Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1111/j.1365-2486.2006.01227.x
Title (Primary) A semi-parametric gap-filling model for eddy covariance CO2 flux time series data
Author Stauch, V.J.; Jarvis, A.J.
Source Titel Global Change Biology
Year 2006
Department CLE
Volume 12
Issue 9
Page From 1707
Page To 1716
Language englisch
Keywords CO2; cubic splines; eddy covariance; gap-filling; interpolation
Abstract This paper introduces a method for modelling the deterministic component of eddy covariance CO2 flux time series in order to supplement missing data in these important data sets. The method is based on combining multidimensional semi-parametric spline interpolation with an assumed but unstated dependence of net CO2 flux on light, temperature and time. We test the model using a range of synthetic canopy data sets generated using several canopy simulation models realized for different micrometeorological and vegetation conditions. The method appears promising for filling large systematic gaps providing the associated missing data do not overerode critical information content in the conditioning data used for the model optimization.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=3049
Stauch, V.J., Jarvis, A.J. (2006):
A semi-parametric gap-filling model for eddy covariance CO2 flux time series data
Glob. Change Biol. 12 (9), 1707 - 1716 10.1111/j.1365-2486.2006.01227.x