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A Comparison of Gap-filling Algorithms for Eddy Covariance Fluxes and Their Drivers by Atbin Mahabbati; Jason Beringer; Matthias Leopold; Ian McHugh; James Cleverly; Peter Isaac; Azizallah Izady is a Earth and Planetary Sciences article available to read on EtoBox.

What is A Comparison of Gap-filling Algorithms for Eddy Covariance Fluxes and Their Drivers about?

Abstract. The errors and uncertainties associated with gap-filling algorithms of water, carbon, and energy fluxes data have always been one of the main challenges of the global network of microclimatological tower sites that use the eddy covariance (EC) technique. To address these concerns and find more efficient gap-filling algorithms, we reviewed eight algorithms to estimate missing values of environmental drivers and nine algorithms for the three major fluxes typically found in EC time series. We then examined the algorithms' performance for different gap-filling scenarios utilising the data from five EC towers during 2013. This research's objectives were (a) to evaluate the impact of the gap lengths on the performance of each algorithm and (b) to compare the performance of traditional and new gap-filling techniques for the EC data, for fluxes, and separately for their corresponding meteorological drivers. The algorithms' performance was evaluated by generating nine gap windows with different lengths, ranging from a day to 365 d. In each scenario, a gap period was chosen randomly, and the data were removed from the dataset accordingly. After running each scenario, a variety of s

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Author

Atbin Mahabbati; Jason Beringer; Matthias Leopold; Ian McHugh; James Cleverly; Peter Isaac; Azizallah Izady

Publisher

Copernicus GmbH

Published

2021

Language

EN

Field

Earth and Planetary Sciences (Physical Sciences)