Skip to Main Content
A method to estimate the additional uncertainty in gap-filled NEE resulting from long gaps in the CO2 flux recordAuthor(s): Andrew D. Richardson; David Y. Hollinger
Source: Agricultural and Forest Meteorology. 147: 199-208.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
PDF: View PDF (497.93 KB)
DescriptionMissing values in any data set create problems for researchers. The process by which missing values are replaced, and the data set is made complete, is generally referred to as imputation. Within the eddy flux community, the term "gap filling" is more commonly applied. A major challenge is that random errors in measured data result in uncertainty in the gap-filled values. In the context of eddy covariance flux records, filling long gaps (days to weeks), which are usually the result of instrument malfunction or system failure, is especially difficult because underlying properties of the ecosystem may change over time, resulting in additional uncertainties. We used synthetic data sets, derived by assimilating data from a range of FLUXNET sites into a simple ecosystem model, to evaluate the relationship between gap length and uncertainty in net ecosystem exchange (NEE) of CO2.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationRichardson, Andrew D.; Hollinger, David Y. 2007. A method to estimate the additional uncertainty in gap-filled NEE resulting from long gaps in the CO2 flux record. Agricultural and Forest Meteorology. 147: 199-208.
Keywordsdata assimilation, ecosystem physiology, eddy covariance, gap filling, Howland, Monte Carlo, phenology, random error, uncertainty
- Current Practices in Reporting Uncertainty in Ecosystem Ecology
- Application of a dual unscented Kalman filter for simultaneous state and parameter estimation in problems of surface-atmosphere exchange
- Comparison of different objective functions for parameterization of simple respiration models
XML: View XML