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    Flux data are noisy, and this uncertainty is largely due to random measurement error. Knowledge of uncertainty is essential for the statistical evaluation of modeled andmeasured fluxes, for comparison of parameters derived by fitting models to measured fluxes and in formal data-assimilation efforts. We used the difference between simultaneous measurements from two towers located less than 1 km apart to quantify the distributional characteristics of the measurement error in fluxes of carbon dioxide (CO2) and sensible and latent heat (H and LE, respectively). Flux measurement error more closely follows a double exponential than a nornal distribution. The CO2 flux uncertainty is negatively correlated with mean wind speed, whereas uncertainty in H and LE is positively correlated with net radiation flux.

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    Hollinger, D.Y.; Richardson, A.D. 2005. Uncertainty in eddy covariance measurements and its application to physiological models. Tree Physiology. 25: 873-885.


    AmeriFlux, forest CO2 exchange, Howland, Monte Carlo

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