Inverse modeling methods are now commonly used for
estimating surface fluxes of carbon dioxide, using atmospheric mass fraction
measurements combined with a numerical atmospheric transport model. Michalak et al. [2004] recently developed a
geostatistical approach to flux estimation that takes advantage of the spatial
and/or temporal correlation in fluxes and does not require prior flux
estimates. In this work, a
geostatistical implementation of a fixed-lag Kalman smoother is developed and
applied to the recovery of gridscale carbon dioxide fluxes for 1997 – 2001 using
data from the NOAA-CMDL Cooperative
Air Sampling Network.
Author: A.M. Michalak, K. Mueller, S. Gourdji, et al (anna dot michalak at umich dot edu)
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