Time-filtered inverse modeling of land-atmosphere carbon exchange
Date
2015
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Abstract
The sources and sinks of biospheric carbon dioxide represent one of the least understood and most critical processes in carbon science. Since the 1990's, carbon dioxide inversion models have estimated the magnitude, location, and uncertainty of carbon sources and sinks. These inversions are underconstrained statistical problems that employ aggressive statistical regularizations in both space and time to estimate quantities like net ecosystem exchange (NEE) on weekly timescales over fine spatial scales. This study developed and tested a new regularization that leverages the available observational information toward a small number of estimates associated with the longer-lived slowly varying biospheric processes, which control time-averaged sources and sinks of carbon dioxide. This approach multiplicatively adjusts the longer lived component fluxes, gross primary production (GPP) and total respiration (RESP), using several timescale harmonics. This methodology was tested by estimating adjustments to either net or component fluxes from Simple Biosphere Model 4 (SiB4) using observational data from 8 different eddy-covariance flux towers selected from the North American Carbon Program (NACP) site synthesis dataset. The time-filtering methodology was robustly capable of accurately estimating both net and component fluxes given high observational uncertainty. Furthermore, the methodology was flexible of correctly producing estimates of all three fluxes when given a component flux as an additional observational constraint.
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Subject
carbon dioxide
eddy covariance
inversions
modeling