A Multi-Site Analysis of Random Error in Tower-Based Measurements of Carbon and Energy Fluxes
Davis, Kenneth J.
Suyker, Andrew E.
Munger, J. William
Katul, Gabriel G.
Ricciuto, Daniel M.
Stoy, Paul C.
Flanagan, Lawrence B.
Richardson, Andrew D.
Hollinger, David Y.
Burba, George C.
Verma, Shashi B.Note: Order does not necessarily reflect citation order of authors.
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CitationRichardson, Andrew D., David Y. Hollinger, George C. Burba, Kenneth J. Davis, Lawrence B. Flanagan, Gabriel G. Katul, J. William Munger, et al. 2006. A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes. Agricultural and Forest Metereology 136(1-2): 1-18.
AbstractMeasured 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 measurements and model predictions.
We differenced paired observations (separated by exactly 24 h, under similar environmental conditions) to infer the
characteristics of the random error in measured ﬂuxes. Random ﬂux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian), distribution, and increase as a linear function of the magnitude of the ﬂux for all three scalar ﬂuxes. Across sites, variation in the random error follows consistent and robust patterns in relation to environmental variables. For example, seasonal differences in the random error for H are small, in contrast to both LE and FCO2, for which the random errors are roughly three-fold larger at the peak of the growing season compared to the dormant season. Random errors also generally scale with Rn (H and LE) and PPFD (FCO2). For FCO2 (but not H or LE), the random error decreases with increasing wind speed. Data from two sites suggest that FCO2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used.
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