Planetary Sciences and Division of Engineering and Applied Sciences, Harvard University, 20 Oxford Street, Hoffman Lab, Cambridge, MA 02138 United States
AU: Jin, L
EM: ljin@lbl.gov
AF: Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, CA 94720 United States
AU: Fischer, M L
EM: mlfischer@lbl.gov
AF: Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, CA 94720 United States
AB: Previous inverse studies have pointed to the sensitivity of flux estimates to errors in atmospheric transport for tracers such as CO2. Current inverse approaches either neglect transport errors or only attempt to roughly assess their effects from the spread in results derived using different transport models or from "high-frequency variability" in observed tracer concentrations. We describe a method to quantitatively account for transport errors in inverse analyses by incorporating uncertainties in mean winds into the stochastic motions of air parcels. The magnitude of errors in wind fields, as well as their spatiotemporal covariances, are determined by direct comparison of assimilated winds to radiosonde observations. The transport error statistics established by the comparisons are propagated through the stochastic motions of air parcels as simulated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model. We illustrate this method by using atmospheric CO2 observations over the continent and examine the effect of transport errors on estimates of regional terrestrial carbon fluxes.
DE: 0315 Biosphere/atmosphere interactions
DE: 0322 Constituent sources and sinks
DE: 0368 Troposphere--constituent transport and chemistry
DE: 1600 GLOBAL CHANGE (New category)
DE: 1610 Atmosphere (0315, 0325)
SC: Atmospheric Sciences [A]
MN: 2003 Fall Meeting