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dc.contributor.authorDavis, Kenneth J.
dc.contributor.authorSuyker, Andrew E.
dc.contributor.authorMunger, J. William
dc.contributor.authorWofsy, Steven
dc.contributor.authorKatul, Gabriel G.
dc.contributor.authorRicciuto, Daniel M.
dc.contributor.authorStoy, Paul C.
dc.contributor.authorFlanagan, Lawrence B.
dc.contributor.authorRichardson, Andrew D.
dc.contributor.authorHollinger, David Y.
dc.contributor.authorBurba, George C.
dc.contributor.authorVerma, Shashi B.
dc.date.accessioned2009-03-31T17:34:11Z
dc.date.issued2006
dc.identifier.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.en
dc.identifier.issn0168-1923en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:2764259
dc.description.abstractMeasured surface-atmosphere fluxes of energy (sensible heat, <i>H</i>, and latent heat, LE) and CO2 (<i>F</i>CO2) 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 <i>H</i> are small, in contrast to both LE and <i>F</i>CO2, 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 (<i>H</i> and LE) and PPFD (<i>F</i>CO2). For <i>F</i>CO2 (but not <i>H</i> or LE), the random error decreases with increasing wind speed. Data from two sites suggest that <i>F</i>CO2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used.en
dc.description.sponsorshipEngineering and Applied Sciencesen
dc.language.isoen_USen
dc.publisherElsevieren
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.agrformet.2006.01.007en
dash.licenseLAA
dc.subjectrandom erroren
dc.subjectfluxen
dc.subjectuncertaintyen
dc.subjectAmerifluxen
dc.subjecteddy covarianceen
dc.subjectdata assimilationen
dc.subjectmeasurement erroren
dc.subjectcarbonen
dc.titleA Multi-Site Analysis of Random Error in Tower-Based Measurements of Carbon and Energy Fluxesen
dc.typeJournal Article
dc.description.versionVersion of Record
dc.relation.journalAgricultural and Forest Meterologyen
dash.depositing.authorWofsy, Steven
dc.identifier.doi10.1016/j.agrformet.2006.01.007*
dash.authorsorderedfalse
dash.contributor.affiliatedWofsy, Steven


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