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Global terrestrial atmosphere–ecosystem carbon dioxide fluxes are  well constrained by the concentration and isotopic composition of  atmospheric carbon dioxide. In contrast, considerable uncertainty  persists surrounding regional contributions to the net global flux  as well as the impacts of atmospheric and biological processes that  drive the net flux. These uncertainties severely limit our ability  to make confident predictions of future terrestrial biological  carbon fluxes. Here we use a simple light-use efficiency land  surface model (the Vegetation Photosynthesis Respiration Model,  VPRM) driven by remotely sensed temperature, moisture, and phenology  to diagnose North American gross ecosystem exchange (GEE), ecosystem  respiration, and net ecosystem exchange (NEE) for the period 2001 to  2006.  We optimize VPRM parameters to eddy covariance (EC) NEE  observations from 65 North American FluxNet sites. We use a separate  set of 27 cross-validation FluxNet sites to evaluate a range of  spatial and temporal resolutions for parameter estimation.  With  these results we demonstrate that different spatial and temporal  groupings of EC sites for parameter estimation achieve similar sum  of squared residuals values through radically different spatial  patterns of NEE. We also derive a regression model to estimate  observed VPRM errors as a function of VPRM NEE, temperature, and  precipitation. Because this estimate is based on model-observation  residuals it is comprehensive of all the error sources present in  modeled fluxes. We find that 1 km interannual variability in VPRM  NEE is of similar magnitude to estimated 1 km VPRM NEE errors

Evaluating terrestrial CO&lt;sub&gt;2&lt;/sub&gt; flux diagnoses and uncertainties from a simple land surface model and its residuals

Evaluating terrestrial CO<sub>2</sub> flux diagnoses and uncertainties from a simple land surface model and its residuals