A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes

Andrew D. Richardson; David Hollinger; George G. Burba; Kenneth J. Davis; Lawrence B. Flanagan; Gabriel G. Katul; J. William Munger; Daniel M. Ricciuto; Paul C. Stoy; Andrew E. Suyker; Shashi B. Verma; Steven C. Wofsy; Steven C. Wofsy

doi:10.1016/j.agrformet.2006.01.007

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A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes

Informally Refereed

Authors:

Andrew D. Richardson, David Hollinger, George G. Burba, Kenneth J. Davis, Lawrence B. Flanagan, Gabriel G. Katul, J. William Munger, Daniel M. Ricciuto, Paul C. Stoy, Andrew E. Suyker, Shashi B. Verma, Steven C. Wofsy, Steven C. Wofsy

Year:

2006

Type:

Miscellaneous Publication

Station:

Northern Research Station

DOI:

https://doi.org/10.1016/j.agrformet.2006.01.007

Source:

Agricultural and Forest Meteorology. 136: 1-18.

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Abstract

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 measurements and model predictions.

Keywords

AmeriFlux, carbon, data assimilation, eddy covariance, flux, measurement error, random error, uncertainty

Citation

Richardson, Andrew D.; Hollinger, David Y.; Burba, George G.; Davis, Kenneth J.; Flanagan, Lawrence B.; Katul, Gabriel G.; Munger, J. William; Ricciuto, Daniel M.; Stoy, Paul C.; Suyker, Andrew E.; Verma, Shashi B.; Wofsy, Steven C. 2006. A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes. Agricultural and Forest Meteorology. 136: 1-18.