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Physical Sciences and Mathematics
School of Natural Resources: Faculty Publications
AmeriFlux; Carbon; Data assimilation; Eddy covariance; Flux; Measurement error; Random error; Uncertainty
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A Multi-Site Analysis Of Random Error In Tower-Based Measurements Of Carbon And Energy Fluxes, Andrew D. Richardson, David Y. Hollinger, George C. Burba, Kenneth J. Davis, Lawrence B. Flanagan, Gabriel G. Katul, J. William Munger, Daniel M. Ricciuto, Paul C. Stoy, Andrew E. Suyker, Shashi Verma, Steven C. Wofsy
A Multi-Site Analysis Of Random Error In Tower-Based Measurements Of Carbon And Energy Fluxes, Andrew D. Richardson, David Y. Hollinger, George C. Burba, Kenneth J. Davis, Lawrence B. Flanagan, Gabriel G. Katul, J. William Munger, Daniel M. Ricciuto, Paul C. Stoy, Andrew E. Suyker, Shashi Verma, Steven C. Wofsy
School of Natural Resources: Faculty Publications
Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the ‘‘true’’ flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include “tall tower” instrumentation), one grassland site, and one agricultural site, to conduct a cross-site analysis of random flux error. Quantification of this uncertainty is a prerequisite to model-data synthesis (data assimilation) and for defining confidence intervals on annual sums of net ecosystem exchange or making statistically valid comparisons between …